Water quality is usually defined in terms of chemical and bacteriological purity,
particulate matter content, and endotoxin levels. Potable water is normally from
the municipal water system, which may have been treated with chlorine to control
microbiological growth. Soft water and deionized water have undergone ion
exchange or similar treatment to eliminate unwanted ionic species, such as Mg2+
and/or Ca2+. Purified water, water for injection, and other types of water meeting
compendial specifications are produced by ion exchange, reverse osmosis, distillation,
or a combination of such treatments.
The validation protocol provides a detailed description of sampling locations
and requirements, testing methodology, and test limits or specifications.
Sampling and testing can be performed daily during qualification and validation.
When the system is in routine use, following the validation the testing frequency
can be reduced to a weekly schedule for monitoring purposes.
An action guideline of not more than 10 CFUs/100 ml for bacteriological
purity is suggested. As with the purified water system, the sampling and testing
frequency for the water for injection (WFI) system is defined in the protocol
and can be reduced after the system is qualified and validated.
Sunday, January 31, 2010
Utility Qualification
Facility design is critical. Likewise, individual utilities require qualification. The
most important of these are heating, ventilation, and air conditioning (HVAC),
water (including clean steam), and compressed gases.
Typical programs begin with installation qualification (IQ). The IQ is described
in a written protocol that contains the following key elements:
1. Equipment or system specifications
2. Spare parts list
3. As-built drawings
4. Wiring diagrams
5. Piping and installation
6. Installation certification statement
Following completion of the IQ, the equipment or system is subjected to
operational qualification (OQ). This is a more rigorous exercise in which the
object is to ascertain that the equipment or system being tested performs in
accordance with design specifications throughout the full operational range(s).
The OQ protocol contains
1. A full system description
2. Calibration certification documents
3. Testing plans
4. Acceptance criteria
5. Full record of testing results
6. Certification statement
1. Heating, Ventilation, and Air Conditioning (HVAC)
Features of the HVAC system that affect product quality (sterility) and therefore
require qualification include
1. HEPA filter integrity
2. Airborne particle control
3. Airflow direction
4. Room air pressure differentials
5. Temperature and humidity control
A popular method for certifying the integrity of the filter installation uses
a polydisperse aerosol, created by blowing air through liquid (e.g., poly-alphaolefin)
introduced into the upstream ductwork, followed by scanning the entire
downstream side of the filter face and periphery with a probe nozzle of an
aerosol photometer. This testing will identify “leaks” caused by damage due to mishandling or faulty construction. Small leaks can be repaired with a suitable
silicone-based compound without removing the filter.
The importance of maintaining air pressure differentials in the enclosures
of the aseptic suite within the ranges specified in the design plans cannot be
overemphasized. Reversal of airflow, which can occur if the relative room pressures
are upset, can allow contaminated air from a noncontrolled region into the
clean room, thus defeating the purpose of the HEPA-filtered air supply.
Most enclosures in the aseptic processing suite are not airtight because of
the need for conveyor lines and pass-through openings, so there is a very real
opportunity for contamination from the noncontrolled adjacent manufacturing
areas and particularly from overhead uncontrolled technical areas.
Special monitoring devices known as Magnahelic or Photohelic gauges
measure the pressure differentials across a diaphragm and depict the value in
terms of inches of water or some other convenient scale. These instruments are
very accurate and sensitive to very small changes in pressure differential. Typically
they are connected directly to an alarm system that will cause a visual signal
(flashing light) or an audible signal (alarm buzzer) and/or trigger a recording device
to report a deviation outside a prescribed range of pressure differential.
most important of these are heating, ventilation, and air conditioning (HVAC),
water (including clean steam), and compressed gases.
Typical programs begin with installation qualification (IQ). The IQ is described
in a written protocol that contains the following key elements:
1. Equipment or system specifications
2. Spare parts list
3. As-built drawings
4. Wiring diagrams
5. Piping and installation
6. Installation certification statement
Following completion of the IQ, the equipment or system is subjected to
operational qualification (OQ). This is a more rigorous exercise in which the
object is to ascertain that the equipment or system being tested performs in
accordance with design specifications throughout the full operational range(s).
The OQ protocol contains
1. A full system description
2. Calibration certification documents
3. Testing plans
4. Acceptance criteria
5. Full record of testing results
6. Certification statement
1. Heating, Ventilation, and Air Conditioning (HVAC)
Features of the HVAC system that affect product quality (sterility) and therefore
require qualification include
1. HEPA filter integrity
2. Airborne particle control
3. Airflow direction
4. Room air pressure differentials
5. Temperature and humidity control
A popular method for certifying the integrity of the filter installation uses
a polydisperse aerosol, created by blowing air through liquid (e.g., poly-alphaolefin)
introduced into the upstream ductwork, followed by scanning the entire
downstream side of the filter face and periphery with a probe nozzle of an
aerosol photometer. This testing will identify “leaks” caused by damage due to mishandling or faulty construction. Small leaks can be repaired with a suitable
silicone-based compound without removing the filter.
The importance of maintaining air pressure differentials in the enclosures
of the aseptic suite within the ranges specified in the design plans cannot be
overemphasized. Reversal of airflow, which can occur if the relative room pressures
are upset, can allow contaminated air from a noncontrolled region into the
clean room, thus defeating the purpose of the HEPA-filtered air supply.
Most enclosures in the aseptic processing suite are not airtight because of
the need for conveyor lines and pass-through openings, so there is a very real
opportunity for contamination from the noncontrolled adjacent manufacturing
areas and particularly from overhead uncontrolled technical areas.
Special monitoring devices known as Magnahelic or Photohelic gauges
measure the pressure differentials across a diaphragm and depict the value in
terms of inches of water or some other convenient scale. These instruments are
very accurate and sensitive to very small changes in pressure differential. Typically
they are connected directly to an alarm system that will cause a visual signal
(flashing light) or an audible signal (alarm buzzer) and/or trigger a recording device
to report a deviation outside a prescribed range of pressure differential.
VALIDATION OF STERILIZING FILTERS
A. Introduction to Filtration
The following definitions will be helpful in using this section. When filter is
used as a verb (“to filter”) it means to pass a solid–liquid mixture through a
permeable medium to cause a separation of the two. Filter when used as a noun
refers to a device for carrying out filtration, and it consists of the filter medium
and a suitable holder for constraining and supporting it in the fluid path. The
permeable material that separates solid particles from the liquid being filtered
is called the filter medium. The unit operation of filtration, then, is the separation
of solids from a liquid by passage through a filter medium. In many instances,
the filter, including the permeable medium, the means for passing liquid
through the medium, and the process piping, are all referred to by the term filter
system.
In general, filtration objectives can be separated into four basic categories:
to save solids and reject liquids, to save liquids and reject solids, to save both
liquids and solids, and to reject both liquids and solids [40].
As a filtration process proceeds, generally under an applied driving force
of pressure, solids are removed by and begin to accumulate on the filter medium.
The liquid portion continues to move through the filter medium and out
of the filter system. The separated liquid is referred to as the filtrate. The amount
of pressure applied to accomplish the filtration depends on the filtration resistance.
Filtration resistance is a result of the frictional drag on the filtrate as it
passes through the filter medium and the accumulated solids. In equation form,
Filtration rate =
pressure
resistance
(13)
Permeability is often referred to as a measure of liquid flow through a filter
system and is the reciprocal of the filtration resistance.
During filtration, as the particulate buildup continues on the filtration medium,
the filtration resistance increases, or in other words, the filtration permeability
decreases. The capacity of a system, expressed in time, volume of liquid
fed, or amount of solids fed, depends on the ability of the system to maintain
acceptable permeability.
When operating a filtration system, it is important to note the following
general relationship:
Retention × permeability = constant
Therefore, in attempting to have a certain degree of filtration efficiency or retention,
a high rate of filtration, and the lowest possible cost, it is necessary to
make a compromise with one or more of the above factors. A high permeability
or low resistance for large filtration flow rates requires a filter medium of low
retention efficiency. A highly efficient retention will have low permeability, low
flow rates, and higher filtration costs.
B. Sterile Filtration
Production of parenteral drugs requires that the product be sterile. In many
cases, terminal sterilization by heat, ethylene oxide gas, or ionizing radiation is
used to render a product sterile; however, certain products are not stable when
exposed to heat, gas, or radiation, and they must be sterilized by other means.
Filtrative sterilization is suitable in such cases. Indeed, the practice of sterile
filtration is not limited to labile preparations. Unlike the other forms of sterilization,
filtration sterilizes by the removal of the bacteria from the product rather
than by inducing a lethality to the micro-organism. Filtration is straightforward
and reliable; it removes particulate matter other than microbiological; it avoids
possible pyrogenicity owing to the presence of dead bacteria in the dosage form;
it is cost effective and energy efficient; and it allows convenient and flexible
manufacturing systems and schedules with low capital investment [41].
Sterile filtration processes are employed to sterile-filter a product prior to
filling it aseptically into its final containers. Bulk drug solutions are sterilefiltered
prior to aseptic crystallization, thus eliminating the possibility of having
organisms within the bulk drug crystals. The bulk drug can then be processed
into a dosage form aseptically or further processed to be terminally sterilized.
Other filtrative operations reduce the organism content of a final product prior
to terminal sterilizations.
As noted earlier, a highly efficient retentive media will have low permeability,
low flow rates, and higher filtration costs than other less retentive filter
media. The highly retentive filter media used for sterilization have a short useful
life because they clog very easily. Consequently, most filtration processes cannot
be efficiently or economically carried out without the use of prefiltration.
Prefiltration filter media are used to protect and thus lengthen the useful life of
the final membrane filter media by collecting the bulk of the particulate material
so that the membrane filter media must filter out only a small portion of the
particulate. Prefiltration media are normally depth-filter media having a relatively
wide pore and size distribution. A properly selected prefilter must meet
the following conditions: (1) it must be retentive enough to protect the final
membrane filter medium; (2) the prefilter assembly must not allow fluid bypass
under any condition; (3) the prefilter system must be designed to make use of
the prefilter medium; (4) it must have the best retention efficiency (with depth-filter media low pressure differentials and low fluid flux, accomplished by a
multielement parallel design, are best); and (5) the prefilter medium must be
compatible with the solution and not leach components into the solution or
absorb components from the solution. One note of caution needs to be mentioned
in reference to lengthening membrane filter media life. Organism growthrough
can become a problem if filtration takes place over an extended period
of time. During filtration, bacteria continuously reproduce by cell division and
eventually find their way through the filter medium to contaminate the filtrate.
For this reason, prolonged filtration must be avoided. The proposed CGMPs for
large-volume parenterals state that final filtration of solutions shall not exceed
8 hr [42].
Sterilization by filtration is a major unit operation used in aseptic processes.
Aseptic processes require the presterilization of all components of the
drug product and its container. Then all of the components are brought together
in a controlled aseptic environment to create the finished sterile product sealed
within its container/closure system. The level of sterility attained by an aseptic
procedure is a cumulative function of all the process steps involved in making
the product. Therefore, the final level of sterility assurance for such a product
cannot be greater than the step providing the lowest probability of sterility. Each
step in the aseptic process must be validated to known levels of sterility assurance
[43].
This section will concentrate on that portion of the aseptic process wherein
the drug product is sterilized by filtration. From the earlier discussion, sterile
filtration is perhaps a misnomer, since the “sterile” filtrate is almost always
processed further under aseptic conditions, which involves a risk of contamination
[44]. Therefore, to speak of drug product sterilization by filtration as being
as final a processing step as the steam sterilization of a product could possibly
lead to erroneous assurances or assumptions. Since a sterile filtrate can be produced
by filtration, however, we will continue to refer to the process as product
sterilization by filtration.
The primary objective of a sterilizing filter is to remove microorganisms.
The filter medium used to accomplish such an efficient retention may be classified
as one of two types—the reusable type or the disposable type.
The reusable filter media are made of sintered glass, unglazed procelain,
or diatomaceous earth (Table 8). Because these filter media may be used repeatedly
without being destroyed, they are less costly; however, the use of reusable
filter media demands that the media be cleaned perfectly and sterilized prior to
use to prevent microbial contamination and chemical cross-contamination. Even
after exacting and painstaking cleaning processes have been used on reusable
filter media, most companies using sterile filtration have decided that the risk
of contamination is still great and prefer the use of the disposable media that
are used once and then discarded. The remainder of our discussion will concern
the disposable media, often referred to as membrane filter media.
Filter media consist
of a matrix of pores held in a fixed spatial relationship by a solid continuum.
The pores allow the product solution to pass through the medium while retaining
the unwanted solid particles and micro-organisms. The size of filter medium
pores to retain micro-organisms must be quite small. The 0.20- or 0.22-μm pore
size filter media are considered to be capable of producing sterile filtrates.
The characteristics of a given membrane filter medium depend on its
method of manufacture: whether by phase separation of casting solutions, by
adhesion into an organic union of matted fibers, or by track etching of solid
films [45]. The retention of micro-organisms by the various membrane media,
while not fully understood, has been investigated by numerous researchers who
have indicated that several mechanisms are responsible. The dominant mechanism
of retention is sieve retention. Particles larger than the pore size of the
filter medium are retained on the medium, and as large particles are retained,
pore openings can become bridged and thereby effectively reduce the filter medium’s
pore size. Other possible mechanisms of retention are adsorption of the
particles into the medium itself, entrapment in a tortuous path, impaction, and
electrostatic capture. [46]. The importance of these latter retention mechanisms
has not been fully determined, and on the whole filtration sterilization is treated
as depending on the steric influences of the sieve retention mechanism. The
problem with assuming a sieve retention mechanism is that a sieve or screen
has uniform openings, whereas a membrane filter medium does not. The filter
medium has a distribution of pores, albeit narrow, rather than pores of a singlesize.
In addition, thinking in terms of a sieve or screen conjures up a vision of
precisely measured and numbered openings. Precise methods for computing
both numbers and the actual sizes of pores in a filter membrane medium are not
available.
Many approaches have been taken in an attempt to measure the size of
membrane filter media pores [47,48]. Flow measurements, both of air and of
water, have been made. Mercury intrusion under high pressure has been employed,
and pore sizing using either molecular templates or particles, including
bacteria of known size, has been tried. The numerical values for pore sizes from
these methods are based on a derivation from a particular model selected. Each
of the various models has difficulties and shortcomings, and a pore size designation
based on one method does not necessarily mean that a filter medium with
the same designated size but from a different method really is the identical size
[49]. More important, relating such a designated pore size to the membrane’s
ability to retain certain size particles may be anywhere from merely uncertain
to misleading. Therefore, a given membrane filter medium with a designated
pore size of 0.2 micron should not be thought of as “absolutely retaining all
particles greater than 0.2 micron” without challenging the medium with a known
size particulate. In fact, filter media should not be thought of as “absolute retentive”
devices at all. It has been demonstrated that under certain operational
conditions or with certain bacterial challenges, 0.2 micron–rated membrane filter
media can be penetrated by bacteria. Filter media companies do challenge
their products to ensure retention efficiency to sterility [46,50–52].
In addition to the pore size–particle size retention relationship problems
mentioned above, other factors can influence a filter medium’s retention characteristics.
Absorptive retention can be influenced by the organism size, organism
population, pore size of the medium, pH of the filtrate, ionic strength, surface
tension, and organic content. Operational parameters can also influence retention,
such as flow rate, salt concentration, viscosity, temperature, filtration duration,
filtration pressure, membrane thickness, organism type, and filter medium
area [52,53].
The complexity of the sterile filtration operation and the CGMP regulations
require the validation of sterilizing filter systems. The validation of a sterile
filtration operation can be complex, with many operational parameters and
their interactions needing to be identified, controlled, and predicted for each end
product to demonstrate that sterility is adequately achieved by the filtration process.
In the commonly used steam sterilization process, the heat parameters are
identified and in-process controls specified such that a level of sterility assurance
can be reproducibly obtained. In steam sterilization, the important parameter
of heat, measured by temperature, can be accurately measured and continuously
monitored to ensure the operational integrity of the autoclave; however,
unlike steam sterilization, filtration sterilization cannot be monitored on a continuous
basis throughout the process.
The important aspect of filtration sterilization, the membrane filter me-
dium—its pore size, pore size distribution, integrity, and capacity—cannot be
monitored during use. Therefore, the prediction that a filter membrane, given a
certain set of operational parameters, will produce a sterile filter is critical. The
only way to test a membrane filter medium’s ability to retain bacteria is to
challenge the medium with bacteria. Unfortunately, after a challenge with bacteria
the filter membrane cannot be used again. Therefore, nondestructive tests
need to be developed by which a filter can be tested as to its suitability for
bacterial retention. Consequently, the approach in filter system validation has
been to establish a reproducible relationship between a membrane’s pore size
and its bacterial retention efficiency. The thinking is that once such a relation
is established, a nondestructive physical test can be developed by which each
filter membrane medium can be tested and its bacterial retention efficiency assured.
Testing of the membrane can then be performed both before and after
use, and if the test results are satisfactory, the filtration process can be deemed
to have been carried out successfully.
The following definitions will be helpful in using this section. When filter is
used as a verb (“to filter”) it means to pass a solid–liquid mixture through a
permeable medium to cause a separation of the two. Filter when used as a noun
refers to a device for carrying out filtration, and it consists of the filter medium
and a suitable holder for constraining and supporting it in the fluid path. The
permeable material that separates solid particles from the liquid being filtered
is called the filter medium. The unit operation of filtration, then, is the separation
of solids from a liquid by passage through a filter medium. In many instances,
the filter, including the permeable medium, the means for passing liquid
through the medium, and the process piping, are all referred to by the term filter
system.
In general, filtration objectives can be separated into four basic categories:
to save solids and reject liquids, to save liquids and reject solids, to save both
liquids and solids, and to reject both liquids and solids [40].
As a filtration process proceeds, generally under an applied driving force
of pressure, solids are removed by and begin to accumulate on the filter medium.
The liquid portion continues to move through the filter medium and out
of the filter system. The separated liquid is referred to as the filtrate. The amount
of pressure applied to accomplish the filtration depends on the filtration resistance.
Filtration resistance is a result of the frictional drag on the filtrate as it
passes through the filter medium and the accumulated solids. In equation form,
Filtration rate =
pressure
resistance
(13)
Permeability is often referred to as a measure of liquid flow through a filter
system and is the reciprocal of the filtration resistance.
During filtration, as the particulate buildup continues on the filtration medium,
the filtration resistance increases, or in other words, the filtration permeability
decreases. The capacity of a system, expressed in time, volume of liquid
fed, or amount of solids fed, depends on the ability of the system to maintain
acceptable permeability.
When operating a filtration system, it is important to note the following
general relationship:
Retention × permeability = constant
Therefore, in attempting to have a certain degree of filtration efficiency or retention,
a high rate of filtration, and the lowest possible cost, it is necessary to
make a compromise with one or more of the above factors. A high permeability
or low resistance for large filtration flow rates requires a filter medium of low
retention efficiency. A highly efficient retention will have low permeability, low
flow rates, and higher filtration costs.
B. Sterile Filtration
Production of parenteral drugs requires that the product be sterile. In many
cases, terminal sterilization by heat, ethylene oxide gas, or ionizing radiation is
used to render a product sterile; however, certain products are not stable when
exposed to heat, gas, or radiation, and they must be sterilized by other means.
Filtrative sterilization is suitable in such cases. Indeed, the practice of sterile
filtration is not limited to labile preparations. Unlike the other forms of sterilization,
filtration sterilizes by the removal of the bacteria from the product rather
than by inducing a lethality to the micro-organism. Filtration is straightforward
and reliable; it removes particulate matter other than microbiological; it avoids
possible pyrogenicity owing to the presence of dead bacteria in the dosage form;
it is cost effective and energy efficient; and it allows convenient and flexible
manufacturing systems and schedules with low capital investment [41].
Sterile filtration processes are employed to sterile-filter a product prior to
filling it aseptically into its final containers. Bulk drug solutions are sterilefiltered
prior to aseptic crystallization, thus eliminating the possibility of having
organisms within the bulk drug crystals. The bulk drug can then be processed
into a dosage form aseptically or further processed to be terminally sterilized.
Other filtrative operations reduce the organism content of a final product prior
to terminal sterilizations.
As noted earlier, a highly efficient retentive media will have low permeability,
low flow rates, and higher filtration costs than other less retentive filter
media. The highly retentive filter media used for sterilization have a short useful
life because they clog very easily. Consequently, most filtration processes cannot
be efficiently or economically carried out without the use of prefiltration.
Prefiltration filter media are used to protect and thus lengthen the useful life of
the final membrane filter media by collecting the bulk of the particulate material
so that the membrane filter media must filter out only a small portion of the
particulate. Prefiltration media are normally depth-filter media having a relatively
wide pore and size distribution. A properly selected prefilter must meet
the following conditions: (1) it must be retentive enough to protect the final
membrane filter medium; (2) the prefilter assembly must not allow fluid bypass
under any condition; (3) the prefilter system must be designed to make use of
the prefilter medium; (4) it must have the best retention efficiency (with depth-filter media low pressure differentials and low fluid flux, accomplished by a
multielement parallel design, are best); and (5) the prefilter medium must be
compatible with the solution and not leach components into the solution or
absorb components from the solution. One note of caution needs to be mentioned
in reference to lengthening membrane filter media life. Organism growthrough
can become a problem if filtration takes place over an extended period
of time. During filtration, bacteria continuously reproduce by cell division and
eventually find their way through the filter medium to contaminate the filtrate.
For this reason, prolonged filtration must be avoided. The proposed CGMPs for
large-volume parenterals state that final filtration of solutions shall not exceed
8 hr [42].
Sterilization by filtration is a major unit operation used in aseptic processes.
Aseptic processes require the presterilization of all components of the
drug product and its container. Then all of the components are brought together
in a controlled aseptic environment to create the finished sterile product sealed
within its container/closure system. The level of sterility attained by an aseptic
procedure is a cumulative function of all the process steps involved in making
the product. Therefore, the final level of sterility assurance for such a product
cannot be greater than the step providing the lowest probability of sterility. Each
step in the aseptic process must be validated to known levels of sterility assurance
[43].
This section will concentrate on that portion of the aseptic process wherein
the drug product is sterilized by filtration. From the earlier discussion, sterile
filtration is perhaps a misnomer, since the “sterile” filtrate is almost always
processed further under aseptic conditions, which involves a risk of contamination
[44]. Therefore, to speak of drug product sterilization by filtration as being
as final a processing step as the steam sterilization of a product could possibly
lead to erroneous assurances or assumptions. Since a sterile filtrate can be produced
by filtration, however, we will continue to refer to the process as product
sterilization by filtration.
The primary objective of a sterilizing filter is to remove microorganisms.
The filter medium used to accomplish such an efficient retention may be classified
as one of two types—the reusable type or the disposable type.
The reusable filter media are made of sintered glass, unglazed procelain,
or diatomaceous earth (Table 8). Because these filter media may be used repeatedly
without being destroyed, they are less costly; however, the use of reusable
filter media demands that the media be cleaned perfectly and sterilized prior to
use to prevent microbial contamination and chemical cross-contamination. Even
after exacting and painstaking cleaning processes have been used on reusable
filter media, most companies using sterile filtration have decided that the risk
of contamination is still great and prefer the use of the disposable media that
are used once and then discarded. The remainder of our discussion will concern
the disposable media, often referred to as membrane filter media.
Filter media consist
of a matrix of pores held in a fixed spatial relationship by a solid continuum.
The pores allow the product solution to pass through the medium while retaining
the unwanted solid particles and micro-organisms. The size of filter medium
pores to retain micro-organisms must be quite small. The 0.20- or 0.22-μm pore
size filter media are considered to be capable of producing sterile filtrates.
The characteristics of a given membrane filter medium depend on its
method of manufacture: whether by phase separation of casting solutions, by
adhesion into an organic union of matted fibers, or by track etching of solid
films [45]. The retention of micro-organisms by the various membrane media,
while not fully understood, has been investigated by numerous researchers who
have indicated that several mechanisms are responsible. The dominant mechanism
of retention is sieve retention. Particles larger than the pore size of the
filter medium are retained on the medium, and as large particles are retained,
pore openings can become bridged and thereby effectively reduce the filter medium’s
pore size. Other possible mechanisms of retention are adsorption of the
particles into the medium itself, entrapment in a tortuous path, impaction, and
electrostatic capture. [46]. The importance of these latter retention mechanisms
has not been fully determined, and on the whole filtration sterilization is treated
as depending on the steric influences of the sieve retention mechanism. The
problem with assuming a sieve retention mechanism is that a sieve or screen
has uniform openings, whereas a membrane filter medium does not. The filter
medium has a distribution of pores, albeit narrow, rather than pores of a singlesize.
In addition, thinking in terms of a sieve or screen conjures up a vision of
precisely measured and numbered openings. Precise methods for computing
both numbers and the actual sizes of pores in a filter membrane medium are not
available.
Many approaches have been taken in an attempt to measure the size of
membrane filter media pores [47,48]. Flow measurements, both of air and of
water, have been made. Mercury intrusion under high pressure has been employed,
and pore sizing using either molecular templates or particles, including
bacteria of known size, has been tried. The numerical values for pore sizes from
these methods are based on a derivation from a particular model selected. Each
of the various models has difficulties and shortcomings, and a pore size designation
based on one method does not necessarily mean that a filter medium with
the same designated size but from a different method really is the identical size
[49]. More important, relating such a designated pore size to the membrane’s
ability to retain certain size particles may be anywhere from merely uncertain
to misleading. Therefore, a given membrane filter medium with a designated
pore size of 0.2 micron should not be thought of as “absolutely retaining all
particles greater than 0.2 micron” without challenging the medium with a known
size particulate. In fact, filter media should not be thought of as “absolute retentive”
devices at all. It has been demonstrated that under certain operational
conditions or with certain bacterial challenges, 0.2 micron–rated membrane filter
media can be penetrated by bacteria. Filter media companies do challenge
their products to ensure retention efficiency to sterility [46,50–52].
In addition to the pore size–particle size retention relationship problems
mentioned above, other factors can influence a filter medium’s retention characteristics.
Absorptive retention can be influenced by the organism size, organism
population, pore size of the medium, pH of the filtrate, ionic strength, surface
tension, and organic content. Operational parameters can also influence retention,
such as flow rate, salt concentration, viscosity, temperature, filtration duration,
filtration pressure, membrane thickness, organism type, and filter medium
area [52,53].
The complexity of the sterile filtration operation and the CGMP regulations
require the validation of sterilizing filter systems. The validation of a sterile
filtration operation can be complex, with many operational parameters and
their interactions needing to be identified, controlled, and predicted for each end
product to demonstrate that sterility is adequately achieved by the filtration process.
In the commonly used steam sterilization process, the heat parameters are
identified and in-process controls specified such that a level of sterility assurance
can be reproducibly obtained. In steam sterilization, the important parameter
of heat, measured by temperature, can be accurately measured and continuously
monitored to ensure the operational integrity of the autoclave; however,
unlike steam sterilization, filtration sterilization cannot be monitored on a continuous
basis throughout the process.
The important aspect of filtration sterilization, the membrane filter me-
dium—its pore size, pore size distribution, integrity, and capacity—cannot be
monitored during use. Therefore, the prediction that a filter membrane, given a
certain set of operational parameters, will produce a sterile filter is critical. The
only way to test a membrane filter medium’s ability to retain bacteria is to
challenge the medium with bacteria. Unfortunately, after a challenge with bacteria
the filter membrane cannot be used again. Therefore, nondestructive tests
need to be developed by which a filter can be tested as to its suitability for
bacterial retention. Consequently, the approach in filter system validation has
been to establish a reproducible relationship between a membrane’s pore size
and its bacterial retention efficiency. The thinking is that once such a relation
is established, a nondestructive physical test can be developed by which each
filter membrane medium can be tested and its bacterial retention efficiency assured.
Testing of the membrane can then be performed both before and after
use, and if the test results are satisfactory, the filtration process can be deemed
to have been carried out successfully.
VALIDATION OF RADIATION STERILIZATION PROCESS
The major objective in validating a radiation sterilization process, regardless of
whether the mode of radiation is cobalt-60, cesium-137, or electron beam, is to
determine the D value of the indicator micro-organism used to monitor the process.
With radiation sterilization, the D value is defined as the dose of radiation in
Mrads or kilograys* necessary to produce a 90% reduction in the number of indicator
microbial cells. The D value depends on such factors as temperature, moisture,
organism species, oxygen tension, and the chemical environment and/or phys-
ical surface on which the indicator microorganism is present.If a probability of nonsterility of 10−6 is specified for a system sterilized by radiation and the D value of B. pumilus in that system is
0.20 Mrad, a radiation dose of 1.2 Mrads would produce a 6-log reduction in
the concentration of B. pumilus spores. Greater probability allowances (e.g.,
10−3) would permit lower radiation doses.*
The development of radiation sterilization cycles follows requirements of
the Association for the Advancement of Medical Instrumentation (AAMI) [38].
1. Determine microbial load on preirradiated products.
2. Determine the D value for natural flora on the product.
3. Determine the D value using biological indicators on the product to
make certain that the natural flora are not more radioresistant than the
biological indicator.
4. Determine the D value of biological indicator spore strips placed
within the product. Determine the location of the lowest radiation
dose point within the product. Then determine the dosage required for
a 10−6 probability of nonsterility for the product.
5. Determine whether or not the D value for the biological indicator
varies as a function of the dose rate. With cobalt-60, dose rate differences
are not of much concern (variance of 0.1–0.5 Mrad/hr), whereas
electron beam sterilization might produce dose rate variances of several
Mrads per min!
The microbiological studies above are conducted to establish the appropriate
dose level to be used to sterilize each specific product or commodity to an acceptable
level of statistical nonsterility. These studies should be conducted following
qualification of the irradiation facility. The Health Industry Manufacturers Associaton
(HIMA) [39] has suggested major items to be included in the qualification
phase of the validation scheme for radiation sterilization installation.
1. Specifications of the irradiator equipment—description, materials used,
instrumentation, etc.
2. Drawings of the equipment and the entire facility
3. Licensing agreement and supporting documentation from both the
Atomic Energy Commission and the appropriate state
4. Reliability and calibration of the dosimeter system
5. Radiation source strength when the sterilization cycle is validated
through D value determination
6. Speed of conveyor belt
7. Dose rate If it is assumed that the radiation sterilizer equipment and facilities have
been qualified and microbiological studies have been conducted as previously
outlined, the next step in the validation process is the complete evaluation of
the radiation sterilization cycle. Tests are conducted to determine the effect of
minimum and maximum product density on the ability of the minimum or nominal
radiation dose—determined during the microbiological studies to produce a
given log reduction in the biological indicator population—to sterilize the load.
For example, it was found that a 0.2-Mrad dose of cobalt-60 will produce a 1-log
reduction in the population of B. pumilus. The microbial load of a one-package
polyvinyl chloride (PVC) device (intravenous administration site) was estimated
to be approximately 1000. A probability of a nonsterility level of 10−6 is desired,
therefore theoretically, the minimum dose necessary to produce a 9-log reduction
in the microbial population is 1.8 Mrad.
Validation tests must be conducted in such a manner that the following
questions are answered:
1. Is the nominal radiation dose sufficient to destroy B. pumilus spore
samples at a relatively high concentration (e.g., 108 spores per ml or
per strip) using a minimum load of product (minimum density)?
2. Is the nominal radiation dose sufficient to destroy B. pumilus spore
samples at a relatively high concentration (e.g., 108 spores per ml or
per strip) using a maximum load of product (maximum density)?
3. What is the radiation sterilization efficiency; that is, how much of the
applied dose is actually absorbed by the product?
4. What is the isodose profile for each irradiated item; that is, what is
the dose of radiation absorbed as a function of the location within the
product being irradiated? What is the ratio between the highest and
lowest doses absorbed within the product?
5. What is the effect of conveyor loading conditions and line speeds on
the amount of radiation absorbed?
As these questions are answered, adjustments probably will be made in
the process. For example, it might be concluded that a higher radiation dose is
required for adequate exposure to all points of a particularly large and/or dense
container system. The loading size or pattern may have to be reduced to permit
adequate sterilization at a given dose level. Once all process parameters have
been defined through preliminary testing, the tedious but essential task of proving
consistency, repeatability, and reliability of the radiation sterilization cycle
must be established. Test records, data work sheets, and monitoring systems
schedules must be kept and organized for easy retrieval and analysis.
While radiation sterilization cycles are validated based upon the achievement
of sterility, many other factors must be considered in the utilization and
approval of the radiation sterilization process. Such factors include the effect of irradiation on (1) the physical appearance of the container system and its contents,
(2) stability of the active ingredient, if present, and (3) safety of the irradiated
material.
whether the mode of radiation is cobalt-60, cesium-137, or electron beam, is to
determine the D value of the indicator micro-organism used to monitor the process.
With radiation sterilization, the D value is defined as the dose of radiation in
Mrads or kilograys* necessary to produce a 90% reduction in the number of indicator
microbial cells. The D value depends on such factors as temperature, moisture,
organism species, oxygen tension, and the chemical environment and/or phys-
ical surface on which the indicator microorganism is present.If a probability of nonsterility of 10−6 is specified for a system sterilized by radiation and the D value of B. pumilus in that system is
0.20 Mrad, a radiation dose of 1.2 Mrads would produce a 6-log reduction in
the concentration of B. pumilus spores. Greater probability allowances (e.g.,
10−3) would permit lower radiation doses.*
The development of radiation sterilization cycles follows requirements of
the Association for the Advancement of Medical Instrumentation (AAMI) [38].
1. Determine microbial load on preirradiated products.
2. Determine the D value for natural flora on the product.
3. Determine the D value using biological indicators on the product to
make certain that the natural flora are not more radioresistant than the
biological indicator.
4. Determine the D value of biological indicator spore strips placed
within the product. Determine the location of the lowest radiation
dose point within the product. Then determine the dosage required for
a 10−6 probability of nonsterility for the product.
5. Determine whether or not the D value for the biological indicator
varies as a function of the dose rate. With cobalt-60, dose rate differences
are not of much concern (variance of 0.1–0.5 Mrad/hr), whereas
electron beam sterilization might produce dose rate variances of several
Mrads per min!
The microbiological studies above are conducted to establish the appropriate
dose level to be used to sterilize each specific product or commodity to an acceptable
level of statistical nonsterility. These studies should be conducted following
qualification of the irradiation facility. The Health Industry Manufacturers Associaton
(HIMA) [39] has suggested major items to be included in the qualification
phase of the validation scheme for radiation sterilization installation.
1. Specifications of the irradiator equipment—description, materials used,
instrumentation, etc.
2. Drawings of the equipment and the entire facility
3. Licensing agreement and supporting documentation from both the
Atomic Energy Commission and the appropriate state
4. Reliability and calibration of the dosimeter system
5. Radiation source strength when the sterilization cycle is validated
through D value determination
6. Speed of conveyor belt
7. Dose rate If it is assumed that the radiation sterilizer equipment and facilities have
been qualified and microbiological studies have been conducted as previously
outlined, the next step in the validation process is the complete evaluation of
the radiation sterilization cycle. Tests are conducted to determine the effect of
minimum and maximum product density on the ability of the minimum or nominal
radiation dose—determined during the microbiological studies to produce a
given log reduction in the biological indicator population—to sterilize the load.
For example, it was found that a 0.2-Mrad dose of cobalt-60 will produce a 1-log
reduction in the population of B. pumilus. The microbial load of a one-package
polyvinyl chloride (PVC) device (intravenous administration site) was estimated
to be approximately 1000. A probability of a nonsterility level of 10−6 is desired,
therefore theoretically, the minimum dose necessary to produce a 9-log reduction
in the microbial population is 1.8 Mrad.
Validation tests must be conducted in such a manner that the following
questions are answered:
1. Is the nominal radiation dose sufficient to destroy B. pumilus spore
samples at a relatively high concentration (e.g., 108 spores per ml or
per strip) using a minimum load of product (minimum density)?
2. Is the nominal radiation dose sufficient to destroy B. pumilus spore
samples at a relatively high concentration (e.g., 108 spores per ml or
per strip) using a maximum load of product (maximum density)?
3. What is the radiation sterilization efficiency; that is, how much of the
applied dose is actually absorbed by the product?
4. What is the isodose profile for each irradiated item; that is, what is
the dose of radiation absorbed as a function of the location within the
product being irradiated? What is the ratio between the highest and
lowest doses absorbed within the product?
5. What is the effect of conveyor loading conditions and line speeds on
the amount of radiation absorbed?
As these questions are answered, adjustments probably will be made in
the process. For example, it might be concluded that a higher radiation dose is
required for adequate exposure to all points of a particularly large and/or dense
container system. The loading size or pattern may have to be reduced to permit
adequate sterilization at a given dose level. Once all process parameters have
been defined through preliminary testing, the tedious but essential task of proving
consistency, repeatability, and reliability of the radiation sterilization cycle
must be established. Test records, data work sheets, and monitoring systems
schedules must be kept and organized for easy retrieval and analysis.
While radiation sterilization cycles are validated based upon the achievement
of sterility, many other factors must be considered in the utilization and
approval of the radiation sterilization process. Such factors include the effect of irradiation on (1) the physical appearance of the container system and its contents,
(2) stability of the active ingredient, if present, and (3) safety of the irradiated
material.
VALIDATION OF VAPOR PHASE HYDROGEN PEROXIDE STERILIZATION PROCESS
Vapor phase hydrogen peroxide (VPHP) is a relatively new sterilization gaseous
agent that is rapidly becoming the gaseous sterilant of choice for many applications,
the most well known being the sterilization of barrier isolation systems.
Its advantages over other gases, such as ethylene oxide, peracetic acid, chlorine
dioxide, and glutaraldehyde, include the following:
1. It does not require temperatures above ambient.
2. There is little or no concern about residual by-products.
Vapor phase hydrogen peroxide equipment and process are described elsewhere
[36]. The basic steps in the process are dehumidification, conditioning,
sterilization, and aeration. More specifically, there are five steps that must be part
of the validation protocol [36].
1. Cycle development
2. Temperature distribution
3. Vapor distribution
4. Biological challenge
5. Aeration verification
Cycle development parameters include temperature, airflow rate, humidity, liquid
peroxide concentration, liquid peroxide delivery rate, peroxide vapor delivery
temperature, and peroxide vapor half-life. Temperature distribution qualification
involves the use of temperature sensors located throughout the sterilant
delivery line and throughout the enclosure. Vapor distribution qualification uses chemical indicators to measure VPHP exposure levels. Biological challenges
involve placement of biological indicators, normally Bacillus stearothermophilus
spore strips or stainless steel coupons at many different locations inside the
enclosure, particularly in those areas most difficult for vapor to contact and
sterilize. Aeration verification determines the parameters (e.g., time, air exchange
rates) necessary to reduce VPHP levels within the system to a certain
value, usually ≤5 ppm. Vapor phase hydrogen peroxide sterilization cycles are
ultimately validated in the same way as traditional aseptic validation processes
via the use of sterile media fills.
agent that is rapidly becoming the gaseous sterilant of choice for many applications,
the most well known being the sterilization of barrier isolation systems.
Its advantages over other gases, such as ethylene oxide, peracetic acid, chlorine
dioxide, and glutaraldehyde, include the following:
1. It does not require temperatures above ambient.
2. There is little or no concern about residual by-products.
Vapor phase hydrogen peroxide equipment and process are described elsewhere
[36]. The basic steps in the process are dehumidification, conditioning,
sterilization, and aeration. More specifically, there are five steps that must be part
of the validation protocol [36].
1. Cycle development
2. Temperature distribution
3. Vapor distribution
4. Biological challenge
5. Aeration verification
Cycle development parameters include temperature, airflow rate, humidity, liquid
peroxide concentration, liquid peroxide delivery rate, peroxide vapor delivery
temperature, and peroxide vapor half-life. Temperature distribution qualification
involves the use of temperature sensors located throughout the sterilant
delivery line and throughout the enclosure. Vapor distribution qualification uses chemical indicators to measure VPHP exposure levels. Biological challenges
involve placement of biological indicators, normally Bacillus stearothermophilus
spore strips or stainless steel coupons at many different locations inside the
enclosure, particularly in those areas most difficult for vapor to contact and
sterilize. Aeration verification determines the parameters (e.g., time, air exchange
rates) necessary to reduce VPHP levels within the system to a certain
value, usually ≤5 ppm. Vapor phase hydrogen peroxide sterilization cycles are
ultimately validated in the same way as traditional aseptic validation processes
via the use of sterile media fills.
VALIDATION OF ETHYLENE OXIDE STERILIZATION CYCLES
Ethylene oxide (EtO) has been a sterilant for over 50 years. Yet, while much
attention in the literature has been focused on validation of heat sterilization
cycles, EtO cycle validation has received relatively little attention. Undoubtedly,a major reason is the inability to define accurately the kinetics of microbial
death upon exposure to EtO. This is a result of the complexity of the process,
in which not one but three variables—heat, EtO concentration, and relative humidity—
must be controlled in order to determine D values of microorganisms
when considering EtO sterilization.
The discussion of EtO validation in this section reflects largely what has
been written on this subject since 1977. Several good references [31–35] have
significantly contributed to the rationale, design, and implementation of validation
programs for EtO sterilization cycles.
Five variables are critical to the EtO process. They are EtO concentration,
relative humidity, temperature, time, and pressure/vacuum. Temperature is the
easiest variable to measure and monitor, therefore temperature is used as the indicator
of the worst-case location within the loaded EtO sterilizer. Once the worstcase
location is identified, the validation studies are conducted with the goal of
inactivating a known concentration of indicator micro-organisms in the worstcase
location using a specific loading pattern with a specific EtO cycle with all
variables defined and controlled.
The procedure for EtO cycle validation can be described in eight steps.
1. Address the products specifications and package design. What is the
chemical nature of the components of the product? Do there exist
long and/or narrow lumens that will represent barriers to EtO permeation?
How dense are the materials through which EtO gas must permeate?
What is the nature of the primary and secondary packaging?
Where are dead air spaces within the package and within the load?
By addressing questions such as these, the problems in validating the
EtO cycle can be anticipated and solved at an early stage in the validation
process.
2. Use a laboratory-sized EtO sterilizer during early phases of the validation
process as long as the sterilizer is equipped with devices allowing
variability in vacuum, relative humidity, temperature, gas pressure,
timing, and rate of gassing the chamber. Involve production sterilizer
experts in these early phases of the EtO validation process.
3. Verify the calibration of all instrumentation involved in monitoring
the EtO cycle. Examples include thermocouple and pressure gauge
calibration, gas leak testing equipment, relative humidity sensors, and
gas chromatographic instrumentation.
4. Perform an extensive temperature distribution study using an empty
sterilizer. Identify the zones of temperature extremes, then use these
locations for monitoring during loaded vessel runs. Monitoring will
be accomplished using both thermocouples and biological indicator
spore strips. The most common biological indicator for EtO cycle validation is B. subtilis var. niger. Concentration of these spores per
strip usually is 106. Significant spore survival results will indicate the
need to increase the cycle lethality parameters. It is also prudent to
analyze gas concentration at periodic intervals during the distribution
studies.
5. Do a series of repetitive runs for each sterilization cycle in an empty
vessel in order to verify the accuracy and reliability of the sterilizer
controls and monitoring equipment. Thermocouple locations should
be basically the same for all the heat-distribution studies.
6. Do a series of repetitive heat-distribution and heat-penetration runs
using a loaded EtO sterilizer. The sterilizer should be an industrial
unit in order to ascertain the cycle requirements that will yield consistent
and reliable assurance that all components of the load will be
sterile. The validation procedure should include data collected on both
partial- and full-load sizes. The loading design should be defined at
this point. Dummy loads closely resembling the actual packaging can
be used to test cyclic parameters. Thermocouples and biological indicators
should be placed in a statistically designed format throughout
the load, including areas within the dummy packaged products. The
number of loading patterns, repetitive runs, and the daily timing sequence
of events should all be based upon prior knowledge and experience.
At this point and before proceeding further, the data should
verify the following questions:
a. What is the concentration of EtO released into the vessel?
b. What is the concentration of water vapor in the vessel?
c. What is the range of temperature distribution throughout the
loaded vessel?
d. How much EtO is consumed during the cycle?
e. What are the rates of creating a vacuum and applying pressure?
f. What D value should be used for the biological indicator employed?
g. Does the selected cycle sterilize the product, and what is the estimated
probability of nonsterility?
7. Tests should be conducted on the final packaged product. The protocol
applied should be one that leads to minimal interruption of the
standard manufacturing operations of the facility. Intermediate pilot
plant studies should be carried out to simulate large-scale industrial
sterilization cycles. The EtO cycle documentation should be integrated
into a single protocol. An example of one protocol is as follows:
a. Use approximately 10 biological indicators per 100 cubic feet of
chamber space.b. Place these indicators throughout the load along with thermocouples
at the same locations.
c. Use at least three sublethal exposure cycle times, each in triplicate;
then define the required EtO exposure times using D value
calculations. The exposure time should be increased by an additional
50% to add a safety factor.
d. Perform three or more fully loaded sterilization cycles at the selected
exposure time, monitoring these cycles with thermocouples
and biological indicators.
e. Concomitantly, perform EtO residual tests on the materials exposed
to the desired exposure cycle times from full-load runs.
8. Institute a documented monitoring system primarily relying on biological
indicators, with lesser reliance on end-product sterility testing.
attention in the literature has been focused on validation of heat sterilization
cycles, EtO cycle validation has received relatively little attention. Undoubtedly,a major reason is the inability to define accurately the kinetics of microbial
death upon exposure to EtO. This is a result of the complexity of the process,
in which not one but three variables—heat, EtO concentration, and relative humidity—
must be controlled in order to determine D values of microorganisms
when considering EtO sterilization.
The discussion of EtO validation in this section reflects largely what has
been written on this subject since 1977. Several good references [31–35] have
significantly contributed to the rationale, design, and implementation of validation
programs for EtO sterilization cycles.
Five variables are critical to the EtO process. They are EtO concentration,
relative humidity, temperature, time, and pressure/vacuum. Temperature is the
easiest variable to measure and monitor, therefore temperature is used as the indicator
of the worst-case location within the loaded EtO sterilizer. Once the worstcase
location is identified, the validation studies are conducted with the goal of
inactivating a known concentration of indicator micro-organisms in the worstcase
location using a specific loading pattern with a specific EtO cycle with all
variables defined and controlled.
The procedure for EtO cycle validation can be described in eight steps.
1. Address the products specifications and package design. What is the
chemical nature of the components of the product? Do there exist
long and/or narrow lumens that will represent barriers to EtO permeation?
How dense are the materials through which EtO gas must permeate?
What is the nature of the primary and secondary packaging?
Where are dead air spaces within the package and within the load?
By addressing questions such as these, the problems in validating the
EtO cycle can be anticipated and solved at an early stage in the validation
process.
2. Use a laboratory-sized EtO sterilizer during early phases of the validation
process as long as the sterilizer is equipped with devices allowing
variability in vacuum, relative humidity, temperature, gas pressure,
timing, and rate of gassing the chamber. Involve production sterilizer
experts in these early phases of the EtO validation process.
3. Verify the calibration of all instrumentation involved in monitoring
the EtO cycle. Examples include thermocouple and pressure gauge
calibration, gas leak testing equipment, relative humidity sensors, and
gas chromatographic instrumentation.
4. Perform an extensive temperature distribution study using an empty
sterilizer. Identify the zones of temperature extremes, then use these
locations for monitoring during loaded vessel runs. Monitoring will
be accomplished using both thermocouples and biological indicator
spore strips. The most common biological indicator for EtO cycle validation is B. subtilis var. niger. Concentration of these spores per
strip usually is 106. Significant spore survival results will indicate the
need to increase the cycle lethality parameters. It is also prudent to
analyze gas concentration at periodic intervals during the distribution
studies.
5. Do a series of repetitive runs for each sterilization cycle in an empty
vessel in order to verify the accuracy and reliability of the sterilizer
controls and monitoring equipment. Thermocouple locations should
be basically the same for all the heat-distribution studies.
6. Do a series of repetitive heat-distribution and heat-penetration runs
using a loaded EtO sterilizer. The sterilizer should be an industrial
unit in order to ascertain the cycle requirements that will yield consistent
and reliable assurance that all components of the load will be
sterile. The validation procedure should include data collected on both
partial- and full-load sizes. The loading design should be defined at
this point. Dummy loads closely resembling the actual packaging can
be used to test cyclic parameters. Thermocouples and biological indicators
should be placed in a statistically designed format throughout
the load, including areas within the dummy packaged products. The
number of loading patterns, repetitive runs, and the daily timing sequence
of events should all be based upon prior knowledge and experience.
At this point and before proceeding further, the data should
verify the following questions:
a. What is the concentration of EtO released into the vessel?
b. What is the concentration of water vapor in the vessel?
c. What is the range of temperature distribution throughout the
loaded vessel?
d. How much EtO is consumed during the cycle?
e. What are the rates of creating a vacuum and applying pressure?
f. What D value should be used for the biological indicator employed?
g. Does the selected cycle sterilize the product, and what is the estimated
probability of nonsterility?
7. Tests should be conducted on the final packaged product. The protocol
applied should be one that leads to minimal interruption of the
standard manufacturing operations of the facility. Intermediate pilot
plant studies should be carried out to simulate large-scale industrial
sterilization cycles. The EtO cycle documentation should be integrated
into a single protocol. An example of one protocol is as follows:
a. Use approximately 10 biological indicators per 100 cubic feet of
chamber space.b. Place these indicators throughout the load along with thermocouples
at the same locations.
c. Use at least three sublethal exposure cycle times, each in triplicate;
then define the required EtO exposure times using D value
calculations. The exposure time should be increased by an additional
50% to add a safety factor.
d. Perform three or more fully loaded sterilization cycles at the selected
exposure time, monitoring these cycles with thermocouples
and biological indicators.
e. Concomitantly, perform EtO residual tests on the materials exposed
to the desired exposure cycle times from full-load runs.
8. Institute a documented monitoring system primarily relying on biological
indicators, with lesser reliance on end-product sterility testing.
Endotoxin Challenge in the Validation of Dry-Heat Sterilizers
The most controversial aspect of endotoxin challenge testing is how much endotoxin
challenge to use. The PDA [13] suggests using a level of endotoxin in
excess of the level expected in the item being subjected to the dry-heat cycle.
Simmons [22] suggested the use of 10,000 ng endotoxin. Akers et al. [26] used
only 10 ng endotoxin.
Papers by Ludwig et al. (27–30) expanded knowledge of dry heat depyrogenation
of glass surfaces using e. coli endotoxin challenges.
The step-by-step procedure for the endotoxin validation of a dry-heat process
may be as follows:
1. Inoculate commodity samples with a known amount of endotoxin
(e.g., 10–100 ng Escherichia coli lipopolysaccharide, obtainable from
several commercial sources). The endotoxin should be contained in a
volume of water equal to the residual water volume following the washing
procedure used prior to sterilization.
2. Thermocouples should be placed in commodities adjacent to those
containing endotoxin for temperature monitoring and correlation with
LAL test results.
3. Endotoxin destruction should be ascertained at the coolest location of
the load. Load configurations should be identical to those used in the
microbial validation studies.
4. Several endotoxin challenge samples should be done per cycle, and
the studies must be adequately replicated (3–5 repeats).
5. Following the dry-heat cycle, aseptically transfer the units containing
endotoxin to an aseptic area for extraction procedures, sampling, and
conducting the limulus amebocyte lysate (LAL) test.
6. F values required for endotoxin destruction at various temperatures
and/or cycle time–temperature variations can be determined using a
Z value of 54°C and the following equation:
Fendo. = Δt Σ 10(T−170)/54
This approach was used by Akers et al. [26].
When the validation studies described in this section have been completed,
all data are analyzed and a decision is made concerning their acceptability. If
acceptable, the entire validation procedure and all appropriate supporting data
are documented in a bound manual. If the studies are unacceptable because of
unsubstantiated claims of the process or a lack of reproducibility, further testing
must be performed or process variables changed followed by additional validation
studies.
The final document will be reviewed and approved by various plant disciplines
(engineering, microbiology, production, etc.) before the dry-heat sterilizer
is considered fully validated and released for use.
challenge to use. The PDA [13] suggests using a level of endotoxin in
excess of the level expected in the item being subjected to the dry-heat cycle.
Simmons [22] suggested the use of 10,000 ng endotoxin. Akers et al. [26] used
only 10 ng endotoxin.
Papers by Ludwig et al. (27–30) expanded knowledge of dry heat depyrogenation
of glass surfaces using e. coli endotoxin challenges.
The step-by-step procedure for the endotoxin validation of a dry-heat process
may be as follows:
1. Inoculate commodity samples with a known amount of endotoxin
(e.g., 10–100 ng Escherichia coli lipopolysaccharide, obtainable from
several commercial sources). The endotoxin should be contained in a
volume of water equal to the residual water volume following the washing
procedure used prior to sterilization.
2. Thermocouples should be placed in commodities adjacent to those
containing endotoxin for temperature monitoring and correlation with
LAL test results.
3. Endotoxin destruction should be ascertained at the coolest location of
the load. Load configurations should be identical to those used in the
microbial validation studies.
4. Several endotoxin challenge samples should be done per cycle, and
the studies must be adequately replicated (3–5 repeats).
5. Following the dry-heat cycle, aseptically transfer the units containing
endotoxin to an aseptic area for extraction procedures, sampling, and
conducting the limulus amebocyte lysate (LAL) test.
6. F values required for endotoxin destruction at various temperatures
and/or cycle time–temperature variations can be determined using a
Z value of 54°C and the following equation:
Fendo. = Δt Σ 10(T−170)/54
This approach was used by Akers et al. [26].
When the validation studies described in this section have been completed,
all data are analyzed and a decision is made concerning their acceptability. If
acceptable, the entire validation procedure and all appropriate supporting data
are documented in a bound manual. If the studies are unacceptable because of
unsubstantiated claims of the process or a lack of reproducibility, further testing
must be performed or process variables changed followed by additional validation
studies.
The final document will be reviewed and approved by various plant disciplines
(engineering, microbiology, production, etc.) before the dry-heat sterilizer
is considered fully validated and released for use.
Biological Process Validation of Dry-Heat Sterilization Cycles
If a dry-heat process is claimed to produce sterile commodities, micro-organisms
known to be most resistant to dry heat must be used to prove the ability
of the dry-heat cycle to destroy them at the coolest location in the load. If the
dry-heat process is claimed to produce both sterile and pyrogen-free commodities,
validation studies must be done using both micro-organisms and microbial
endotoxins. It is the strong opinion of many, including the authors, that biological
validation of dry-heat cycles should be based on the destruction of endotoxin
rather than on the destruction of microorganisms because of the enormous dryheat
resistance of endotoxin compared to micro-organisms [23]. To satisfy the
FDA, however, microbial challenges continue to be done.
With both micro-organism and endotoxin challenges, the cool spot identified
in the heat-distribution and heat-penetration studies will be the logical location
to run the microbial challenge tests. Containers inoculated with microbial
cells or endotoxin will be situated adjacent to identical containers into which
thermocouples are secured to monitor temperature. Temperature profiles must
not deviate from temperature data obtained in earlier studies.
The goal of the biological validation procedure depends on the nature of
the process. If the process is intended to sterilize only, the probability of survival
approach is used. In this case, validation studies must determine a dry-heat cycle
that will assure that the probability of survival of the microbial indicator is not
greater than 10−6. If the process is intended to sterilize and depyrogenate, which
occurs when the materials can withstand excessive heat, the overkill approach
is used. The goal here is to validate a heating cycle that can produce a 12-log
reduction in the biological indicator population.
Equations that apply for determining log reductions or survival probabilities
are Eq. (11) and Eq. (12), respectively. Information that must be known
prior to initiating biological validations include the D value of the biological
indicator to be used, the change in its heat resistance as temperature is changed
(Z value), and the presterilization microbial load on the commodity being steri-lized. Methods for obtaining these values have been adequately described with
ample references in the Parenteral Drug Association technical report on dry-heat
validation [13].
The most widely used biological indicators for dry heat have been spores
of B. subtilis; however, spores of other bacterial species may be used if they are
shown to have greater resistance to dry heat. At 170°C, even the most resistant
microbial spore form will have a D value of 6 to 10 min. At temperatures required
to depyrogenate, microbial spores will have D values of only a few seconds.
The acceptable Z value for microbial dry-heat resistance is 20°C [13].
This value is used primarily in programming computerized temperature-detection
devices, which take temperature data from thermocouple monitors and compute
F values as seen with Eq. (6). A suggested Z value to be used for endotoxin
dry-heat resistance is 54°C [24]. The greater Z value for endotoxin demonstrates
the greater resistance of endotoxin to dry heat.
A suggested step-by-step sequence in the microbial validation of a dryheat
process for sterilizing and depyrogenating large-volume glass containers by
a convection batch oven is presented. Procedures for the validation of a tunnel
sterilization process have been reported by Wegel [25] and Akers et al. [26].
1. The overkill approach is selected for the validation study. This eliminates
the need for bioburden and resistance studies. The objective is
to ensure that the coolest area in the loading pattern, as determined in
earlier heat-penetration and heat-distribution studies, receives sufficient
heat to cause a 12-log reduction in the biological indicator
chosen.
2. Select the type of biological indicator to be used in monitoring process
lethality. Calibrate the biological indicator in its carrier medium
(strip or suspension).
3. Place spore carrier in approximately 12 glass bottles located at the
previously determined coolest area of the oven. Bottles adjacent to
the inoculated bottles should contain thermocouples for monitoring
purposes.
4. Run a complete cycle using the desired loading pattern for future dryheat
overkill cycles.
5. After the cycle, aseptically transfer the spore strip to vessels of culture
media. If spore suspensions were used, aseptically transfer the inoculated
bottles to a laminar airflow workstation and add culture media
to the bottles. Use appropriate positive and negative controls.
6. Determine the number of survivors by plate-counting or fraction negative
methods [13].
known to be most resistant to dry heat must be used to prove the ability
of the dry-heat cycle to destroy them at the coolest location in the load. If the
dry-heat process is claimed to produce both sterile and pyrogen-free commodities,
validation studies must be done using both micro-organisms and microbial
endotoxins. It is the strong opinion of many, including the authors, that biological
validation of dry-heat cycles should be based on the destruction of endotoxin
rather than on the destruction of microorganisms because of the enormous dryheat
resistance of endotoxin compared to micro-organisms [23]. To satisfy the
FDA, however, microbial challenges continue to be done.
With both micro-organism and endotoxin challenges, the cool spot identified
in the heat-distribution and heat-penetration studies will be the logical location
to run the microbial challenge tests. Containers inoculated with microbial
cells or endotoxin will be situated adjacent to identical containers into which
thermocouples are secured to monitor temperature. Temperature profiles must
not deviate from temperature data obtained in earlier studies.
The goal of the biological validation procedure depends on the nature of
the process. If the process is intended to sterilize only, the probability of survival
approach is used. In this case, validation studies must determine a dry-heat cycle
that will assure that the probability of survival of the microbial indicator is not
greater than 10−6. If the process is intended to sterilize and depyrogenate, which
occurs when the materials can withstand excessive heat, the overkill approach
is used. The goal here is to validate a heating cycle that can produce a 12-log
reduction in the biological indicator population.
Equations that apply for determining log reductions or survival probabilities
are Eq. (11) and Eq. (12), respectively. Information that must be known
prior to initiating biological validations include the D value of the biological
indicator to be used, the change in its heat resistance as temperature is changed
(Z value), and the presterilization microbial load on the commodity being steri-lized. Methods for obtaining these values have been adequately described with
ample references in the Parenteral Drug Association technical report on dry-heat
validation [13].
The most widely used biological indicators for dry heat have been spores
of B. subtilis; however, spores of other bacterial species may be used if they are
shown to have greater resistance to dry heat. At 170°C, even the most resistant
microbial spore form will have a D value of 6 to 10 min. At temperatures required
to depyrogenate, microbial spores will have D values of only a few seconds.
The acceptable Z value for microbial dry-heat resistance is 20°C [13].
This value is used primarily in programming computerized temperature-detection
devices, which take temperature data from thermocouple monitors and compute
F values as seen with Eq. (6). A suggested Z value to be used for endotoxin
dry-heat resistance is 54°C [24]. The greater Z value for endotoxin demonstrates
the greater resistance of endotoxin to dry heat.
A suggested step-by-step sequence in the microbial validation of a dryheat
process for sterilizing and depyrogenating large-volume glass containers by
a convection batch oven is presented. Procedures for the validation of a tunnel
sterilization process have been reported by Wegel [25] and Akers et al. [26].
1. The overkill approach is selected for the validation study. This eliminates
the need for bioburden and resistance studies. The objective is
to ensure that the coolest area in the loading pattern, as determined in
earlier heat-penetration and heat-distribution studies, receives sufficient
heat to cause a 12-log reduction in the biological indicator
chosen.
2. Select the type of biological indicator to be used in monitoring process
lethality. Calibrate the biological indicator in its carrier medium
(strip or suspension).
3. Place spore carrier in approximately 12 glass bottles located at the
previously determined coolest area of the oven. Bottles adjacent to
the inoculated bottles should contain thermocouples for monitoring
purposes.
4. Run a complete cycle using the desired loading pattern for future dryheat
overkill cycles.
5. After the cycle, aseptically transfer the spore strip to vessels of culture
media. If spore suspensions were used, aseptically transfer the inoculated
bottles to a laminar airflow workstation and add culture media
to the bottles. Use appropriate positive and negative controls.
6. Determine the number of survivors by plate-counting or fraction negative
methods [13].
Tunnel Sterilizer Validation
Principles as described above for the physical process validation of batch ovens
apply also in the validation of tunnel sterilizers; however, in addition to the
variables affecting batch oven validation, tunnel sterilizers have an extra variable-
belt speed. This variable can be held constant by maintaining the same belt
speed throughout the validation process and not changing it after validation has
been compzleted.
Air Balance Determination
Proper and even air balance is more critical to a tunnel sterile process than a
batch oven process. Since the items being sterilized are moving, they are exposed
to different air systems (e.g., heating zone and cooling zone). Air flow
must be balanced in order to provide a gradual decrease in air temperature as
items move along the conveyor. In the absence of a critical balance of air dynamics,
either the items will not be cooled sufficiently once they exit the tunnel
or they will be cooled too quickly, causing the glass to shatter and contaminate
the entire tunnel area with particles. In fact, the major problem in validating tunnel sterilizers is the control of particles. Not only are the items exposed to
great extremes in temperature, but also the conveyor belt is a natural source of
particulates because metal is moving against metal.
Adjustments in the air source should be made to obtain a controlled flow
of air within the tunnel and across the entrance and exit openings. Air must be
particulate-free as it enters the tunnel area; therefore, all high efficiency particulate
air (HEPA) filters in the tunnel must be integrity tested and certified prior
to validation studies.
2. Heat-Distribution Studies
Thermocouples used in tunnel sterilizer validation must be sufficiently durable
to withstand the extremely high (≥300°C) temperatures in the heating zone area
of the tunnel. Heat-distribution studies should determine where the cold spots
are located as a function of the width of the belt and height of the tunnel chamber.
Trays or racks of ampules or vials should be run through the tunnel and
thermocouples placed at strategic locations among the containers.
Bottle-mapping studies may also be conducted during this phase [21]. The
purpose of these studies is to determine possible locations inside the container
that are most difficult to heat. The loading configuration should be identical to
what will be used in production cycles. The major difficulty in doing these
studies is the avoidance of thermocouple wire hang-ups. Thermocouples must
be long enough to be transported through the entire tunnel. A special harness
for thermocouple wires should be constructed for feeding these wires into and
throughout the tunnel.
Repeatability of the thermal process must be demonstrated during these
studies. Peak temperature readings should remain within ±10°C across the belt
for at least three replicate runs.
3. Heat-Penetration Studies'
Prior to microbial challenge testing of the tunnel sterilization, heat-penetration
studies must be completed in order to identify the coolest container in the entire
load. Results of heat-distribution studies should aid in predicting where the coolest
location within the load should be. Thermocouples should be deposited at or
near the coolest point inside the container as determined previously from bottlemapping
studies. Normally, the coolest point inside the container is at the juncture
of the bottom of the container and the sidewall. The container’s inner surface
should be in contact with the thermocouple tip because the objective is to
sterilize the inner walls of the container, as well as the inner space.
Three to five replicate runs for each commodity size and every loading
configuration should be done using 10 to 20 thermocouples distributed throughout
the load. Careful analysis of the temperature data after each run will be
invaluable in the determination of the cool spot and the repeatability of the
process using the minimum number of replicate runs.
4. Mechanical Repeatability
Tunnel sterilizers must demonstrate mechanical repeatability in the same manner
as batch ovens. Air velocity, air particulates, temperature consistency, and
reliability of all the tunnel controls (heat zone temperatures, belt speed, and
blower functions) must be proved during the physical validation studies.
apply also in the validation of tunnel sterilizers; however, in addition to the
variables affecting batch oven validation, tunnel sterilizers have an extra variable-
belt speed. This variable can be held constant by maintaining the same belt
speed throughout the validation process and not changing it after validation has
been compzleted.
Air Balance Determination
Proper and even air balance is more critical to a tunnel sterile process than a
batch oven process. Since the items being sterilized are moving, they are exposed
to different air systems (e.g., heating zone and cooling zone). Air flow
must be balanced in order to provide a gradual decrease in air temperature as
items move along the conveyor. In the absence of a critical balance of air dynamics,
either the items will not be cooled sufficiently once they exit the tunnel
or they will be cooled too quickly, causing the glass to shatter and contaminate
the entire tunnel area with particles. In fact, the major problem in validating tunnel sterilizers is the control of particles. Not only are the items exposed to
great extremes in temperature, but also the conveyor belt is a natural source of
particulates because metal is moving against metal.
Adjustments in the air source should be made to obtain a controlled flow
of air within the tunnel and across the entrance and exit openings. Air must be
particulate-free as it enters the tunnel area; therefore, all high efficiency particulate
air (HEPA) filters in the tunnel must be integrity tested and certified prior
to validation studies.
2. Heat-Distribution Studies
Thermocouples used in tunnel sterilizer validation must be sufficiently durable
to withstand the extremely high (≥300°C) temperatures in the heating zone area
of the tunnel. Heat-distribution studies should determine where the cold spots
are located as a function of the width of the belt and height of the tunnel chamber.
Trays or racks of ampules or vials should be run through the tunnel and
thermocouples placed at strategic locations among the containers.
Bottle-mapping studies may also be conducted during this phase [21]. The
purpose of these studies is to determine possible locations inside the container
that are most difficult to heat. The loading configuration should be identical to
what will be used in production cycles. The major difficulty in doing these
studies is the avoidance of thermocouple wire hang-ups. Thermocouples must
be long enough to be transported through the entire tunnel. A special harness
for thermocouple wires should be constructed for feeding these wires into and
throughout the tunnel.
Repeatability of the thermal process must be demonstrated during these
studies. Peak temperature readings should remain within ±10°C across the belt
for at least three replicate runs.
3. Heat-Penetration Studies'
Prior to microbial challenge testing of the tunnel sterilization, heat-penetration
studies must be completed in order to identify the coolest container in the entire
load. Results of heat-distribution studies should aid in predicting where the coolest
location within the load should be. Thermocouples should be deposited at or
near the coolest point inside the container as determined previously from bottlemapping
studies. Normally, the coolest point inside the container is at the juncture
of the bottom of the container and the sidewall. The container’s inner surface
should be in contact with the thermocouple tip because the objective is to
sterilize the inner walls of the container, as well as the inner space.
Three to five replicate runs for each commodity size and every loading
configuration should be done using 10 to 20 thermocouples distributed throughout
the load. Careful analysis of the temperature data after each run will be
invaluable in the determination of the cool spot and the repeatability of the
process using the minimum number of replicate runs.
4. Mechanical Repeatability
Tunnel sterilizers must demonstrate mechanical repeatability in the same manner
as batch ovens. Air velocity, air particulates, temperature consistency, and
reliability of all the tunnel controls (heat zone temperatures, belt speed, and
blower functions) must be proved during the physical validation studies.
VALIDATION OF STEAM STERILIZATION CYCLES General Considerations
The literature contains more information on steam sterilization validation than
any other process in the sterile product area. One reason was the publication of
the proposed CGMPs for LVPs in June 1976. Actually, the FDA had been
surveying the LVP industry long before the proposed CGMPs for LVP regulations
were published. One of the major areas of concern was sterility and the
heat sterilization processes for achieving sterility. Thus, at least three sections of
the proposed CGMPs for LVPs contain statements related to steam sterilization
validation. Although these regulations have not become officially and legally
valid, they are taken seriously by the parenteral industry. Table 4 summarizes
CGMP-LVP statements pertaining to steam sterilization validation.
The key expression used in steam sterilization validation is F0. Interestingly,
despite the familiarity of this term, it is still misunderstood or misused in
the parenteral industry. The main purpose of the F0 value is to express in a
single quantitative term the equivalent time at which a microbial population
having a Z value of 10°C has resided at a temperature of 121.1°C. The time
units here are not clock time units; rather, F0 time is a complete summary of
the time the indicator organism spent during the entire cycle at a temperature of
exactly 121.1°C plus a fraction of the times spent at temperatures below
121.1°C, in addition to a multiple of the times spent at temperatures greater than
121.1°C. F0 is a summation term, as exemplified in Figure 3 and Table 1. F0 is
a time value that is referenced to 121.1°C. It includes heat effects on microorganisms
during the heating and cooling phases of the cycle, taking into account
that heat effects below 121.1°C are not as powerful in destroying microbial
life as the effect found at 121.1°C.
F0 values may be calculated in several ways. The basic way is by manually
recording the temperature of the monitored product at specific time intervals,
substituting the recorded temperature for T in Eq. (7), solving the exponential
part of the equation for all temperatures recorded, and then multiplying by Δt.
This was done in Table 1. Alternatively, and more expediently, a computer
program can integrate the temperature and time data to obtain the F0 value.
This approach is now widely used because of the availability of programmable
multipoint recorders that record temperature and solve the F0 equation on an
accumulative basis.
any other process in the sterile product area. One reason was the publication of
the proposed CGMPs for LVPs in June 1976. Actually, the FDA had been
surveying the LVP industry long before the proposed CGMPs for LVP regulations
were published. One of the major areas of concern was sterility and the
heat sterilization processes for achieving sterility. Thus, at least three sections of
the proposed CGMPs for LVPs contain statements related to steam sterilization
validation. Although these regulations have not become officially and legally
valid, they are taken seriously by the parenteral industry. Table 4 summarizes
CGMP-LVP statements pertaining to steam sterilization validation.
The key expression used in steam sterilization validation is F0. Interestingly,
despite the familiarity of this term, it is still misunderstood or misused in
the parenteral industry. The main purpose of the F0 value is to express in a
single quantitative term the equivalent time at which a microbial population
having a Z value of 10°C has resided at a temperature of 121.1°C. The time
units here are not clock time units; rather, F0 time is a complete summary of
the time the indicator organism spent during the entire cycle at a temperature of
exactly 121.1°C plus a fraction of the times spent at temperatures below
121.1°C, in addition to a multiple of the times spent at temperatures greater than
121.1°C. F0 is a summation term, as exemplified in Figure 3 and Table 1. F0 is
a time value that is referenced to 121.1°C. It includes heat effects on microorganisms
during the heating and cooling phases of the cycle, taking into account
that heat effects below 121.1°C are not as powerful in destroying microbial
life as the effect found at 121.1°C.
F0 values may be calculated in several ways. The basic way is by manually
recording the temperature of the monitored product at specific time intervals,
substituting the recorded temperature for T in Eq. (7), solving the exponential
part of the equation for all temperatures recorded, and then multiplying by Δt.
This was done in Table 1. Alternatively, and more expediently, a computer
program can integrate the temperature and time data to obtain the F0 value.
This approach is now widely used because of the availability of programmable
multipoint recorders that record temperature and solve the F0 equation on an
accumulative basis.
Methods of Sterilization of Sterile Products
Heat
1. Moist heat (steam) = saturated steam under pressure =
autoclave
2. Dry heat = oven or tunnel
Gas
1. Ethylene oxide
2. Peracetic acid
3. Vapor phase hydrogen peroxide
4. Chlorine dioxide
Radiation
1. Gamma
2. Beta
3. Ultraviolet
4. Microwave
Light
1. PureBright
Filtration
1. Moist heat (steam) = saturated steam under pressure =
autoclave
2. Dry heat = oven or tunnel
Gas
1. Ethylene oxide
2. Peracetic acid
3. Vapor phase hydrogen peroxide
4. Chlorine dioxide
Radiation
1. Gamma
2. Beta
3. Ultraviolet
4. Microwave
Light
1. PureBright
Filtration
BASIC PRINCIPLES IN THE VALIDATION OF STERILE PRODUCTS Theoretical Approaches
Generally, five basic steps are necessary to validate any manufacturing process
[15].
1. Written documentation
2. Manufacturing parameters
3. Testing parameters
4. In-process controls
5. Final product testing
In sterile product manufacturing, five major steps are involved in approaching
the validation of a sterile process. These are outlined below using thermal sterilization
as the example process.
1. Select or define the desired attributes of the product. Example: The
product will be sterile.
2. Determine specifications for the desired attributes. Example: The
product will be sterilized by a sterilization process sufficient to produce
a probability of nonsterility of one out of 1 million containers
(10−6).
3. Select the appropriate processes and equipment. Example: Use microbial
kinetic equations such as Eq. (11) to determine the probability
of nonsterility. Select cleaning equipment and container component procedures designed and validated to reduce the product bioburden to
the lowest practical level. Select an autoclave that can be validated in
terms of correct operation of all mechanical controls. Use the appropriate
types of thermocouples, thermal sensing devices, biological indicators,
integrated chemical indicators, and culture media to conduct
the validation tests.
4. Develop and conduct tests that evaluate and monitor the processes,
equipment, and personnel.
Examples:
a. Determine microbial load counts prior to container filling.
b. Determine D and Z values of biological indicator organism.
c. Perform heat distribution studies of empty and loaded autoclave.
d. Perform heat penetration studies of product at various locations
in the batch.
5. Examine the test procedures themselves to ensure their accuracy and
reliability.
Examples:
a. Accuracy of thermocouples as a function of variances in time and
temperature.
b. Repeatability of the autoclave cycle in terms of temperature and
F value consistency.
c. A challenge of the sterilization cycle with varying levels of bioindicator
organisms.
d. Reliability of cleaning processes to produce consistent low-level
product bioburdens.
Each validation process should have a documented protocol of the steps
to follow and the data to collect during the experimentation. As an example,
App. I presents a protocol for the validation of a steam sterilization process.
Upon completion of the experimental phase of validation, the data are
compiled and evaluated by qualified scientific personnel. The results may be
summarized on a summary sheet, an example of which is shown in Table 2.
Once a process has been validated, it must be controlled to assure that the
process consistently produces a product within the specifications established by
the validation studies. As shown in Table 2, documentation should present original
validation records, a schedule of revalidation dates, and data from the revalidation
studies. The interval between validation studies strictly depends on the
judgment of the validation team based on the experience and history of the
consistency of the process.
Table 3 lists the sterilization methods used for sterile products. There are
five basic methods—heat, gas, radiation, light, and filtration. The first four
methods destroy microbial life, while filtration removes micro-organisms. Vali-dation approaches and procedures used for most of these methods will be addressed
in the remainder of this chapter. Gaseous validation and radiation validation
approaches will be focused on ethylene oxide and gamma radiation,
respectively. The other gaseous and radiation methods, however, generally will
follow the same principles as those discussed for ethylene oxide and gamma radiation. Some extra coverage will be given to vapor phase hydrogen peroxide
because of its increased application, particularly in the sterilization of barrier
isolators.
[15].
1. Written documentation
2. Manufacturing parameters
3. Testing parameters
4. In-process controls
5. Final product testing
In sterile product manufacturing, five major steps are involved in approaching
the validation of a sterile process. These are outlined below using thermal sterilization
as the example process.
1. Select or define the desired attributes of the product. Example: The
product will be sterile.
2. Determine specifications for the desired attributes. Example: The
product will be sterilized by a sterilization process sufficient to produce
a probability of nonsterility of one out of 1 million containers
(10−6).
3. Select the appropriate processes and equipment. Example: Use microbial
kinetic equations such as Eq. (11) to determine the probability
of nonsterility. Select cleaning equipment and container component procedures designed and validated to reduce the product bioburden to
the lowest practical level. Select an autoclave that can be validated in
terms of correct operation of all mechanical controls. Use the appropriate
types of thermocouples, thermal sensing devices, biological indicators,
integrated chemical indicators, and culture media to conduct
the validation tests.
4. Develop and conduct tests that evaluate and monitor the processes,
equipment, and personnel.
Examples:
a. Determine microbial load counts prior to container filling.
b. Determine D and Z values of biological indicator organism.
c. Perform heat distribution studies of empty and loaded autoclave.
d. Perform heat penetration studies of product at various locations
in the batch.
5. Examine the test procedures themselves to ensure their accuracy and
reliability.
Examples:
a. Accuracy of thermocouples as a function of variances in time and
temperature.
b. Repeatability of the autoclave cycle in terms of temperature and
F value consistency.
c. A challenge of the sterilization cycle with varying levels of bioindicator
organisms.
d. Reliability of cleaning processes to produce consistent low-level
product bioburdens.
Each validation process should have a documented protocol of the steps
to follow and the data to collect during the experimentation. As an example,
App. I presents a protocol for the validation of a steam sterilization process.
Upon completion of the experimental phase of validation, the data are
compiled and evaluated by qualified scientific personnel. The results may be
summarized on a summary sheet, an example of which is shown in Table 2.
Once a process has been validated, it must be controlled to assure that the
process consistently produces a product within the specifications established by
the validation studies. As shown in Table 2, documentation should present original
validation records, a schedule of revalidation dates, and data from the revalidation
studies. The interval between validation studies strictly depends on the
judgment of the validation team based on the experience and history of the
consistency of the process.
Table 3 lists the sterilization methods used for sterile products. There are
five basic methods—heat, gas, radiation, light, and filtration. The first four
methods destroy microbial life, while filtration removes micro-organisms. Vali-dation approaches and procedures used for most of these methods will be addressed
in the remainder of this chapter. Gaseous validation and radiation validation
approaches will be focused on ethylene oxide and gamma radiation,
respectively. The other gaseous and radiation methods, however, generally will
follow the same principles as those discussed for ethylene oxide and gamma radiation. Some extra coverage will be given to vapor phase hydrogen peroxide
because of its increased application, particularly in the sterilization of barrier
isolators.
PROCESS OF MICROBIAL DESTRUCTION
Regardless of the type of lethality induced by a sterilization process—whether
it be heat, chemical, or radiation—micro-organisms, upon exposure to adequate
levels of such treatments, will die according to a logarithmic relationship between
the concentration or population of living cells and the time exposure or
radiation dose to the treatment.
A. D Value
The D value is a single quantitative expression of the rate of killing of microorganisms.
The D term refers to the decimal point in which microbial death
rates become positive time values by determining the time required to reduce
the microbial population by one decimal point. This is also the time required
for a 90% reduction in the microbial population. Hence, the time or dose it takes
to reduce 1000 microbial cells to 100 cells is the D value. The D value is
important in the validation of sterilization processes for several reasons.
1. It is a specific kinetic expression for each micro-organism in a specific
environment subjected to a specific sterilization agent or condition.
In other words, the D value will be affected by
a. The type of microorganism used as the biological indicator.*
b. The formulation components and characteristics (e.g., pH).
c. The surface on which the micro-organism is exposed (glass, steel,
plastic, rubber, in solution, dry powder, etc.).
d. The temperature, gas concentration, or radiation dose of the particular
sterilization process.*
2. Knowledge of the D value at different temperatures in heat sterilization
is necessary for the calculation of the Z value. (See p. 87.)
3. The D value is used in the calculation of the biological F value. (See
p. 87.)
4. Extrapolation of the D value from large microbial population values
to fractional (e.g., 10−x) values predicts the number of log reductions
a given exposure period will produce.
D values are determined experimentally by either of two methods, the
survivor-curve method or the fraction-negative method [7,8]. The survivor-curve
method is based on plotting the log number of surviving organisms versus an
independent variable such as time, gas concentration, or radiation dose. The
fraction-negative method uses replicate samples containing identical spore populations
treated in an identical manner and determining the number (fraction) of
samples still showing microbial growth after treatment and incubation. Fractionnegative
data are used primarily for determining D values of micro-organisms
exposed to thermal destruction processes. The following discussion concentrates
on D values calculated by the survivor-curve method.
Data obtained by the survivor-curve method are plotted semilogarithmically.
Data points are connected by least-squares analysis. In most cases the
equation used is the first-order death rate equation,
log N = a + bt (1)
where N is the number of surviving organisms of time t, a is the Y intercept,
and b is the slope of the line as determined by linear regression. The D value is
the reciprocal of the linear slope,
D = 1
b
(2)
Many micro-organisms produce nonlinear survivor curves, such as 1-B in Figure
1. The cause of nonlinear survivor curves has been explained by several theories,
such as the multiple critical sites theory [9], experimental artifacts [10],
and the heterogeneity of spore heat resistance [11]. Mathematical models for
concave survivor curves have been developed by Han et al. [12]. They are quite
it be heat, chemical, or radiation—micro-organisms, upon exposure to adequate
levels of such treatments, will die according to a logarithmic relationship between
the concentration or population of living cells and the time exposure or
radiation dose to the treatment.
A. D Value
The D value is a single quantitative expression of the rate of killing of microorganisms.
The D term refers to the decimal point in which microbial death
rates become positive time values by determining the time required to reduce
the microbial population by one decimal point. This is also the time required
for a 90% reduction in the microbial population. Hence, the time or dose it takes
to reduce 1000 microbial cells to 100 cells is the D value. The D value is
important in the validation of sterilization processes for several reasons.
1. It is a specific kinetic expression for each micro-organism in a specific
environment subjected to a specific sterilization agent or condition.
In other words, the D value will be affected by
a. The type of microorganism used as the biological indicator.*
b. The formulation components and characteristics (e.g., pH).
c. The surface on which the micro-organism is exposed (glass, steel,
plastic, rubber, in solution, dry powder, etc.).
d. The temperature, gas concentration, or radiation dose of the particular
sterilization process.*
2. Knowledge of the D value at different temperatures in heat sterilization
is necessary for the calculation of the Z value. (See p. 87.)
3. The D value is used in the calculation of the biological F value. (See
p. 87.)
4. Extrapolation of the D value from large microbial population values
to fractional (e.g., 10−x) values predicts the number of log reductions
a given exposure period will produce.
D values are determined experimentally by either of two methods, the
survivor-curve method or the fraction-negative method [7,8]. The survivor-curve
method is based on plotting the log number of surviving organisms versus an
independent variable such as time, gas concentration, or radiation dose. The
fraction-negative method uses replicate samples containing identical spore populations
treated in an identical manner and determining the number (fraction) of
samples still showing microbial growth after treatment and incubation. Fractionnegative
data are used primarily for determining D values of micro-organisms
exposed to thermal destruction processes. The following discussion concentrates
on D values calculated by the survivor-curve method.
Data obtained by the survivor-curve method are plotted semilogarithmically.
Data points are connected by least-squares analysis. In most cases the
equation used is the first-order death rate equation,
log N = a + bt (1)
where N is the number of surviving organisms of time t, a is the Y intercept,
and b is the slope of the line as determined by linear regression. The D value is
the reciprocal of the linear slope,
D = 1
b
(2)
Many micro-organisms produce nonlinear survivor curves, such as 1-B in Figure
1. The cause of nonlinear survivor curves has been explained by several theories,
such as the multiple critical sites theory [9], experimental artifacts [10],
and the heterogeneity of spore heat resistance [11]. Mathematical models for
concave survivor curves have been developed by Han et al. [12]. They are quite
Sterilization Validation INTRODUCTION
Sterile products have several unique dosage form properties, such as freedom
from micro-organisms, freedom from pyrogens, freedom from particulates, and
extremely high standards of purity and quality; however, the ultimate goal in
the manufacture of a sterile product is absolute absence of microbial contamination.
The emphasis of this chapter will be the validation of the sterilization
processes responsible for achieving this goal.
Unlike many dosage form specifications, the sterility specification is an
absolute value. A product is either sterile or nonsterile. Historically, judgment
of sterility has relied on an official compendial sterility test; however, endproduct
sterility testing suffers from a myriad of limitations [1–4]. The most
obvious limitation is the nature of the sterility test. It is a destructive test; thus,
it depends on the statistical selection of a random sample of the whole lot.
Uncertainty will always exist as to whether or not the sample unequivocally
represents the whole. If it were known that one unit out of 1000 units was
contaminated (i.e., contamination rate = 0.1%) and 20 units were randomly sampled
out of those 1000 units, the probability of that one contaminated unit being
included in those 20 samples is 0.02 [5]. In other words, the chances are only
2% that the contaminated unit would be selected as part of the 20 representative
samples of the whole 1000-unit lot.
Even if the contaminated unit were one of the 20 samples selected for the
sterility test, the possibility still exists that the sterility test would fail to detect the contamination. The microbial contaminant might be at too low a concentration
to be detectable during the incubation period or might not grow rapidly
enough or at all because of media and incubation insufficiencies.
If microbial growth is detected in a sterility test, this may reflect a falsepositive
reading because of the problem of accidental contamination of the culture
media while performing the sterility test. The problem of accidental contamination
is a serious yet unavoidable limitation of the sterility test.
The Food and Drug Administration (FDA) published guidelines pertaining
to general principles of process validation [6]. General concepts and key elements
of process validation considered acceptable by the FDA were outlined. A
major point stressed in the guidelines was the insufficiency of relying solely on
end-product sterility testing alone in ascertaining the sterility of a parenteral of
a sterile product lot. Greater significance should be placed on process validation
of all systems involved in producing the final product.
These major limitations demonstrate that reliance on end-product sterility
testing alone in ascertaining the sterility of a parenteral product may lead to
erroneous results. One purpose of validation in the manufacture of sterile products
is to minimize this reliance on end-product testing. Three principles are
involved in the validation process for sterile product.
1. To build sterility into a product
2. To demonstrate to a certain maximum level of probability that the
processing and sterilization methods have established sterility to all
units of a product batch
3. To provide greater assurance and support of the results of the endproduct
sterility test
Validation of sterile products in the context of this chapter will refer to the
confirmation that a product has been exposed to the appropriate manufacturing
processes and especially to the appropriate sterilization method yielding a batch
of product having a known degree of nonsterility.
from micro-organisms, freedom from pyrogens, freedom from particulates, and
extremely high standards of purity and quality; however, the ultimate goal in
the manufacture of a sterile product is absolute absence of microbial contamination.
The emphasis of this chapter will be the validation of the sterilization
processes responsible for achieving this goal.
Unlike many dosage form specifications, the sterility specification is an
absolute value. A product is either sterile or nonsterile. Historically, judgment
of sterility has relied on an official compendial sterility test; however, endproduct
sterility testing suffers from a myriad of limitations [1–4]. The most
obvious limitation is the nature of the sterility test. It is a destructive test; thus,
it depends on the statistical selection of a random sample of the whole lot.
Uncertainty will always exist as to whether or not the sample unequivocally
represents the whole. If it were known that one unit out of 1000 units was
contaminated (i.e., contamination rate = 0.1%) and 20 units were randomly sampled
out of those 1000 units, the probability of that one contaminated unit being
included in those 20 samples is 0.02 [5]. In other words, the chances are only
2% that the contaminated unit would be selected as part of the 20 representative
samples of the whole 1000-unit lot.
Even if the contaminated unit were one of the 20 samples selected for the
sterility test, the possibility still exists that the sterility test would fail to detect the contamination. The microbial contaminant might be at too low a concentration
to be detectable during the incubation period or might not grow rapidly
enough or at all because of media and incubation insufficiencies.
If microbial growth is detected in a sterility test, this may reflect a falsepositive
reading because of the problem of accidental contamination of the culture
media while performing the sterility test. The problem of accidental contamination
is a serious yet unavoidable limitation of the sterility test.
The Food and Drug Administration (FDA) published guidelines pertaining
to general principles of process validation [6]. General concepts and key elements
of process validation considered acceptable by the FDA were outlined. A
major point stressed in the guidelines was the insufficiency of relying solely on
end-product sterility testing alone in ascertaining the sterility of a parenteral of
a sterile product lot. Greater significance should be placed on process validation
of all systems involved in producing the final product.
These major limitations demonstrate that reliance on end-product sterility
testing alone in ascertaining the sterility of a parenteral product may lead to
erroneous results. One purpose of validation in the manufacture of sterile products
is to minimize this reliance on end-product testing. Three principles are
involved in the validation process for sterile product.
1. To build sterility into a product
2. To demonstrate to a certain maximum level of probability that the
processing and sterilization methods have established sterility to all
units of a product batch
3. To provide greater assurance and support of the results of the endproduct
sterility test
Validation of sterile products in the context of this chapter will refer to the
confirmation that a product has been exposed to the appropriate manufacturing
processes and especially to the appropriate sterilization method yielding a batch
of product having a known degree of nonsterility.
SELECTION AND EVALUATION OF PACKAGING DATA
To this point retrospective validation has been discussed in the context of dosage
form manufacture. Some of the same concepts may be applied to validating a
packaging operation. Consider the following. Packaging lines are typically controlled
by making spot observations to confirm machinery performance and component usage. The frequency of the inspections and the number of samples
examined during each cycle are normally defined in a written procedure. Furthermore,
the results of each monitor are generally documented in an inspection
report, which becomes part of the packaging record for that lot of product. Also
available from the packaging record is the number of units produced, thus the
information needed to allow inferences about the reliability of a particular operation
is readily accessible.
If we can show that over an extended period of time an operation had a
certain reliability, it is not unreasonable to expect the same level of performance
for the future as long as the equipment is reasonably maintained. Conversely,
any conclusion reached by such a study would be invalidated by substantial
change to the equipment or its method of operation.
How many packaging runs must be examined to draw a sound conclusion
about the reliability of the operation? Unfortunately, no one answer is appropriate
for every situation, but there are some rules that will aid the decision
process. The sample size should be large enough to capture all variables normally
experienced; for instance, routine machine problems, shift and personnel
changes, component vendor differences, and seasonal conditions. Furthermore,
the sample must be of sufficient size to provide a high degree of confidence in
the conclusion. Ten thousand observations made over 6 to 12 months of continuous
production generally satisfy these requirements. For high-speed, multipleshift
operations the 10,000-observation figure is likely to be reached well before
sufficient time has elapsed to include all avenues of variability. In these cases,
time rather than units produced should be the first consideration.
To validate an aspect of the packaging operation retrospectively the following
information must be tabulated:
1. The total number of observations made for the quality attribute under
review
2. The total number of nonconformances detected by the inspection process
form manufacture. Some of the same concepts may be applied to validating a
packaging operation. Consider the following. Packaging lines are typically controlled
by making spot observations to confirm machinery performance and component usage. The frequency of the inspections and the number of samples
examined during each cycle are normally defined in a written procedure. Furthermore,
the results of each monitor are generally documented in an inspection
report, which becomes part of the packaging record for that lot of product. Also
available from the packaging record is the number of units produced, thus the
information needed to allow inferences about the reliability of a particular operation
is readily accessible.
If we can show that over an extended period of time an operation had a
certain reliability, it is not unreasonable to expect the same level of performance
for the future as long as the equipment is reasonably maintained. Conversely,
any conclusion reached by such a study would be invalidated by substantial
change to the equipment or its method of operation.
How many packaging runs must be examined to draw a sound conclusion
about the reliability of the operation? Unfortunately, no one answer is appropriate
for every situation, but there are some rules that will aid the decision
process. The sample size should be large enough to capture all variables normally
experienced; for instance, routine machine problems, shift and personnel
changes, component vendor differences, and seasonal conditions. Furthermore,
the sample must be of sufficient size to provide a high degree of confidence in
the conclusion. Ten thousand observations made over 6 to 12 months of continuous
production generally satisfy these requirements. For high-speed, multipleshift
operations the 10,000-observation figure is likely to be reached well before
sufficient time has elapsed to include all avenues of variability. In these cases,
time rather than units produced should be the first consideration.
To validate an aspect of the packaging operation retrospectively the following
information must be tabulated:
1. The total number of observations made for the quality attribute under
review
2. The total number of nonconformances detected by the inspection process
RELIABILITY OF THE VALIDATED PROCESS
Once the process has been validated, controls must be put into place to make
certain that operations continue to be performed as originally described. It is unreasonable
to assume that machines, instruments, plant services, and personnel will
remain static indefinitely. The FDA recognized the need for revalidation when it
issued the process validation guidelines [1]. A number of resources are available
to monitor for process drift. The quality assurance department can perform periodic
audits of manufacturing and laboratory practices against official procedures, review
equipment maintenance records including calibration history, and examine personnel
training programs. Any departures from original assumptions must be brought
to the attention of the validation team for evaluation of their impact on the process.
The CGMPs require the manufacturer of a product to conduct an annual
review of written records to evaluate product quality [6]. A number of authors have suggested that when done properly the review can highlight trends that
might otherwise go unnoticed. Lee discusses how analytical and production data,
as well as product complaint experience, can be arranged or collated for this
purpose [19]. The annual review would be an expedient means of monitoring
the conclusions reached during validation.
When planned changes are made to the process, equipment, or immediate
operating environment, the validation team should carefully assess the nature of
the change for its impact on different aspects of the process. It may not be
necessary to revalidate the entire process in cases in which the change can be
shown to be isolated [1]. There may be an opportunity to supplement the historical
experience with a prospective study specific to the planned change. To ensure
that this review occurs, a formal change control system must be in place.
It would also be appropriate to have in place a written plan describing the
company functions that have responsibility for monitoring the process.
certain that operations continue to be performed as originally described. It is unreasonable
to assume that machines, instruments, plant services, and personnel will
remain static indefinitely. The FDA recognized the need for revalidation when it
issued the process validation guidelines [1]. A number of resources are available
to monitor for process drift. The quality assurance department can perform periodic
audits of manufacturing and laboratory practices against official procedures, review
equipment maintenance records including calibration history, and examine personnel
training programs. Any departures from original assumptions must be brought
to the attention of the validation team for evaluation of their impact on the process.
The CGMPs require the manufacturer of a product to conduct an annual
review of written records to evaluate product quality [6]. A number of authors have suggested that when done properly the review can highlight trends that
might otherwise go unnoticed. Lee discusses how analytical and production data,
as well as product complaint experience, can be arranged or collated for this
purpose [19]. The annual review would be an expedient means of monitoring
the conclusions reached during validation.
When planned changes are made to the process, equipment, or immediate
operating environment, the validation team should carefully assess the nature of
the change for its impact on different aspects of the process. It may not be
necessary to revalidate the entire process in cases in which the change can be
shown to be isolated [1]. There may be an opportunity to supplement the historical
experience with a prospective study specific to the planned change. To ensure
that this review occurs, a formal change control system must be in place.
It would also be appropriate to have in place a written plan describing the
company functions that have responsibility for monitoring the process.
USING VALIDATION EXPERIENCE TO SET PRODUCT ALERT LIMITS
Experience gained during validation can be used to fine-tune the process for
greater reliability. Several examples of changes being recommended based on
study findings may be found in the section of this chapter devoted to evaluation
of process data. Another application of the information gathered during validation
is in setting alert limits to be incorporated into the mechanism for product
release. The alert limits would be the control limits (UCL and LCL) calculated
as part of the review process for each analytical test; they could be made part
of the written specifications for product release.
The recommendation to use control limits calculated as part of validation
as alert limits is based on the expectation that test results from future production
should normally fall within these limits. Indeed, this is the essence of retrospective
validation. Furthermore, for a stable, centered process the control limits
would fall within the release specification for the test. Exceeding an alert limit
therefore would not necessarily delay product release but could precipitate an
investigation into the cause.
Requiring quality control to use validation experience to release product
achieves two objectives: it monitors conclusions reached during validation for
ongoing reliability and identifies a trend early before a rejection occurs. For
quality control laboratories using a laboratory information management system
(LIMS), routine performance of test result-alert limit comparisons can be automated.
Where such a system is not available, manually recorded test results
could be transferred to a stand-alone computer for trend analysis. An x¯ plot
depicting the process in relation to the alert and specification limits should be
considered for monitoring trends.
greater reliability. Several examples of changes being recommended based on
study findings may be found in the section of this chapter devoted to evaluation
of process data. Another application of the information gathered during validation
is in setting alert limits to be incorporated into the mechanism for product
release. The alert limits would be the control limits (UCL and LCL) calculated
as part of the review process for each analytical test; they could be made part
of the written specifications for product release.
The recommendation to use control limits calculated as part of validation
as alert limits is based on the expectation that test results from future production
should normally fall within these limits. Indeed, this is the essence of retrospective
validation. Furthermore, for a stable, centered process the control limits
would fall within the release specification for the test. Exceeding an alert limit
therefore would not necessarily delay product release but could precipitate an
investigation into the cause.
Requiring quality control to use validation experience to release product
achieves two objectives: it monitors conclusions reached during validation for
ongoing reliability and identifies a trend early before a rejection occurs. For
quality control laboratories using a laboratory information management system
(LIMS), routine performance of test result-alert limit comparisons can be automated.
Where such a system is not available, manually recorded test results
could be transferred to a stand-alone computer for trend analysis. An x¯ plot
depicting the process in relation to the alert and specification limits should be
considered for monitoring trends.
USING VALIDATION EXPERIENCE TO SET PRODUCT ALERT LIMITS
Experience gained during validation can be used to fine-tune the process for
greater reliability. Several examples of changes being recommended based on
study findings may be found in the section of this chapter devoted to evaluation
of process data. Another application of the information gathered during validation
is in setting alert limits to be incorporated into the mechanism for product
release. The alert limits would be the control limits (UCL and LCL) calculated
as part of the review process for each analytical test; they could be made part
of the written specifications for product release.
The recommendation to use control limits calculated as part of validation
as alert limits is based on the expectation that test results from future production
should normally fall within these limits. Indeed, this is the essence of retrospective
validation. Furthermore, for a stable, centered process the control limits
would fall within the release specification for the test. Exceeding an alert limit
therefore would not necessarily delay product release but could precipitate an
investigation into the cause.
Requiring quality control to use validation experience to release product
achieves two objectives: it monitors conclusions reached during validation for
ongoing reliability and identifies a trend early before a rejection occurs. For
quality control laboratories using a laboratory information management system
(LIMS), routine performance of test result-alert limit comparisons can be automated.
Where such a system is not available, manually recorded test results
could be transferred to a stand-alone computer for trend analysis. An x¯ plot
depicting the process in relation to the alert and specification limits should be
considered for monitoring trends.
greater reliability. Several examples of changes being recommended based on
study findings may be found in the section of this chapter devoted to evaluation
of process data. Another application of the information gathered during validation
is in setting alert limits to be incorporated into the mechanism for product
release. The alert limits would be the control limits (UCL and LCL) calculated
as part of the review process for each analytical test; they could be made part
of the written specifications for product release.
The recommendation to use control limits calculated as part of validation
as alert limits is based on the expectation that test results from future production
should normally fall within these limits. Indeed, this is the essence of retrospective
validation. Furthermore, for a stable, centered process the control limits
would fall within the release specification for the test. Exceeding an alert limit
therefore would not necessarily delay product release but could precipitate an
investigation into the cause.
Requiring quality control to use validation experience to release product
achieves two objectives: it monitors conclusions reached during validation for
ongoing reliability and identifies a trend early before a rejection occurs. For
quality control laboratories using a laboratory information management system
(LIMS), routine performance of test result-alert limit comparisons can be automated.
Where such a system is not available, manually recorded test results
could be transferred to a stand-alone computer for trend analysis. An x¯ plot
depicting the process in relation to the alert and specification limits should be
considered for monitoring trends.
USING VALIDATION EXPERIENCE TO SET PRODUCT ALERT LIMITS
Experience gained during validation can be used to fine-tune the process for
greater reliability. Several examples of changes being recommended based on
study findings may be found in the section of this chapter devoted to evaluation
of process data. Another application of the information gathered during validation
is in setting alert limits to be incorporated into the mechanism for product
release. The alert limits would be the control limits (UCL and LCL) calculated
as part of the review process for each analytical test; they could be made part
of the written specifications for product release.
The recommendation to use control limits calculated as part of validation
as alert limits is based on the expectation that test results from future production
should normally fall within these limits. Indeed, this is the essence of retrospective
validation. Furthermore, for a stable, centered process the control limits
would fall within the release specification for the test. Exceeding an alert limit
therefore would not necessarily delay product release but could precipitate an
investigation into the cause.
Requiring quality control to use validation experience to release product
achieves two objectives: it monitors conclusions reached during validation for
ongoing reliability and identifies a trend early before a rejection occurs. For
quality control laboratories using a laboratory information management system
(LIMS), routine performance of test result-alert limit comparisons can be automated.
Where such a system is not available, manually recorded test results
could be transferred to a stand-alone computer for trend analysis. An x¯ plot
depicting the process in relation to the alert and specification limits should be
considered for monitoring trends.
greater reliability. Several examples of changes being recommended based on
study findings may be found in the section of this chapter devoted to evaluation
of process data. Another application of the information gathered during validation
is in setting alert limits to be incorporated into the mechanism for product
release. The alert limits would be the control limits (UCL and LCL) calculated
as part of the review process for each analytical test; they could be made part
of the written specifications for product release.
The recommendation to use control limits calculated as part of validation
as alert limits is based on the expectation that test results from future production
should normally fall within these limits. Indeed, this is the essence of retrospective
validation. Furthermore, for a stable, centered process the control limits
would fall within the release specification for the test. Exceeding an alert limit
therefore would not necessarily delay product release but could precipitate an
investigation into the cause.
Requiring quality control to use validation experience to release product
achieves two objectives: it monitors conclusions reached during validation for
ongoing reliability and identifies a trend early before a rejection occurs. For
quality control laboratories using a laboratory information management system
(LIMS), routine performance of test result-alert limit comparisons can be automated.
Where such a system is not available, manually recorded test results
could be transferred to a stand-alone computer for trend analysis. An x¯ plot
depicting the process in relation to the alert and specification limits should be
considered for monitoring trends.
Softgels (Soft Gelatin Capsules; Drug C)
This dosage form consists of a solution of active ingredient encased within a
spherical, plasticized gelatin shell. Unlike hard gelatin capsules, for which several
discrete operations are required to produce the final product, the softgel is
formed, filled, and hermetically sealed in one continuous operation [16]. Molten
gelatin mass is formed into two sheets or ribbons, each of which passes over a
die of the desired size and shape. At the point at which the two rotating dies
meet, the hemispheres are sealed and simultaneously filled with the solution of
active ingredient. Next the capsules are cleaned by immersion in an organic
solvent, dried, and inspected. (See Fig. 9.)
According to the process instructions, the active ingredient powder is dissolved
in vegetable oil with the aid of a solubilizer. Blend time is stated as 25
to 30 min. This is an elapsed time. Because a range of time is permitted, this
step is one for which historical data will be sought (Table 5). The bulk solution
is assayed to confirm that the prescribed weight of drug C was charged and
dissolution is complete before capsule filling may proceed. Concentration of the
active ingredient should vary very little from one batch to another with such a
straightforward process. We will want to confirm that this is the case. The purity
of each active ingredient raw material receipt is also of interest for reasons
previously stated.
The instructions for gelatin mass preparation direct that gelatin powder be
blended with water, a plasticizer, and colorant until a uniform consistency is
achieved, then heated until molten. The recommended blend time is 20 min at
a temperature of 60°C ± 5°. The temperature of the molten gelatin just prior to
formation into a ribbon is critical; too high a temperature causes the gelatin to
deteriorate, and a low temperature affects flow rate. Both conditions are to be
avoided for their deleterious effect on capsule formation. For these reasons,gelatin mass temperature is listed in Table 5. Blend time is of interest, too, as a
measure of process and raw material performance.
An important specification for gelatin is bloom strength, a quality of the
raw material that determines whether or not a capsule can be formed and sealed.
As with active ingredient purity, we will want to know this value for each lot
of gelatin used in the validation study.
The rationale of their selection is as follows: die rotation speed controls dwell time. If there is insufficient contact
time, the capsule halves will not properly seal. Subpotent softgels may result
from loss of liquid fill through a poorly developed seam. Gelatin ribbon thickness
determines capsule wall and seam thickness. Insufficient thickness will
contribute to poorly formed capsules and leakers. An overly thick ribbon results
in shell sealing problems. Ribbon condition is influenced by the temperature of
the gelatin mass, as previously noted. Relative humidity in the encapsulation
room is important to efficient drying. Minimally, we will want to know the
room condition during the time in which the 20 batches in this study were manufactured.
It would be best to examine environmental conditions over a longer
time period, say 1 year, to capture seasonal trends should they exist.
The batch record instructs the encapsulation machine operator to measure
and record seam and wall thickness every 45 min. Softgel weight is also checked
periodically by this operator. This information could be useful in demonstrating
process control but to a large extent seam and wall thickness are controlled by
manufacturing conditions for which historical data are already being sought. For
this reason, the results of these in-process monitors need not be pursued initially.
Consistent with the approach taken for other dosage forms previously discussed,
finished softgel weight data can be obtained from quality control reports when
dissolution and assay results are collected.
spherical, plasticized gelatin shell. Unlike hard gelatin capsules, for which several
discrete operations are required to produce the final product, the softgel is
formed, filled, and hermetically sealed in one continuous operation [16]. Molten
gelatin mass is formed into two sheets or ribbons, each of which passes over a
die of the desired size and shape. At the point at which the two rotating dies
meet, the hemispheres are sealed and simultaneously filled with the solution of
active ingredient. Next the capsules are cleaned by immersion in an organic
solvent, dried, and inspected. (See Fig. 9.)
According to the process instructions, the active ingredient powder is dissolved
in vegetable oil with the aid of a solubilizer. Blend time is stated as 25
to 30 min. This is an elapsed time. Because a range of time is permitted, this
step is one for which historical data will be sought (Table 5). The bulk solution
is assayed to confirm that the prescribed weight of drug C was charged and
dissolution is complete before capsule filling may proceed. Concentration of the
active ingredient should vary very little from one batch to another with such a
straightforward process. We will want to confirm that this is the case. The purity
of each active ingredient raw material receipt is also of interest for reasons
previously stated.
The instructions for gelatin mass preparation direct that gelatin powder be
blended with water, a plasticizer, and colorant until a uniform consistency is
achieved, then heated until molten. The recommended blend time is 20 min at
a temperature of 60°C ± 5°. The temperature of the molten gelatin just prior to
formation into a ribbon is critical; too high a temperature causes the gelatin to
deteriorate, and a low temperature affects flow rate. Both conditions are to be
avoided for their deleterious effect on capsule formation. For these reasons,gelatin mass temperature is listed in Table 5. Blend time is of interest, too, as a
measure of process and raw material performance.
An important specification for gelatin is bloom strength, a quality of the
raw material that determines whether or not a capsule can be formed and sealed.
As with active ingredient purity, we will want to know this value for each lot
of gelatin used in the validation study.
The rationale of their selection is as follows: die rotation speed controls dwell time. If there is insufficient contact
time, the capsule halves will not properly seal. Subpotent softgels may result
from loss of liquid fill through a poorly developed seam. Gelatin ribbon thickness
determines capsule wall and seam thickness. Insufficient thickness will
contribute to poorly formed capsules and leakers. An overly thick ribbon results
in shell sealing problems. Ribbon condition is influenced by the temperature of
the gelatin mass, as previously noted. Relative humidity in the encapsulation
room is important to efficient drying. Minimally, we will want to know the
room condition during the time in which the 20 batches in this study were manufactured.
It would be best to examine environmental conditions over a longer
time period, say 1 year, to capture seasonal trends should they exist.
The batch record instructs the encapsulation machine operator to measure
and record seam and wall thickness every 45 min. Softgel weight is also checked
periodically by this operator. This information could be useful in demonstrating
process control but to a large extent seam and wall thickness are controlled by
manufacturing conditions for which historical data are already being sought. For
this reason, the results of these in-process monitors need not be pursued initially.
Consistent with the approach taken for other dosage forms previously discussed,
finished softgel weight data can be obtained from quality control reports when
dissolution and assay results are collected.
Coated Tablet (Drug B)
Let’s now turn our attention to a different dosage form, applying some of the
strategies developed during the examination of drug A. Again we want to identify
the process steps that are responsible for distributing the active ingredient
as well as the tests that measure the effectiveness of those actions. Drug B is a
sugar-coated tablet prepared in the traditional manner; that is, layers are slowly
built up around a core by applying a coat of shellac and then subcoating, gross-
Copyright © 2003 Marcel Dekker, Inc.
ing, and smoothing coats until specifications are met at each stage. In the case
of drug B, the core contains two active ingredients. The coating, on the other
hand, has no medicinal value and is intended solely to enhance the aesthetic
appearance of the product. The manufacturing process is shown in Figure 6.
Table 3 summarizes the selected critical steps for the manufacture of the
core tablet of drug B. The core is prepared by dry-blending the first active
ingredient (i.e., B1) with several excipients. Blend time is of interest for its
impact on the distribution of the therapeutic agent. The premix just prepared is
granulated using an alcohol-binder solution. The process directions allow the
operator some latitude in using additional alcohol to ensure that the batch is
uniformly wet. It will be necessary to know whether or not additional alcohol
is routinely required, and if so, how much is used. Besides measuring operator
technique, the wetting step affects particle size distribution. The oven tray dryer
is identified for drying the wet mix. Granulation drying time is of interest, because
loss on drying is not measured. Once dry, the granulation is milled using
a specified screen size and machine setting. Alternate equipment is not provided
for in the aforementioned steps.
The powder produced in the prior operation is combined with the second
active ingredient (B2), as well as several other excipients in a twin-shell blender
and mixed for several min. For reasons previously discussed, mix time is of
interest, and thus it is listed as a critical process step.
The blend of the two active ingredients (B1 and B2) is slugged and then
the slugs are oscillated. Slugger model and tooling are listed in the batch instructions.
The thickness of the slug is specified, but no information is recorded on
the slugging operation, as control of this procedure is left to the experience of
the press operator. The batch record permits the use of only one screen size.
Since all of the batches have been made in the same manner, this important
process step will not be included as one to be studied.
Next, lubricant and oscillated granulation are blended for several min. The
elapsed mixing time is of interest because of its impact on drug distribution and
the effect of the lubricant on dissolution. During compression, 1000 randomly
selected cores are accumulated for use by quality control.
The ATW, hardness, and disintegration time are determined by the press
operator during compression. As in the case of drug A, we will not rely on these
results for our study, but rather on the test data from quality control.
Following approval of the bulk cores by quality control, they are shellaccoated.
According to the manufacturing directions, one or two coats may be
applied based on the process operator’s judgment. A third coat is permissible
but only in response to directions from the supervisor. In any event, the actual
number of coats applied is recorded in the batch record. Because of its potential
impact on drug availability,Once the shellacking stage has been completed, the cores are built up
through a series of coating operations. The number of applications of coating
solution, the volume of coating solution applied, and the coating environment
can influence product performance and therefore need to be studied.
The quality control tests selected after review of in-process and finishedproduct
specifications are listed in Table 3. The rationale for selection has been
addressed in general terms during the review for drug A. These quality control
tests, while informative, provide no insight into how the shellac coating will
behave a number of years from now. For some perspective, we can examine the
stability profile of commercial batches placed into the stability program. Of
course, the batches considered would have been made by the same process as
the one being validated. Particular attention should be paid to disintegration and
dissolution results.
strategies developed during the examination of drug A. Again we want to identify
the process steps that are responsible for distributing the active ingredient
as well as the tests that measure the effectiveness of those actions. Drug B is a
sugar-coated tablet prepared in the traditional manner; that is, layers are slowly
built up around a core by applying a coat of shellac and then subcoating, gross-
Copyright © 2003 Marcel Dekker, Inc.
ing, and smoothing coats until specifications are met at each stage. In the case
of drug B, the core contains two active ingredients. The coating, on the other
hand, has no medicinal value and is intended solely to enhance the aesthetic
appearance of the product. The manufacturing process is shown in Figure 6.
Table 3 summarizes the selected critical steps for the manufacture of the
core tablet of drug B. The core is prepared by dry-blending the first active
ingredient (i.e., B1) with several excipients. Blend time is of interest for its
impact on the distribution of the therapeutic agent. The premix just prepared is
granulated using an alcohol-binder solution. The process directions allow the
operator some latitude in using additional alcohol to ensure that the batch is
uniformly wet. It will be necessary to know whether or not additional alcohol
is routinely required, and if so, how much is used. Besides measuring operator
technique, the wetting step affects particle size distribution. The oven tray dryer
is identified for drying the wet mix. Granulation drying time is of interest, because
loss on drying is not measured. Once dry, the granulation is milled using
a specified screen size and machine setting. Alternate equipment is not provided
for in the aforementioned steps.
The powder produced in the prior operation is combined with the second
active ingredient (B2), as well as several other excipients in a twin-shell blender
and mixed for several min. For reasons previously discussed, mix time is of
interest, and thus it is listed as a critical process step.
The blend of the two active ingredients (B1 and B2) is slugged and then
the slugs are oscillated. Slugger model and tooling are listed in the batch instructions.
The thickness of the slug is specified, but no information is recorded on
the slugging operation, as control of this procedure is left to the experience of
the press operator. The batch record permits the use of only one screen size.
Since all of the batches have been made in the same manner, this important
process step will not be included as one to be studied.
Next, lubricant and oscillated granulation are blended for several min. The
elapsed mixing time is of interest because of its impact on drug distribution and
the effect of the lubricant on dissolution. During compression, 1000 randomly
selected cores are accumulated for use by quality control.
The ATW, hardness, and disintegration time are determined by the press
operator during compression. As in the case of drug A, we will not rely on these
results for our study, but rather on the test data from quality control.
Following approval of the bulk cores by quality control, they are shellaccoated.
According to the manufacturing directions, one or two coats may be
applied based on the process operator’s judgment. A third coat is permissible
but only in response to directions from the supervisor. In any event, the actual
number of coats applied is recorded in the batch record. Because of its potential
impact on drug availability,Once the shellacking stage has been completed, the cores are built up
through a series of coating operations. The number of applications of coating
solution, the volume of coating solution applied, and the coating environment
can influence product performance and therefore need to be studied.
The quality control tests selected after review of in-process and finishedproduct
specifications are listed in Table 3. The rationale for selection has been
addressed in general terms during the review for drug A. These quality control
tests, while informative, provide no insight into how the shellac coating will
behave a number of years from now. For some perspective, we can examine the
stability profile of commercial batches placed into the stability program. Of
course, the batches considered would have been made by the same process as
the one being validated. Particular attention should be paid to disintegration and
dissolution results.
Evaluation of Historical Data
Earlier in the discussion of process validation strategies, 20 production batches
were suggested as a minimum number upon which to draw conclusions about
the validity of the process. In this particular example, however, two distinct
methods of drying are provided. In order to have sufficient history on each
operation, the number of batches examined was increased to 30.
The batches were selected so that the same number was dried by each
process. For the other critical manufacturing steps and release tests listed in
Table 1, data were collected for all 30 batches.
The first manufacturing step, premix blending time, was consistently reported
as 10 min, but with one exception. In this instance, the powders were
tumbled for 20 min, which is still within the limits (10 to 20 min) prescribed
by the batch record. It would be interesting to know if this source of variability can materially affect attributes of the final product. Unfortunately, having only
one batch produced by the 20-min process does not permit statistically valid
comparisons. At best, test results for the single 20-min batch can be screened
using summary data from the remainder of the study. Under different circumstances,
batches would have been grouped by mixing time and compared by
dosage form attributes. More than likely, subsequent manipulation of the blend
would have negated any contribution, allowing us to conclude that a mixing
time of 10 to 20 min is not unreasonable.
At the wet milling step we encounter a situation similar to preblending;
that is, only two of the 30 study batches are prepared using the no. 5 drilled
screen. The no. 7 is obviously the screen of choice. The purpose of this step is
to produce particles of reasonably uniform size, which in turn will improve
drying. From the records, we also know that the no. 5 screen was used
only with batches that were tray dried. Elapsed drying time and residual
moisture were compared for the two batches from the no. 5 screen process
and the other 13 batches that were tray dried. No important differences were
detected. Still, in light of the limited use of the no. 5 screen, it would not
be inappropriate to recommend this option be eliminated from the processing
instructions.
Mean drying time for the oven tray process is 19.2 hr. All 15 batches
were dried within the specified time of 16 to 20 hr. No seasonal influence was
apparent. The average moisture content of these batches is 1.2%; the standard
deviation is 0.3%. The 15 batches dried using the fluid bed dryer had a residual
moisture of 0.8% (SD = 0.1%). Drying time is mechanically controlled and not
recorded. The statistics favor the fluid bed process; it is more efficient and
uniform. There is nothing in these data to disqualify the oven tray dryer from
further use, however.
Oscillation of the dried granulation and lubricant was accomplished in
every instance using a no. 10 wire screen. Reference to the no. 12 screen, the
alternative method for pulverizing the batch, must be deleted from the manufacturing
instructions for the process to be validated retrospectively.
The final mix blending time was reported as either 10 or 15 min. Twentyone
of the 30 batches were tumbled for 10 min and the remainder were mixed
for 15 min. The mixing time is not mechanically controlled or automatically
recorded; it is left to the operator to interpret elapsed time. Because of the
importance of the step to distribution of the therapeutic agent, a comparison was
made between the distribution of the percentage of relative tablet potency [(tablet
assay/tablet weight) × 100] for the two mixing times. The frequency distributions
of the two populations are shown in Figure 3.
The two histograms are visually different, with the 15-min process exhibiting
more dispersion. Despite this difference both populations are tightly grouped,
which is a reflection of the uniformity of the blend.The processes may be studied quantitatively by comparing the means and
standard deviations of the two populations. The effect of final blend time on
lubricant distribution was examined by comparing disintegration time statistics
for the grouped data. None was noted.
The moisture content of the 15 tray-dried batches following final mix
remained essentially unchanged from the drying step. The batches from the fluid
bed process gained moisture. This is probably attributable to handling very dry
material in a relatively humid environment. Both groups are still below the
target for this step of 1.5 %, however.
Table 2 gives a comparison of the moisture contents following the drying
and tumbling steps. The sizable increase in mean moisture content of the fluid
bed-dried batches deserves further study. To determine whether or not all
batches were uniformly affected, the mean moisture content was plotted in the
order in which the batches were produced. Whereas the plot for the tray-dried
batches is unremarkable, the fluid bed process chart (Fig. 4) depicts an unnatural
pattern. Further investigation discloses that heating, ventilation, and air condition
(HVAC) problems were experienced by the area in which a number of
these batches were blended.
During compression, 1000 tablets were randomly selected for use by quality
control. Inspection of the batch records revealed that all 30 batches were
compressed on the same model press operating at approximately the same speed.
All presses were fed by overhead delivery systems of the same design, thus
tableting equipment will not be a source of variability from batch to batch.
The test for disintegration is performed as described in the USP, and the
results are rounded to the nearest half-min. Disintegration time varied over a
narrow range for all batches studied. The 15-batch average for the tray dryer
process (2.7 min) is well below the specification (10 min) for this test. Hardness
of tablets from the tray dryer process averaged 15 Strong–Cobb units (SCU).
All batches exceeded the minimum specification (9 SCU); there is no upper limit. Hardness and disintegration time are not well correlated, probably due to
rounding of test results and the need to compare averages.
On average, tablets from the fluid bed process were slightly harder. Also,
the individual batches had a greater range of hardness than batches from the
alternative drying process. Disintegration time for the fluid bed process averaged
3.0 min. Individual batches ranged from2.0 to 4.5 min. As with the tray process,
no correlation was found between hardness and disintegration time. In summary,
tablets from the fluid bed dryer process were somewhat harder and took slightly
longer to disintegrate. (See Table 2.) These differences are considered insignificant,
however. If any recommendations were made, it would be to lower the
disintegration time specification or establish an internal action limit closer to
the historical upper range of the process.
Control charts were plotted for hardness and average tablet weight (ATW)
to evaluate process performance over time. Separate charts were prepared for
the tray dryer and fluid bed processes. Hardness values are an average of 10
individual measurements. The ATW subgroups are the result of weighing 20
tablets individually. The control charts were inspected for trends and evidence
of instability using well-established methods [9]. Only the control chart for hardness
of tablets from the fluid bed process responded to one of the tests for
pattern instability (Fig. 5); that is, two of three consecutive points exceeded the
2-sigma limit. From the chart it is obvious the general trend toward greater
tablet hardness (from 11 to 25 SCU) is the underlying cause of the instability.
The trend to greater hardness was subsequently arrested and may have to do with attempts to regulate another tablet variable—thickness, for example—
although the records are vague in this regard.
Water content of the bulk tablets irrespective of the drying process was
higher than at the final mix stage (Table 2). This is probably due to the compression
room environment and the low initial moisture of the powder. Still, the
specification limit of 2% is easily met.
The FDA has recently issued draft guidelines that recommend blend uniformity
analysis for all products for which USP requires content uniformity
analysis [10]. The USP requires this test when the product contains less than 50
mg of the active ingredient per dosage form or when the active ingredient is
less than 50% of the dosage form by weight. The concern FDA has is that if
blend uniformity is not achieved with mixing of the final granulation, then some
dosage units are likely not to be uniform [11]. Blend uniformity is not routinely
determined for drug A, nor is there a requirement because the dosage form is
over 50% active ingredient. In the absence of historical information about uniformity
of the blend, the relationship between tablet weight and potency should
be carefully examined.
Tablet weight should bear a direct relationship to milligrams of active
ingredient available where the final blend is homogeneous. This conclusion assumes
that demixing does not occur as the compound is transferred to intermediate
storage containers or to a tablet press hopper [12]. To measure the likelihood
that controlling tablet weight assures dosage uniformity, 50 tablet assays selected
at random (from 300 tablet assays) were compared to tablet weight using
regression analysis. Because the same model tablet press and blender were employed
for every batch, assay results from all 30 batches were pooled. The mean
purity of the 25 receipts of active ingredients used to manufacture the 30 batches
in the validation study was 99.7%, or 0.3% below target. Individual lots ranged from 98.8–102%. Because of these lot-to-lot differences, active ingredient raw
material potency was also included in the regression analysis.
The general model from the regression analysis is [13]
y = bo + b1X1 + b2Y2
where
y = tablet potency
bo = constant
X1 = raw material purity
X2 = tablet weight
Tablet potency was found to be related to raw material purity and tablet
weight as follows:
y = −414.6 + 6.605OX1 + 0.4303X2
We would expect the regression plane to have a significant positive slope;
that is, as purity of the active ingredient and tablet weight increase, so will
tablet potency, and this was found to be the case. Both slopes are statistically
significantly different from 0 at α = 0.025. When the above equation is used to
predict tablet potency given the ideal tablet weight (600 mg) for the product
and mean raw material purity of 99.7%, the resulting value is only 2.1 mg
different from the theoretical value of 500 mg.
In conclusion, drug A production was shown to be within established
specifications, and there is no reason to believe this will not be the case for
future production as long as all practices are continued in their present form.
Furthermore, there is no significant difference between batches produced by the
tray dryer process and the fluid bed process. A validation report should memorialize
these findings. The report should also recommend eliminating the option
to use a no. 5 screen for the wet milling step and a no. 12 screen to pulverize
the dried granulation. There is no experience or only limited experience with
this equipment that supports its continued availability. In the same vein, the
final blend time should be standardized at 10 min and automatically controlled
by means of a timer.
were suggested as a minimum number upon which to draw conclusions about
the validity of the process. In this particular example, however, two distinct
methods of drying are provided. In order to have sufficient history on each
operation, the number of batches examined was increased to 30.
The batches were selected so that the same number was dried by each
process. For the other critical manufacturing steps and release tests listed in
Table 1, data were collected for all 30 batches.
The first manufacturing step, premix blending time, was consistently reported
as 10 min, but with one exception. In this instance, the powders were
tumbled for 20 min, which is still within the limits (10 to 20 min) prescribed
by the batch record. It would be interesting to know if this source of variability can materially affect attributes of the final product. Unfortunately, having only
one batch produced by the 20-min process does not permit statistically valid
comparisons. At best, test results for the single 20-min batch can be screened
using summary data from the remainder of the study. Under different circumstances,
batches would have been grouped by mixing time and compared by
dosage form attributes. More than likely, subsequent manipulation of the blend
would have negated any contribution, allowing us to conclude that a mixing
time of 10 to 20 min is not unreasonable.
At the wet milling step we encounter a situation similar to preblending;
that is, only two of the 30 study batches are prepared using the no. 5 drilled
screen. The no. 7 is obviously the screen of choice. The purpose of this step is
to produce particles of reasonably uniform size, which in turn will improve
drying. From the records, we also know that the no. 5 screen was used
only with batches that were tray dried. Elapsed drying time and residual
moisture were compared for the two batches from the no. 5 screen process
and the other 13 batches that were tray dried. No important differences were
detected. Still, in light of the limited use of the no. 5 screen, it would not
be inappropriate to recommend this option be eliminated from the processing
instructions.
Mean drying time for the oven tray process is 19.2 hr. All 15 batches
were dried within the specified time of 16 to 20 hr. No seasonal influence was
apparent. The average moisture content of these batches is 1.2%; the standard
deviation is 0.3%. The 15 batches dried using the fluid bed dryer had a residual
moisture of 0.8% (SD = 0.1%). Drying time is mechanically controlled and not
recorded. The statistics favor the fluid bed process; it is more efficient and
uniform. There is nothing in these data to disqualify the oven tray dryer from
further use, however.
Oscillation of the dried granulation and lubricant was accomplished in
every instance using a no. 10 wire screen. Reference to the no. 12 screen, the
alternative method for pulverizing the batch, must be deleted from the manufacturing
instructions for the process to be validated retrospectively.
The final mix blending time was reported as either 10 or 15 min. Twentyone
of the 30 batches were tumbled for 10 min and the remainder were mixed
for 15 min. The mixing time is not mechanically controlled or automatically
recorded; it is left to the operator to interpret elapsed time. Because of the
importance of the step to distribution of the therapeutic agent, a comparison was
made between the distribution of the percentage of relative tablet potency [(tablet
assay/tablet weight) × 100] for the two mixing times. The frequency distributions
of the two populations are shown in Figure 3.
The two histograms are visually different, with the 15-min process exhibiting
more dispersion. Despite this difference both populations are tightly grouped,
which is a reflection of the uniformity of the blend.The processes may be studied quantitatively by comparing the means and
standard deviations of the two populations. The effect of final blend time on
lubricant distribution was examined by comparing disintegration time statistics
for the grouped data. None was noted.
The moisture content of the 15 tray-dried batches following final mix
remained essentially unchanged from the drying step. The batches from the fluid
bed process gained moisture. This is probably attributable to handling very dry
material in a relatively humid environment. Both groups are still below the
target for this step of 1.5 %, however.
Table 2 gives a comparison of the moisture contents following the drying
and tumbling steps. The sizable increase in mean moisture content of the fluid
bed-dried batches deserves further study. To determine whether or not all
batches were uniformly affected, the mean moisture content was plotted in the
order in which the batches were produced. Whereas the plot for the tray-dried
batches is unremarkable, the fluid bed process chart (Fig. 4) depicts an unnatural
pattern. Further investigation discloses that heating, ventilation, and air condition
(HVAC) problems were experienced by the area in which a number of
these batches were blended.
During compression, 1000 tablets were randomly selected for use by quality
control. Inspection of the batch records revealed that all 30 batches were
compressed on the same model press operating at approximately the same speed.
All presses were fed by overhead delivery systems of the same design, thus
tableting equipment will not be a source of variability from batch to batch.
The test for disintegration is performed as described in the USP, and the
results are rounded to the nearest half-min. Disintegration time varied over a
narrow range for all batches studied. The 15-batch average for the tray dryer
process (2.7 min) is well below the specification (10 min) for this test. Hardness
of tablets from the tray dryer process averaged 15 Strong–Cobb units (SCU).
All batches exceeded the minimum specification (9 SCU); there is no upper limit. Hardness and disintegration time are not well correlated, probably due to
rounding of test results and the need to compare averages.
On average, tablets from the fluid bed process were slightly harder. Also,
the individual batches had a greater range of hardness than batches from the
alternative drying process. Disintegration time for the fluid bed process averaged
3.0 min. Individual batches ranged from2.0 to 4.5 min. As with the tray process,
no correlation was found between hardness and disintegration time. In summary,
tablets from the fluid bed dryer process were somewhat harder and took slightly
longer to disintegrate. (See Table 2.) These differences are considered insignificant,
however. If any recommendations were made, it would be to lower the
disintegration time specification or establish an internal action limit closer to
the historical upper range of the process.
Control charts were plotted for hardness and average tablet weight (ATW)
to evaluate process performance over time. Separate charts were prepared for
the tray dryer and fluid bed processes. Hardness values are an average of 10
individual measurements. The ATW subgroups are the result of weighing 20
tablets individually. The control charts were inspected for trends and evidence
of instability using well-established methods [9]. Only the control chart for hardness
of tablets from the fluid bed process responded to one of the tests for
pattern instability (Fig. 5); that is, two of three consecutive points exceeded the
2-sigma limit. From the chart it is obvious the general trend toward greater
tablet hardness (from 11 to 25 SCU) is the underlying cause of the instability.
The trend to greater hardness was subsequently arrested and may have to do with attempts to regulate another tablet variable—thickness, for example—
although the records are vague in this regard.
Water content of the bulk tablets irrespective of the drying process was
higher than at the final mix stage (Table 2). This is probably due to the compression
room environment and the low initial moisture of the powder. Still, the
specification limit of 2% is easily met.
The FDA has recently issued draft guidelines that recommend blend uniformity
analysis for all products for which USP requires content uniformity
analysis [10]. The USP requires this test when the product contains less than 50
mg of the active ingredient per dosage form or when the active ingredient is
less than 50% of the dosage form by weight. The concern FDA has is that if
blend uniformity is not achieved with mixing of the final granulation, then some
dosage units are likely not to be uniform [11]. Blend uniformity is not routinely
determined for drug A, nor is there a requirement because the dosage form is
over 50% active ingredient. In the absence of historical information about uniformity
of the blend, the relationship between tablet weight and potency should
be carefully examined.
Tablet weight should bear a direct relationship to milligrams of active
ingredient available where the final blend is homogeneous. This conclusion assumes
that demixing does not occur as the compound is transferred to intermediate
storage containers or to a tablet press hopper [12]. To measure the likelihood
that controlling tablet weight assures dosage uniformity, 50 tablet assays selected
at random (from 300 tablet assays) were compared to tablet weight using
regression analysis. Because the same model tablet press and blender were employed
for every batch, assay results from all 30 batches were pooled. The mean
purity of the 25 receipts of active ingredients used to manufacture the 30 batches
in the validation study was 99.7%, or 0.3% below target. Individual lots ranged from 98.8–102%. Because of these lot-to-lot differences, active ingredient raw
material potency was also included in the regression analysis.
The general model from the regression analysis is [13]
y = bo + b1X1 + b2Y2
where
y = tablet potency
bo = constant
X1 = raw material purity
X2 = tablet weight
Tablet potency was found to be related to raw material purity and tablet
weight as follows:
y = −414.6 + 6.605OX1 + 0.4303X2
We would expect the regression plane to have a significant positive slope;
that is, as purity of the active ingredient and tablet weight increase, so will
tablet potency, and this was found to be the case. Both slopes are statistically
significantly different from 0 at α = 0.025. When the above equation is used to
predict tablet potency given the ideal tablet weight (600 mg) for the product
and mean raw material purity of 99.7%, the resulting value is only 2.1 mg
different from the theoretical value of 500 mg.
In conclusion, drug A production was shown to be within established
specifications, and there is no reason to believe this will not be the case for
future production as long as all practices are continued in their present form.
Furthermore, there is no significant difference between batches produced by the
tray dryer process and the fluid bed process. A validation report should memorialize
these findings. The report should also recommend eliminating the option
to use a no. 5 screen for the wet milling step and a no. 12 screen to pulverize
the dried granulation. There is no experience or only limited experience with
this equipment that supports its continued availability. In the same vein, the
final blend time should be standardized at 10 min and automatically controlled
by means of a timer.
SELECTION AND EVALUATION OF PROCESSING DATA
Drug A is a compressed tablet containing a single active ingredient. Inspection
of the batch record reveals that the following operations are involved in the
manufacture of the dosage unit. The active ingredient is combined with several
excipients in a twin-shell blender. The premix just prepared is granulated using
a purified water-binder solution. The resulting wet mix is milled using a specified
screen and machine setting, then dried using either an oven tray dryer or a
fluid bed dryer. When dry, the blend is oscillated, combined with previously
sized lubricant, and blended. The granulation is then compressed. See Figure 2
for a flow diagram of the manufacturing process.
At the premix blending step, the batch record provides two pieces of infor-mation: recommended blending time and blender load. The latter will be of little
interest, as only one size batch is produced for this product. Blender speed is
not specified in the batch record because it is fixed. Because mixing time has
been recognized as influencing blend uniformity, this operation will become the
first of the critical process steps for which we will want to collect historical
information [8].
The second major step is granulation. The process is controlled by the
operator, whose judgment is relied on for the appropriate end point. As no
information useful for process validation is available, we will move on to the
next step, comminution.
The batch record calls for passing the wet mix through a comminutor
using a no. 5 or 7 drilled stainless steel screen. Knife position and rotational
speed are two other factors that influence particle size; however, the step instruction
is quite specific about machine setup. Therefore, only screen size is a source
of variability for this step. We will want to know the frequency of use of each
screen.
Next, the granulation is dried to a target moisture of 1%. Either a tray or
fluid bed dryer may be used, at the discretion of area supervision. Regardless
of the method, drying time will be of interest. In addition, the final moisture
content should be ascertained for each batch. The dried granulation and lubricant
are then oscillated using a no. 10 or 12 wire screen. This is the last sizing
operation of the process; it will determine the particle size distribution of the
final blend. Knowing the history of use of each screen size is thus important.
The lubricant and granulation are blended for several minutes. The elapsed
mixing time is of interest because of its impact on drug distribution and the
generally deleterious effect of the lubricant on dissolution.
Because excess moisture is thought to have a negative effect on the dosage
form, loss on drying (LOD) is determined on the final blend.
Blending is followed by tableting. During compression, online measurements
such as tablet weight, hardness, and disintegration are made by the process
operator in order to ensure uniformity of the tablets. The weight of the
tablets is not measured individually; rather, the average weight of 10 tablets is
recorded. Although these data are good indicators of operation and machine
performance, we would prefer to have the more precise picture provided by
individual tablet weight.
Disintegration time and tablet hardness data could be collected from the
manufacturing batch records; however, for ease of administration these figures
will be obtained from the quality control test results, which also contain individual
tablet weighings.
Disintegration time was selected as a critical variable because for a drug
substance to be absorbed it must first disintegrate and then dissolve. The resistance
of a tablet to breakage, chipping, and so forth depends on its hardness.Disintegration, too, can be influenced by hardness of the tablet. For these reasons,
hardness testing results also will be examined.
Specifications used by quality control to release drug A are found in a
laboratory procedure. In addition to the previously discussed hardness and disintegration
time requirements, the procedure calls for determining the average
tablet weight by the United States Pharmacopeia (USP) procedure; that is, 20
individual tablets are weighed.
The control procedure also requires assay of individual tablets. Of all the
information available, these data will be the most useful in reaching an opinion
of the adequacy of the process to distribute the therapeutic agent uniformly.
In addition, the laboratory checks the moisture content of the bulk tablets.
It will be interesting to compare these results to the LOD of the final blend to
measure the contribution of material handling.
of the batch record reveals that the following operations are involved in the
manufacture of the dosage unit. The active ingredient is combined with several
excipients in a twin-shell blender. The premix just prepared is granulated using
a purified water-binder solution. The resulting wet mix is milled using a specified
screen and machine setting, then dried using either an oven tray dryer or a
fluid bed dryer. When dry, the blend is oscillated, combined with previously
sized lubricant, and blended. The granulation is then compressed. See Figure 2
for a flow diagram of the manufacturing process.
At the premix blending step, the batch record provides two pieces of infor-mation: recommended blending time and blender load. The latter will be of little
interest, as only one size batch is produced for this product. Blender speed is
not specified in the batch record because it is fixed. Because mixing time has
been recognized as influencing blend uniformity, this operation will become the
first of the critical process steps for which we will want to collect historical
information [8].
The second major step is granulation. The process is controlled by the
operator, whose judgment is relied on for the appropriate end point. As no
information useful for process validation is available, we will move on to the
next step, comminution.
The batch record calls for passing the wet mix through a comminutor
using a no. 5 or 7 drilled stainless steel screen. Knife position and rotational
speed are two other factors that influence particle size; however, the step instruction
is quite specific about machine setup. Therefore, only screen size is a source
of variability for this step. We will want to know the frequency of use of each
screen.
Next, the granulation is dried to a target moisture of 1%. Either a tray or
fluid bed dryer may be used, at the discretion of area supervision. Regardless
of the method, drying time will be of interest. In addition, the final moisture
content should be ascertained for each batch. The dried granulation and lubricant
are then oscillated using a no. 10 or 12 wire screen. This is the last sizing
operation of the process; it will determine the particle size distribution of the
final blend. Knowing the history of use of each screen size is thus important.
The lubricant and granulation are blended for several minutes. The elapsed
mixing time is of interest because of its impact on drug distribution and the
generally deleterious effect of the lubricant on dissolution.
Because excess moisture is thought to have a negative effect on the dosage
form, loss on drying (LOD) is determined on the final blend.
Blending is followed by tableting. During compression, online measurements
such as tablet weight, hardness, and disintegration are made by the process
operator in order to ensure uniformity of the tablets. The weight of the
tablets is not measured individually; rather, the average weight of 10 tablets is
recorded. Although these data are good indicators of operation and machine
performance, we would prefer to have the more precise picture provided by
individual tablet weight.
Disintegration time and tablet hardness data could be collected from the
manufacturing batch records; however, for ease of administration these figures
will be obtained from the quality control test results, which also contain individual
tablet weighings.
Disintegration time was selected as a critical variable because for a drug
substance to be absorbed it must first disintegrate and then dissolve. The resistance
of a tablet to breakage, chipping, and so forth depends on its hardness.Disintegration, too, can be influenced by hardness of the tablet. For these reasons,
hardness testing results also will be examined.
Specifications used by quality control to release drug A are found in a
laboratory procedure. In addition to the previously discussed hardness and disintegration
time requirements, the procedure calls for determining the average
tablet weight by the United States Pharmacopeia (USP) procedure; that is, 20
individual tablets are weighed.
The control procedure also requires assay of individual tablets. Of all the
information available, these data will be the most useful in reaching an opinion
of the adequacy of the process to distribute the therapeutic agent uniformly.
In addition, the laboratory checks the moisture content of the bulk tablets.
It will be interesting to compare these results to the LOD of the final blend to
measure the contribution of material handling.
Other Considerations
Comprehensive records of complaints received either directly from the customer
or through a drug problem reporting program should be reviewed. Furthermore,
a record of any follow-up investigation of such complaints is mandatory [6] and
should be part of this file. Review of customer complaint records can furnish a
useful overview of process performance and possibly hint at product problems.
Complaint analysis should therefore be viewed as a meaningful adjunct to the
critical process step and control test selection process.
Batch yield reflects efficiency of the operation. Because yield figures are
the sum of numerous interactions, they fail in most cases to provide specific
information about process performance and therefore must be used with caution
in retrospective validation. In any event, this information should be collected,
as it can contribute to further refinement of the yield limits that appear in the
batch record.
Lot-to-lot differences in the purity of the therapeutic agent must be considered
when evaluating in-process and finished-product test results. In addition to
potency such qualities as particle size distribution, bulk density, and source of
the material will be of interest. Such information should be available from the
raw material test reports prepared by the quality control laboratory for each lot
of material received. The physical characteristics of the excipients should not
be overlooked, especially for those materials with inherent variability. Metallic
stearates is a classic example. In such instances, the source of supply is desirable
information to have available.
There is value in examining logs of equipment and physical plant maintenance.
These documents can provide a chronological profile of the operating
environment and reveal recent alterations to the process equipment that may
have enough impact to disqualify the product from retrospective validation consideration.
For this reason, it is always prudent to contemplate equipment status
early in the information-gathering stage. The availability of such information
should be ascertained for yet another reason: rarely is equipment dedicated to
Copyright © 2003 Marcel Dekker, Inc.
one product. More often than not, each blender, comminutor, tablet press, and
so forth is used for several operations. Information gathered initially can therefore
be incorporated into subsequent studies.
Retrospective validation is directed primarily toward examining the records
of past performance, but what if one of these documents is not a true
reflection of the operation performed? Suppose that changes have crept into the
processing operation over time and have gone unreported. This condition would
result in the validation of a process that in reality does not exist. It is therefore
essential to audit the existing operation against the written instructions. There is
obvious advantage to undertaking this audit before commencing data acquisition.
Ideally, the manufacture of more than one batch should be witnessed, especially
where multiple-shift operations are involved. The same logic would apply
to the testing performed in process and at the finished stage. If any deviation
from the written directions is noted, an effort must be made to measure its
impact. In this regard, the previously described validation organization is a logical
forum for discussion and evaluation.
As a rule, batches that are rejected or reworked are not suitable for inclusion
in a retrospective validation study [7]. Indeed, a processing failure that is
not fully explainable should be cause to rethink the application of retrospective
validation. Nonconformance to specification that is attributable to a unique
event–operator error, for example, may be justifiably disregarded. In such cases,
the batch is not considered when the historical data are assembled.
Raw materials, both actives and excipients, can be a source of product
variability. To limit this risk, there should be meaningful acceptance specifications
and periodic confirmation of test results reported on the supplier’s certificate
of analysis. Also, purchases must be limited to previously qualified suppliers.
A determination that such controls are in place should be part of any
retrospective validation effort.
or through a drug problem reporting program should be reviewed. Furthermore,
a record of any follow-up investigation of such complaints is mandatory [6] and
should be part of this file. Review of customer complaint records can furnish a
useful overview of process performance and possibly hint at product problems.
Complaint analysis should therefore be viewed as a meaningful adjunct to the
critical process step and control test selection process.
Batch yield reflects efficiency of the operation. Because yield figures are
the sum of numerous interactions, they fail in most cases to provide specific
information about process performance and therefore must be used with caution
in retrospective validation. In any event, this information should be collected,
as it can contribute to further refinement of the yield limits that appear in the
batch record.
Lot-to-lot differences in the purity of the therapeutic agent must be considered
when evaluating in-process and finished-product test results. In addition to
potency such qualities as particle size distribution, bulk density, and source of
the material will be of interest. Such information should be available from the
raw material test reports prepared by the quality control laboratory for each lot
of material received. The physical characteristics of the excipients should not
be overlooked, especially for those materials with inherent variability. Metallic
stearates is a classic example. In such instances, the source of supply is desirable
information to have available.
There is value in examining logs of equipment and physical plant maintenance.
These documents can provide a chronological profile of the operating
environment and reveal recent alterations to the process equipment that may
have enough impact to disqualify the product from retrospective validation consideration.
For this reason, it is always prudent to contemplate equipment status
early in the information-gathering stage. The availability of such information
should be ascertained for yet another reason: rarely is equipment dedicated to
Copyright © 2003 Marcel Dekker, Inc.
one product. More often than not, each blender, comminutor, tablet press, and
so forth is used for several operations. Information gathered initially can therefore
be incorporated into subsequent studies.
Retrospective validation is directed primarily toward examining the records
of past performance, but what if one of these documents is not a true
reflection of the operation performed? Suppose that changes have crept into the
processing operation over time and have gone unreported. This condition would
result in the validation of a process that in reality does not exist. It is therefore
essential to audit the existing operation against the written instructions. There is
obvious advantage to undertaking this audit before commencing data acquisition.
Ideally, the manufacture of more than one batch should be witnessed, especially
where multiple-shift operations are involved. The same logic would apply
to the testing performed in process and at the finished stage. If any deviation
from the written directions is noted, an effort must be made to measure its
impact. In this regard, the previously described validation organization is a logical
forum for discussion and evaluation.
As a rule, batches that are rejected or reworked are not suitable for inclusion
in a retrospective validation study [7]. Indeed, a processing failure that is
not fully explainable should be cause to rethink the application of retrospective
validation. Nonconformance to specification that is attributable to a unique
event–operator error, for example, may be justifiably disregarded. In such cases,
the batch is not considered when the historical data are assembled.
Raw materials, both actives and excipients, can be a source of product
variability. To limit this risk, there should be meaningful acceptance specifications
and periodic confirmation of test results reported on the supplier’s certificate
of analysis. Also, purchases must be limited to previously qualified suppliers.
A determination that such controls are in place should be part of any
retrospective validation effort.
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K. Dashora, D. Singh, Swarnlata Saraf and S. Saraf *. Institute of Pharmacy, Pt.RavishankarShuklaUniversity, Raipur 492 010. *Author for ...
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