An Overview of Pharmaceutical Process Validation of Solid Dosage Form

An Overview of Pharmaceutical Process Validation of Solid Dosage Form.
*Umed A. Nikam, Abhijit V. Jadhav, V. R. Salunkhe, C. S. Magdum
Rajarambapu College of Pharmacy, Kasegaon Tal:-Walva, Dist:-Sangli, M.S. India


Abstract
The present article gives an introduction and general overview on process validation
of pharmaceutical manufacturing process especially tablet manufacturing process.
The principal objective of dosage form design is to achieve a predictable therapeutic
response to a drug included in a formulation which is capable of large scale
manufacture with reproducible product quality. Solid dosage forms include tablets
and capsules. Quality is always an imperative prerequisite when we consider any
product. Therefore, drugs must be manufactured to the highest quality levels.
Process Validation is one of the important steps in achieving and maintaining the
quality of final product. This article covers Introduction, type of validation
,Prospective validation Retrospective validation Concurrent validation Revalidation
,Elements of Process Validation, Product Lifecycle View ,Phases of Process
Validation , Rationale for selection of critical steps and parameters for process
validation, Documentation ,SOP, Validation Master Plan, Validation Protocol,
General notes process variations, critical factors and sample thief ,sampling plan and
acceptance criteria, the validation report, studies on the process validation by all
these parameter highlight the quality output of finished dosage form.
Key Words

Process validation, Quality management, manufacturing procedure, protocol.



Introduction
The concept of validation was first proposed by two Food and Dru Administration (FDA) officials, Ted  Byers and Bud Loftus, in the mid  1970 s in order to improve the  quality of pharmaceuticals Assurance of product quality is derived from careful attention to number of factors including selection of quality parts and materials, adequate product and process design, control of the process, and in process and end product testing1. Due to the complexity today s medical products, routine end product testing alone often is not sufficient to assure product quality for several reasons. Some end-products tests have limited sensitivity E.g.:- In some cases, where end product testing does not several all variations that may occur in the product, which may have an impact on safety and effectiveness, destructive testing is required to show that the manufacturing process is adequate.
Even the details of the equipments and their maintenance were also involved.
Validation Master Plan
An approved written plan of objectives and actions stating how and when a company will achieve
compliance with the GMP requirements regarding validation. VMP is a summary intention document stating the scope of the validation and outlining the methods to be used to establish the performance adequacy. The validation master plan should provide an overview of the entire validation
operation, its organizational structure,\ its content and planning. The main elements of its being the list/inventory of the items to, relevant to product and process controls within a firm should be included in the validation master plan. It even holds the calibration and qualification of equipments, summary and conditions of Validation Protocol.
Validation Protocol
A written plan of actions stating how process validation will be conducted, it will specify who will conduct the various tasks and define testing parameters, sampling plans, testing methods and specifications, will specify product characteristics, and equipment to be used. It must be specify the minimum number of batches to be used for validation studies, it must specify the acceptance
criteria and who will sign \ approve \ disapprove the conclusions derived from such a scientific study. The validation protocol should contain the following elements,
  • Short description of the process.
  • . Summary of critical processing steps to be investigated.
  • . In process, finished product specification for release.
  • . Sampling plans.
  • . Departmental responsibility.
  • . Proposed timetable.
  • . Approval of protocol.
Responsible authorities for validation8 ,10
The validation working party is convened to define, investigate, progress, collate, co-ordinate and
ultimately approve the entire effort, including all of the documentation generated. The working part would usually involve the following staff members
 Production manager,
Head of Quality Control (Manager),
Executive-QC, Head of Engineering
(Manager), Production executive,
Validation Executive, Validation
Manager, Head of Quality Assurance (Manager).

Selection of Critical Steps and Parameters for Process Validation

Granulation
It is the process of collecting particles by creating bonds between them. It is most critical step in tablet manufacturing as virtually all tablet characteristics like flow, weight variation, hardness, disintegration, and dissolution etc. depend on the granulation parameters. The granulation variables that need be controlled are;
  • . Mixing speed
  • . Granulation time
  • . Feed rate
  • . Amount of binder solution and its concentration
By controlling the above parameters, one can control the granule strength (fines) and density of granules, there by having a more smooth compression process. Another important aspects is
the granulator used, because high shear-granulators like RMG, Iodize
mixer produces denser granules compared to low shear granulators like FBG, their by questioning their suitability for fast-release preparation.
Drying
This step involves drying of wet mass. Moisture content in granules is an important factor, which has bearing on tablet characteristics. Hence to control moisture content, critical process variables like inlet temperature, drying time are to be monitored and controlled, if the moisture content is less (over dried granules). It produces fines upon milling, which in turn causes weight variation, capping and
chipping. Drying time needs to be controlled, because shorter drying period results in granules having
entrapped moisture, which during compression escapes from the granules having entrapped moisture,
which during compression escapes from the granules and causes the granules to stick to punches (case hardening) where as longer drying period produces friable granules.
Blending
It involves mixing of granules with other blending materials. The purpose of blending is to get uniform distribution of drug, appoint that becomes critical for low dose products like tablet and to impart good flow and anti adhesion property to the blend. Here the critical controlling variable is the mixing time, as under blending will result in segregation of blend and increase in disintegration
time due to coating of the granules with low melting lubricants like stearates. Hence content uniformity testing of drug is to be done at periodic intervals.
Compression
The major variables affecting the compression process are machine speed and compression force.
Variation in the machine speed leads to varied die fill volume hence varied tablet weight. Compression force needs to be controlled as it affects the tablet hardness, thickness, and
disintegration time and dissolution rate. Another controlling aspect is the machine vibration as excess vibration lead to segregation of blend in the hopper and altering the uniform distribution of the drug in the tablets.
Blister packing
This process involves packing in polyethylene lined aluminum foil and PVC blister pack. Temperature of rollers (sealing and forming) and speed of machine are critical
variables. Adequate forming roller temperature is essential to get proper blister formation. Adequate sealing roller temperature is essential to get proper sealing. Less temperature will leaf to leakage and higher temperature will result in burning or spoilage of aluminum foil and PVC. Leak test and
physical evaluation are carried out to establish the above variables during
blister packing operation.

In spite of the method we select for tableting we have some parameters which are to be considered during the process. These parameters were measured or estimated for process validation of the method. The parameters are: Process validation is generally done with three consecutive
batches. All the critical parameters were evaluated for fixing the optimum process parameters. Every processing step is validated for all the three batches and the results obtained must be present within the acceptance criteria, such that the product can be forwarded for the commercial production. All the problems that arise during validation are overcome and the product will be kept ready for the commercial batch production.
Sample Thief
A significant improvement in sampling can be achieved with the use of sample thief, sometimes
known as a grain thief of historical reasons. This device consists of 2 tubes one fitting tightly inside the other and with along holes cut through the tubes in corresponding positions. One end of the outer tube fitted to a point to facilitate is insertion in to a bulk powder the sampling procedure consists of rotating the inner tube to close the holes, inserting the device into the powder, rotating the inner tube
to open the holes, allowing the powder to enter the device, rotating the inner tube once more to close the wholes and finally removing the thief from the bulk powder wholes and finally removing the thief from the bulk powder The thief sampling is better method than merely scoping off it is still an inferior technique the top of a bulk powder Even through most thieves have relatively sharp ends; the very act of plunging the thief through the bulk powder must perturb the sample to some degree.
A compression force of the thief as propagates ahead it is pressed into the bulk thus potentially of the bulk changing the strata and alteringthe wall of powder at the outer walls of the thief. Furthermore, because large particles will flow more easily than will small particles, an opened thief is liable to be filled preferentially with the coarse fraction of the particle distribution
Working procedure by sample Thief
The sleeve rotates so that the interior compartment is isolated from the bulk powder, while in the
closed position, the thief is plunged into the central mass of the powder. Once the thief is at the desired position, the unit is rotated so that the interior compartment is now exposed to bulk powder. Powder flows into the thief compartment of its own accord. Once the interior compartment of the thief is filled, the sleeve of the thief is rotated so that the interior compartment is again isolated from the bulk powder. The thief is then withdrawn from the powder, and the sample is analyzed.
Sampling Plan and Acceptance Criteria
It is the responsibility of the manufacturer to ensure that the sampling plan and acceptance criteria
defined are adequate to ascertain that the manufacturing process is well- controlled and robust to produce drug product consistently meeting specifications. The following sampling plan and acceptance criteria provide a guide for the process validation of a typical solid oral dosage manufacturing process with medium risk indication. Other sampling plans may be acceptable if
they are statistically sound and justified. The extent of sampling, tests and acceptance must take into
consideration, the level of risk, e.g. the equipment type and capacity, to patient health of the drug product and should be considered on a case-by- case basis. The finished product specifications have to be adequately justified and the analytical methods have to be validated as per the
ASEAN Guidelines for Validation of Analytical Procedures.

The validation report
A written report should be available after completion of the validation. If found acceptable, it should be approved and authorized (signed and dated) the report should include at least the following,
1. Title and objective of study
2.Reference to protocol
3. Details of material
4. Equipment
5. Programs and cycles used 6.Details of procedures and test methods
6. Result (compared with acceptance criteria), and 8.Recommendations on the limit and criteria to be applied on future basis.
Conclusion
Process validation is an integral part of among all validation like equipment validation, cleaning
validation, vender validation etc. Validation is art step of assure to identity, strength, purity, safty, and
efficacy of pharmaceutical product. Applicable and critical parameter for validation process of solid dosage form must be consider to fulfills the requirement of quality assurance of final product.
References
1. Rockville M D. Guideline on General Principles of Process Validation. U.S. Food and Drug Administration., U.S. FDA: 2010.
2. Rockville M D. Guideline on General Principles of Process Validation. U.S. Food and Drug Administration., U.S. FDA: 1987.
3. www.processvalidation.com
4. Chaitanya Kumar G, Rout RP, Ram take S, Bhattachaiya S. Process Validation. The Indian pharmacist, 2005, 14-19.
5. Lambert J. Validation Guidelines for Pharmaceutical Dosage Forms. Health Canada/
Health Products and Food Branch Inspectorate, 2004, 7-15.
6. Satyabrata jena, Arjun G, Anil kumar ravipati N V, Satish kumar D,Vinod K R, David



Validation Deviations

Validation deviations are just a part of life when you are working through validation protocols and test scripts; it’s highly unlikely that you will ever complete a full validation project without raising the odd validation deviation here and there.

So what is a Deviation or Exception?

It’s quite simple it’s an error or a failure which occurs during Verification of Validation.
Types of Deviations

There are three main types of deviations that can occur during a validation project they are:

    Critical
    Non-critical
    Simple

Simple Deviations

Simple deviations are usually classified as documentation or protocol errors, these errors are usually found prior to execution or are “obvious” errors or typos. These deviations have no impact on the validation and offer to real risk to the validation process.

Examples of simple deviations include:

    Wrong test selected for product
    Incorrect specification for product
    Loss of power to the equipment being tested

Non Critical Deviations

Non-critical deviations are errors in the protocol or execution of the validation which have no impact on the validation, there errors are normally found during or after the execution. It is good practice to carry out an assessment to determine if the deviation has any impact. There is no real need to document the risk or lack thereof.

Examples of non-critical exceptions include:

    Operator not trained to perform the operation
    An interruption in the computer system or the equipment’s performance

Critical Deviations

Critical deviations are errors which have an impact on the validation, these errors are found during or after execution. It is good practice in this scenario to carry out an assessment to determine the impact if any.

Examples of critical exceptions include:

    Acceptance criterion failure
    An interruption in the computer system or the equipment’s performance

Deviation Process Flow

SME involvement throughout the deviation process is critical. You cannot document enough, even if all of it does not make it into the final event write up. A CAPA may not be needed for simple events, but consider a CAPA if there are many of them or the same ones repeatedly.
General Process Considerations

It is advisable to commence with the resolution process as soon as the event is observed. Involve the SME’s/QA throughout the process as appropriate and get agreement on next steps and/or results prior to execution, or after the completion. Immediately notify the relevant SME/QA if there is any potential Product/Material impact. Conduct a risk assessment to determine the impact and actions to be taken.
Types of Deviations

Typographical errors
These errors are found prior to execution or are “obvious” errors or typos.

External Issues
Failures caused by factors external to the process or system under test.

Execution Errors
Failures to follow instructions within the Test Document or referenced procedures.

Document Generation Errors
Incorrect detail in procedures, acceptance criteria or referenced documentation.

Acceptance Criteria Failures
Pre-defined acceptance criteria have not been achieved.

Things To Consider When It Comes To Qualifying Autoclaves

Autoclave Validation / Qualification is mandatory for all machines used for biological sterilization, in the biomedical and pharmaceutical industries. Sterilization can be accomplished by either physical or chemical means. The principal physical means is autoclaving; other physical methods include boiling and dry heat.

Chemicals used for sterilization include the gases ethylene oxide and formaldehyde, and liquids such asglutaraldehyde . Of all these sterilants, autoclaving is the fastest and most reliable, which is why the regulators always scrutinize autoclave validation / Qualification activities.

Here are 10 items to consider when qualifying autoclaves.
1. Testing of Steam for Porous Product Sterilization

Before commencing temperature testing the correct conditions must be satisfied. The first condition for sterilization of porous product is saturated steam quality. The ideal for steam sterilization is dry saturated steam and entrained water (dryness fraction ≥ 97%). The largest heat transfer occurs when the steam is at boundary conditions. If the steam is dry or contains gas then it cannot condense and its effectiveness is reduced.
2. Equipment Used for Testing

The equipment used must support 21 CFR Part 11 and must be of adequate accuracy. Testing with equipment that is not appropriate can be a major problem so also buy from a trusted vendor. As a small temperature range is required for accuracy (A few degrees) the accuracy of the equipment is very important for the overall measuring chain.
3. System Description of Autoclave

The first impression is very important when the qualification of critical equipment such as an autoclave is at stake. A good description of the system in a protocol shows that you understand how the process works and which critical points you need to keep under control. This description must contain the programs that are used, how they work, how many, where the control probes are located and what regulates this process.
4. Operating Instructions, Calibration and Maintenance

Before the temperature is tested it must be checked whether the operating instruction are valid, whether the instruments are calibrated and what was changed in the system since the last qualification occurred.

Operating Instructions must include parameters of sterilization, the scheme item and position of the control probes in the chamber. The emphasis is on the calibration of instruments because small errors in temperature can affect the Fo value to a great extent.
5. Procedure

One of the most common mistakes is inaccurate testing procedures. The test procedure must be unambiguous and accurate and must not leave the possibility for different interpretations.

Ambiguous: Put the thermocouple in a glass bottle.

Unambiguous: Put the thermocouple in a glass bottle at the contact between the bottom of the bottle and the side of the bottle (This is the most critical place to collect condensate).
6. Load

The most common objections are about loads. That they are not sufficiently described and that regular production does not reflect the qualified load being used.

This can be avoided by item photographing and releasing the same patterns in the protocol and work instructions. This will avoid the arbitrary interpretation of descriptive configuration.

Although sometimes this may seem trite the differences in the temperature profiles of the solution and air filters can be great. Pay special attention to the worst case loads and explain the rationale (mostly filter and silicone hose).
7. The Position of the Thermocouples

The position of the thermocouples must be unambiguous and precise to avoid different interpretations by individuals that perform tests or inspections. You do not want to enter into a debate about where the thermocouple is positioned.

Of course, the critical areas must be covered, and this must be explained in the rationale. When sterilizing liquid loads studies must be done to define coldest and warmest point for min and max load.
8. Acceptance Criteria in the Heat Penetration Tests

Since there are differences in the standards (e.g. PDA Technical Report and EN 285) it would be best if all eligibility criteria are taken into account. Special emphasis should be on equilibration time and temperature because it is a requirement for a good Fo.
9. Deviations

Deviations cannot be forgotten as they may be encountered regularly throughout the qualification process. A robust deviation management process should exist as they may impact the quality of the product. Good handling of deviations help us to improve our qualification, though they are often viewed negatively and not as a mechanism for process improvement.
10. Reports

The report should be accurate as it eliminates the use of data from the protocol and the ability to find errors in them. The report should contain the time and the date of tests, parameters, results related to temperature, BI results , positions of thermocouples, Fo and comparison of results from initial and previous qualification in order to see in which direction the process is moving.
Zeljko Joksimovic
Senior Expert Associate for Validation

Tips On How To Investigate Laboratory & Manfacturing Sterility Failures

Sterility can be defined as the freedom from the presence of viable microorganisms. However, the conditions that guarantee absolute sterility are usually too harsh for active ingredients, and the definition of sterility for a medicinal product must be defined in functional terms.

What do you do when you encounter a sterility failure?

It depends on your perspective!

If you are a Lab Technician you get worried and cry……….if you are a Lab Manager you get furious and try to find out who messed up………if you are QA you reject the batch…………….and if you are part of the manufacturing unit you reject the batch.
How can you settle all these concerns methodically?

The problem can be solved by conducting root cause of the failure.

Investigate:

    What went wrong?
    Where did it go wrong?
    What went wrong?
    How did it go wrong?
    How can it go wrong?
    What & who all are involved?

Investigate the Procedure
The investigation shall be done by a team of professional experts based on company specific written procedures and SOP’s.

Conduct based on Risk
Sterility Failure investigation shall be conducted on a System based Approach.
Laboratory System Investigations

Culture Media

    Media Preparation Details (in-house / ready to use / dehydrated media)
    Negative controls results (passes / fails)
    Growth promotion test results (passes / fails)

Sterilizer & Sterilization

    Media sterilization details
    Sterilizer filter Integrity testing records
    Sterilizer Qualification Reports – any cold spots?

Test Procedure

    Test Procedure / SOP
    Sterilizer filter Integrity testing records
    Analytical manipulations done during testing : Reconstitution / Mixing of the Product

Test Equipment

    Open Sterility Equipments -Requires independent Sterilization and assembly
    Closed Sterility Equipments- Ready to use containers

Test Samples

    Sample Transportation and Handling Procedures
    Records of Sanitization / Decontamination of the sample surface

Analyst

    Qualified
    Training Records
    Self Assessment During Stress Conditions
Environmental Monitoring

    Trend Analysis: Recent Out of Trend data
    Comparison of the recovered organism with that of data bank
    Identification of the organism to species level
    Any typical or atypical organism observed
Cleaning & Disinfection

    Records of preparation of the solution
    Filter integrity testing records
    Reports of disinfection agent effectiveness on the recovered organism



Test Environment

    Sterility Performed in a Uni-Directional Air Flow unit in a classified cleanroom
    Investigate reports for : Preventive maintenence , Air velocity, differential pressure, leak rates , sanitization cycles, cleaning records
    Sterility Performed in an Isolator

Top Tips for Pharmaceutical Automation and Validation

Automation is generally considered as a risky subject because of the specialized and technical nature of work. If there is no understanding of how automation is made and designed, it will be very uncompromising to develop an automation system validation strategy. Several studies of software projects have recorded success rates of less than thirty percent, where it was measured based on the schedule, meeting cost estimates, and satisfying requirements.

There are many ways to do automation projects poorly, but just a few ways to do them correctly. The availability of enhanced software tools and techniques makes it visible and testable for the application to the mainstream of the project. This article focuses on new practices and tools to reduce the complexity of the process.
Structure of Automation Projects

Pharmaceutical automation is tough, but when successful, it is very rewarding.

This is the formula for success:

    Meeting schedule milestone and cost estimates;
    Sustaining automation requirements and quality standards;
    Make automation system work right away;
    Satisfying the owners of the business or facilities.

Since, the automated systems will be integrated to the production equipment; this can greatly affect operations, maintenance, profitability, and safety of the finished production facility.

The pharmaceutical industry is regulated by the U.S. Food and Drug Administration (FDA) and the international Ministry of Health. These regulations apply to the manufacturing of drugs and medical devices including the use of computers to manufacture these products.

Since then, the industry’s automation professionals have developed the business processes to support a cradle to grave, life-cycle approach to automation. The industry has had a lot of opportunity over the years to apply business processes to support the delivery of automation.
Beating the Odds

Improve your chances of success with planning, requirements, testing, and documentation. In pharmaceutical automation projects, define and fix your requirements. Have a robust plan, attain management support, and keep the discipline to execute the plan.

There should be organization, consistency, and coordination all throughout the project. Tasks and requirements should be well-defined in the different phases such as design/review, procurement/delivery, and commissioning. Documents are software’s deliverables and these should be specified and given proper resources.

Existing organizations involve in the project such as QA, engineering, maintenance, validation, regulatory affairs and production committees, should be made aware of the scope of their functions and responsibilities. In the later part of the article, we will discuss in detail some techniques and pointers to have a smooth implementation flow.
Conditions Encountered In Project Management

Design specifications should be detailed and complete. Project managers should work hard to complete all information needed. A structured approach that begins with a plan can increase your odds of success. An automation validation master plan defines at a high level the expectations for quality, requirements, testing, documentation, review, and approval. It would also cover expectations for security, change control, maintenance strategy, contingency planning, and periodic reviews.

Since manufacturing facilities are very complicated, design policies should be clearly established recognizing the interest of various stakeholders to attain balance for an efficient operation. The other main part of the plan is to get it approved by the business leaders. In the preliminary planning of a proposed automation upgrade project, controlling cost was identified as the primary issue with getting approval.

For example, the automation team will probably be asked to significantly reduce the estimated cost for the proposed project.  If you have a robust plan, obtain management support, and maintain the discipline to execute the plan, you can achieve your targets. Define the requirements before you start the design, and get the key stakeholders to agree to them. Communicate broadly and keep the requirements fixed during the course of the project design, implementation, and through start-up.
Control Strategy

Along the way, changes cannot be avoided and they would affect the project design, costs, and schedule. A well-established and effective control process is very important. To maximize control, define and fix your requirement.

Accurately define the automation project requirements with the help of the users of the automation system. They should be measurable and testable identifying the industry, tools, and development needs.
Testing

Tests should show the expected functionality of the equipment. Comprehensive and quantitative tests should be created in accordance with the actual specifications to achieve their purpose. The success of testing depends, in part, on good requirements. If a process automation professional has solid and fixed requirements, it would be a lot easier. Inappropriate testing will increase cost and extend the development time. Testing reduces start-up issues.

If a developer does too little testing during the development process, there will be mistakes in the process control application code. The software will then have to be fixed later in the development process or during start-up of the manufacturing equipment in the facility. The sooner a designer catches a mistake, the cheaper it is to fix. Appropriate testing can reduce overall project cost and reduce rework during start-up.
Author

Mark Richardson
IT Quality Specialist
Premier Infrastructure

Disinfectant Testing and Validation

A controlled manufacturing cleanroom environment requires a sound disinfectant testing program. Disinfectants utilized in routine cleaning must be validated to confirm their effectiveness for use. Proper rotation of the disinfectants can be determined based on the data collected in this study.
Why should I choose Microtest Laboratories to perform my disinfectant validation study?
  • Microtest is a high-quality laboratory that has been performing microbiological work for more than 25 years.
  • Our specialized microbiology group possesses years of experience performing qualification work on many different surface types using a wide range of disinfectants.
  • Microtest has an internal collection of ATCC organisms ready for use onsite, plus the ability to identify and cryopreserve client environmental isolates.
How do I know which method to follow for my disinfectant testing study?
Tube Dilution Method
  • For clients with new facilities with little or no environmental trending history.
  • Utilizes ATCC strains and some environmental isolates, where applicable.
  • Isolates are directly inoculated into the desired concentration of disinfectant being tested.
  • Studies of this sort allow a facility to begin production with some assurance that their disinfectants can kill specific microorganisms of concern.
  • Initial screening of disinfectants does not validate that they are effective on hard surfaces.
Coupon Testing Using the Swab Recovery Method
  • For established facilities with environmental programs and trending.
  • Coupons are prepared from the actual surfaces present in the client's clean room environment.
  • The disinfectants are sprayed on the surfaces using the method and contact time that are captured in the client's cleaning procedures.
  • To ensure implementation of a proper disinfection program, the FDA recommends the use of the facility's environmental isolates. However ATCC organisms may be used as well.
Microtest can create a proposal for your disinfectant validation study with the following information:
  • Quantity of surface materials found in your facility
  • Quantity of environmental isolates/ATCC strains to be utilized in study
  • Quantity of disinfectants to be challenged against in study
  • Quantity of time-points to be challenged in the study (time disinfectant sits on a given surface)

A Risk-Management Approach to Cleaning-Assay Validation

By Brian W. Pack,Jeffrey D. Hofer

The authors recommend a strategy for classifying similar nonstainless-steel surfaces into three groups based upon the analytical recovery that was observed in this study.

Cleaning validation and verification are based on the premise of risk management. Several regulatory and guidance documents make this clear. The International Conference on Harmonization's (ICH) guideline on risk management outlines several approaches to making and documenting risk-based decisions (1). It clearly states that risk management should be based on scientific knowledge and that personnel should evaluate the effect of potential failures on the patient. In addition, it notes that the levels of effort, formality (e.g., use of tools), and documentation of the quality risk-management process should be commensurate with the level of risk.
The US Code of Federal Regulations states that equipment and utensils shall be cleaned, maintained, and sanitized at appropriate intervals to prevent malfunctions or contamination that would alter the safety, identity, strength, quality, or purity of the drug product (2). In accordance with 21 CFR 211.67, ICH issued recommendations on equipment maintenance and cleaning (Q7A, Sections 5.20–5.26) for compliance and safety that include similar, but more detailed requirements (3).
The US Food and Drug Administration's 1993 guidance on cleaning inspections states that for a swab method, recovery should be established from the surface (4). The guidance contains no specific requirements about how to establish these recovery estimates, or the acceptance limits. It is up to the manufacturer to document the cleaning rationale (i.e., process and acceptance limits) for maintaining the quality and purity of the drug product being manufactured.
Cleaning validation and verification
Cleaning verification consists of routine monitoring (e.g., swab analysis) of equipment-cleaning processes. Cleaning validation confirms the effectiveness and consistency of a cleaning procedure and eliminates the need for routine testing (5). For example, cleaning limits are established to determine the maximum allowance of Product A that can carry over to Product B. The calculation of these limits is well documented and includes factors that increase the margin of safety to protect the patient (6, 7). Because it is not feasible to swab every square inch of the equipment, swabbing locations are chosen based upon factors such as how difficult the area is to clean, the size of the equipment, and the areas where product buildup is likely. All product-contact surfaces must be considered during cleaning verification to demonstrate that equipment is clean, and a recovery value is expected to be established for each product-contact surface during method validation. The recovery is used to correct the submitted swab result for incomplete removal from the surface and to compare it with the acceptance limit. This last aspect of risk management (i.e., establishing the surface recovery) is the focus of this article.


Figure 1: (ALL FIGURES ARE COURTESY OF THE AUTHORS)
Analysts have many ways to establish the swab-recovery value for a particular product-contact surface. Stainless steel is the most common material in a manufacturing environment (see Figure 1). Some companies therefore establish a recovery value for stainless steel and apply that standard to all swab submissions. Other companies attempt to establish a recovery value for each product-contact surface for every compound. From an analytical standpoint, supporting this activity becomes arduous, if not impossible to sustain. For example, equipment in a clinical-trial materials (CTM) manufacturing area is used for many compounds in the company's portfolio. New equipment might have different product-contact surfaces. Each compound in the portfolio manufactured on a new piece of equipment would require a method revalidation to add a recovery factor for the new product-contact surface. As the number of materials of construction increases, the difficulty of sustaining that approach also increases. Grouping materials of construction for analytical-method development in support of cleaning verification and validation activities is an excellent opportunity to apply a quality risk-management approach, especially when the total product-contact surface area is considered. Stainless steel accounts for approximately 95% of the surface area in a CTM manufacturing and packaging environment. Other product-contact surfaces account for only 5% of the total surface area. When polymer surfaces are considered in a CTM packaging environment, the number of minor product-contact surfaces can grow significantly. A risk-management approach allows the majority of the time and effort to be spent on activities that ensure the cleanliness of the stainless-steel area while identifying, analyzing, evaluating, and communicating the risks associated with the small fraction of remaining surfaces. This strategy does not ignore the surfaces other than stainless steel, but divides them into three recovery groups to support analytical-method validation. By choosing representative recovery surfaces for those nonstainless-steel materials, the effort proportionally addresses the risk.
Design of experiments
Several variables (i.e., roughness average, material of construction, active ingredient, and spiked amount) were evaluated in a randomized fashion to prevent systematic bias that could be introduced by going from the lowest to the highest acceptance limit, from the smoothest to the roughest surface, or from one material of construction to the next. The initial design of experiments included two active pharmaceutical ingredients (APIs), three spiked acceptance-limit levels (i.e., 0.5, 5.0, and 50 μg/swab), seven surface types, four target roughness averages (Ra < 25, 75, 125, and 150 μin.), and six replicates per surface. These Ras were targeted to evaluate whether surface recovery depended on the surface Ra. Coupons were divided into a group of polymers [i.e., Lexan (polycarbonate), acetal (Polyoxymethylene), and PTFE] and a group of metals (i.e., stainless steel 316L, bronze, Type III hard-anodized aluminum, and cast iron). These surfaces were chosen to represent a cross section of surfaces found in the CTM manufacturing and packaging areas and required 1008 swab determinations to complete the study. The remaining product-contact surfaces found in the clinical-trial manufacturing and packaging areas were evaluated according to the initial design of experiments. These surfaces included nickel, anodized aluminum, Rilsan (polyamide), Oilon (blended-oil nylon), and stainless steel 316L with a 4 × 4-in. area.
The authors chose two APIs for this evaluation on the basis of their solubility profiles to represent the most- and least-soluble compounds a company would likely manufacture. Compound A, the less soluble, is slightly soluble in methanol and insoluble across the pH range, but Compound B is soluble in all solvents. In addition, Eli Lilly (Indianapolis, IN) identified Compound A as one of the most difficult compounds to clean from equipment, based on its low solubility and staining properties. A control (i.e., stainless steel 316L, 0.5 μg/swab, Compound A) was run each day that data were generated.
Equipment and operating conditions


Table I: High-performance liquid chromatography (HPLC) operating conditions.
The authors used an Agilent 1100 high-performance liquid chromatography (HPLC) analyzer (Agilent, Santa Clara, CA) for all experiments. The HPLC operating conditions were validated according to ICH standards for precision, linearity, limit of detection (LOD), limit of quantitation (LOQ) and specificity (see Table I) (8). Precision was 1.85% and 3.13% for Compounds A and B, respectively, and was determined at 0.025 μg/mL (i.e., 25% of the lowest spike). The method was linear across the equivalent range of 0.5 μg/swab to 5 μg/swab (R = 0.999). The LOQ was calculated to be 0.005 μg/mL for Compound A and 0.008 μg/mL for Compound B. The LOD was calculated to be 0.001 μg/mL for Compound A and 0.0024 μg/mL for Compound B. Swabs and solvents did not result in interfering peaks. The authors performed swabbing consistently using Texwipe Alpha large swabs (ITW Texwipe, Kernersville, NC). First, 10 vertical swipes, then 10 horizontal swipes were performed for the 2 × 2-in. surfaces. For the 4 × 4-in. surfaces, 20 swipes were executed in each direction. Methanol was used as the swabbing solvent. Spike amounts were 0.5, 5, and 50 μg per surface and were extracted into 5 mL of mobile phase, which corresponded to 0.1-, 1.0-, and 10-μg/mL standard concentrations, respectively. The authors used a Quanta FEG 200F field-emission scanning electron microscope (SEM, FEI, Hillsboro, OR) to generate the surface images. Results and discussion
In this study, a single analyst evaluated the analytical swab recovery from a representative set of surfaces found in the CTM manufacturing and packaging areas. The surfaces were manufactured specifically for this study to have a broad range of Ras. In addition to Ra, the effect of the material of construction, acceptance limit, compound, and method variability also were evaluated. Based upon these data sets, the authors used a strategy involving three groups of materials to represent all of the surfaces in CTM operations. Merck and Co. used a similar strategy to establish five recovery groups (9). The authors expanded on Merck's strategy by adding a detailed study supporting the groups and an approach for determining the appropriate placement of new surfaces into pre-established groups.
Roughness average (Ra). The Ra targets listed above were difficult to achieve. The intermediate Ra values were significantly lower than the target values given in the design of experiments section above. Both intermediate Ra values, initially targeted for 75 and 125 Ra, were measured to be approximately 40 μin. Although the machining process at each level yielded visually different surfaces, the measured Ra changed little from surface to surface. The authors decided to proceed with the surfaces and define smooth surfaces as Ra < 100 μin. and rough surfaces as Ra > 100 μin. This approach allowed for an assessment of the anticipated relationship between Ra and analytical recovery.


Figure 2
The Ra had little impact on the observed analytical-swab recovery, but the recovery was expected to improve with lower Ras. Figure 2 shows roughness grouped by surfaces that had a measured Ra > 100 μin. and by surfaces that had a Ra < 100 μin. Only 5- and 50-μg spikes are represented in Figure 2; the variability in the 0.5-μg spikes confused the interpretation of the data slightly, but is consistent. As Figure 2 shows, the recovery within each roughness group was approximately the same for a given analyte on a given material and did not correlate to Ra. Therefore, Ra should not be used as a predictor of analytical recovery or as a grouping criterion.

Figure 3
Material of construction. Because Ra was eliminated as a factor contributing to recovery losses, the authors performed data analysis by combining all average recovery values and assessing the effect of the material of construction. The data in Figure 3 were first separated by API, and groups were generated to represent the logical separations in recovery. Figures 3(a–c) contain the data for the 0.5-μg spikes, the 5-μg spikes, and the 50-μg spikes, respectively. The data from the 0.5- and 5-μg spikes exhibited a trend similar to that of the 50-μg spikes. The variability in the results increased as the spiked amount decreased, and the 50-μg spike results were substantially less than that of the other spike levels. For both compounds, the Type III hard anodized aluminum exhibited the poorest recovery. The next logical break point grouped bronze and cast iron. The recovery of Compound B from bronze suggested that the material was representative of Group 1. The recovery of Compound A on bronze was lower and more variable, however, so the authors placed bronze into Group 2. For the majority of the surfaces, the recovery of Compound A was lower than that for Compound B at a given limit. In some cases, the recovery was approximately the same (i.e., of 5- and 50-μg spikes on cast iron, and of the 50-μg spike on Type III hard anodized aluminum). In addition, the predominant trend was that the average recovery of a compound increased as the spiked amount increased on a given material of construction. For example, the recovery of Compound B from stainless steel 316L was approximately 74%, 90%, and 95% at 0.5-μg, 5-μg, and 50-μg swabs, respectively.


Figure 4
Ra was originally considered a variable in the experiments previously outlined and did not affect swab recovery. To understand the surface attributes that might contribute to incomplete recovery for the different materials of construction, the authors acquired SEM images for Group 1, Group 2, and Group 3 surfaces (see Figure 4). Stainless steel is a relatively smooth surface with some striations from machining (see Figure 4a). Cast iron has a pitted surface that could provide opportunities for an API in solution to be trapped during a spiking experiment (see Figure 4b). The anodization process makes Type III hard anodized aluminum, the worst recovery surface, porous, thereby creating the greatest opportunity to lose analyte (see Figure 4c). Note that polymers were grouped together with metals and might not be considered to be similar on first pass. The SEM image of Lexan in Figure 4d, however, illustrated that the polymer surface was smooth, albeit with some surface debris, which prevented the loss of analyte. The polymer surface was grouped with stainless steel in Group 1. The SEM images were good supporting evidence that the groupings were logical based upon surface characteristics.


Table II: Grouping of material surface of construction.
Table II is based on the data shown in Figure 3. The top surface in Table II represents the surface that was validated for recovery in each group. This recovery value represented all others within a given group. The groupings were supplied to the CTM areas, and the group number was included on the swab submission to the analytical laboratory so that the correct recovery factor was applied to each surface. In addition, the table served as a tool for engineering to determine whether newly purchased equipment contained a new product-contact surface. Analytical methods. The model and worst-case compound evaluation did not replace any analytical-method validation activities. Analytical recovery must be established for each compound in the portfolio, but not on all surfaces. If multiple limits are to be considered, or if a range of reporting is required, the lowest limit may be evaluated, and that recovery can be applied to all acceptance limits as a conservative estimate. In the analytical method, three recovery factors were presented: Group 1, Group 2, and Group 3. Methods could be validated for any surface within a group and could be considered representative. The authors chose stainless steel 316L because it is the most prevalent, and cast iron because it is a common material on a tablet press. Type III hard anodized aluminum is the only surface in Group 3. This strategy did not ignore any uncommon surfaces. It grouped them appropriately, swabbed them, and applied a representative recovery factor.
Variability. Method variability was evaluated by performing a control sample (Compound A, 6 replicates, 0.5-μg swab, stainless steel 316L, Ra = 3.5) each day. The mean recovery of the entire experiment was 52%. These data suggested that the swabbing ability of the analyst did not change over time. The standard deviation within a day typically was less than 6. The pooled-within-run standard deviation was 3.99 over the course of the experiments. This value was used as a criterion for grouping new surfaces. The day-to-day standard deviation was 15.34.


Figure 5
Incorporating new materials of construction into the grouping strategy. Periodically, new equipment will be introduced into the CTM area that incorporates a product-contact surface made of a material of construction that is not listed in Table II. This problem is often caused by alloys of metals that have already been evaluated and by polymers of proprietary composition. Because surface recovery must be evaluated, personnel need a way to incorporate new surfaces into the groupings outlined in Table II. When a new piece of equipment is purchased, CTM-engineering employees prepare the needed documentation to evaluate the equipment with regard to the cleaning program before use. If an identified sampling location is made of a new material of construction, the engineer asks the person responsible for the cleaning program and analytical development to perform the next steps, which are shown in Figure 5. Suppose that new equipment incorporated three new materials: a crystalline thermoplastic polyester marketed under the trade name of Ertalyte (Quadrant Engineering, Reading, PA), stainless steel 420, and stainless steel 630. Without the grouping strategy in place, method revalidation would have to occur for all compounds handled by this piece of equipment. With the strategy in place, these surfaces are placed into groups based on model-compound recovery. No method revisions are required.
The analytical recovery of Compound A was evaluated for Ertalyte, stainless steel 420, and stainless steel 630 at the 5.0-μg/in. 2 level. The authors used the validated method to evaluate the recovery of the three new surfaces compared with a representative surface from Group 1 (i.e., stainless steel 316L), Group 2 (i.e., cast iron), and Group 3 (Type III hard anodized aluminum). Recovery was evaluated for both the group representative and the new surfaces on the same two days with three replicates on each day. As an alternative, six replicates may be performed on the same day as the controls because the comparison of recovery is relative.



The new surfaces are placed in one of the three groups or define a new lower group, based on how close their average is to that of the group control. The authors obtained a cutoff value of 3.0% in the following manner. Based upon the data for the control, the within-day standard deviation was calculated to be 3.99 and was used in Equation 1. A series of one-sided hypothesis tests with an error rate of α = 0.10 were performed to assess whether the new surface mean was less than a specified control-surface mean. The confidence limit half-width for the difference between the means of two surfaces was computed using the within-day standard deviation because the replicates for each surface had to be run on the same two days, with each day treated as a block. For these calculations, it was assumed that this standard deviation was known. The lower one-sided confidence limit for the difference in means was derived using the following steps: This calculation did not indicate a difference between a control surface and the new surface under evaluation if the recovery differed by less than 3.0%. This approach was conservative because Eq. 1 categorized a new surface into Group 2 if it differed from stainless steel by more than 3.0%, which could be viewed as a strict criterion. Because the results were obtained on the same days and runs, the authors believed that this approach was reasonable. When evaluating the recovery of a new surface, this strategy helps personnel to place each material into the appropriate group. The grouping starts with a comparison of the new surface average to that of Group 1 (stainless steel 316L) and continues sequentially. If the new surface recovery (NSR) is more than 3.0% less than that of the group reference, it is compared with the reference surface in the next lower group until a group is found with which it does not differ by more than 3.0%. If no such group is found, then the new surface forms a new, lower group. The procedure is as follows:
  • If the NSR > mean stainless-steel recovery – 3.0%, the new surface belongs in Group 1.
  • If the NSR > mean cast-iron recovery – 3.0%, the new surface belongs in Group 2.
  • If the NSR > mean Type III anodized aluminum recovery – 3.0%, the new surface belongs in Group 3.
  • If the NSR < mean Type III anodized aluminum recovery – 3.0%, the new surface becomes a new group or becomes the worst-case surface for Group 3 and is used in all future method validations.


Table III: Swab recovery of three new materials of construction compared with controls from each representative group.
The data for the three new surfaces are outlined in Table III. Based on this approach, Ertalyte was placed into Group 1 because the difference between its recovery and that of stainless steel 316L (i.e., Group 1) was less than 3.0% (i.e., 2.48%). The recovery from stainless steel 420 and stainless steel 630 was more than 3.0% less than that from stainless steel 316L, but greater than that from cast iron. The authors placed stainless steel 420 and stainless steel 630 into Group 2. The placement of these two grades of stainless steel into Group 2 highlighted the conservative nature of this approach because their recoveries were only 4% and 8% less than that from stainless steel 316L. The recoveries were 12% and 9% greater than that from cast iron for stainless steel 630 and 420, respectively. Table II was updated to reflect this placement. Because the grouping strategy was conservative, it prevented the underestimation of recovery factors when assay values were reported and prevented the formation of additional groups for method validation unless the recovery value for a new surface is sufficiently low to warrant such an addition.
Conclusion
The authors' data-driven risk-management approach to cleaning verification methods uses analytical-recovery values for a model compound to place product-contact surfaces into groupings for analytical-method validation. The data generated during the studies supported the formation of three recovery groups to validate analytical swab methods. Groups 1–3 were represented by stainless steel 316L, cast iron, and Type III hard anodized aluminum, respectively. This approach allowed all surfaces to be considered during analytical-method validation and provided an objective mechanism to incorporate new surfaces into the strategy.
The benefits of this strategy are numerous. First, only three surfaces must be validated on each compound, which drastically minimizes the number of recovery values established to support the entire portfolio. Second, the strategy includes a way to add new materials of construction to the cleaning program if new equipment is purchased. Traditionally, all swab methods must be revalidated to incorporate the new surface. With this strategy in place, a model compound is evaluated, the new surface is grouped, and no changes to existing methods are required. Third, the strategy allows for a constant state of compliance. A relative recovery value is known for any material of construction for all equipment.
Because the grouping strategy is applied to a small fraction of the total surface area, no surface material of construction is ignored, each molecule undergoes a typical method validation, and the strategy places surfaces into groups conservatively. The authors believe that the strategy controls risks appropriately and that the data set given in this study scientifically supports the strategy of grouping materials of construction to support analytical methods within the cleaning program.
Acknowledgments
The authors would like to acknowledge the following colleagues at Eli Lilly: Gifford Fitzgerald, intern, for generating the swab-recovery data; Ron Iacocca, research advisor, for the SEM data; Sarah Davison, consultant chemist; Mike Ritchie, senior specialist; Mark Strege, senior research scientist; Matt Embry, associate consultant chemist; Kelly Hill, associate consultant for quality assurance; Bill Cleary, analytical chemist; and Laura Montgomery, senior technician, for their contributions and insightful suggestions throughout the project. In addition, Leo Manley, associate consultant engineer, provided the roughness measurements in support of this project.
Brian W. Pack* is a research advisor for analytical sciences research and development, and Jeffrey D. Hofer is a research advisor for statistics, discovery and development, both at Eli Lilly and Company, Indianapolis, IN, tel. 317.422.9043, packbw@lilly.com [packbw@lilly.com]
.

*To whom all correspondence should be addressed.
Submitted: Oct. 12, 2009. Accepted: Dec. 22, 2009.
References
1. ICH, Q9 Quality Risk Management, Step 5 version (2005).
2. Code of Federal Regulations, Title 21, Food and Drugs (Government Printing Office, Washington, DC), Part 211.67.
3. ICH, Q7 Good Manufacturing Practice Guide for Active Pharmaceutical Ingredients, Step 5 version (2000).
4. FDA, Guideline to Inspection of Validation of Cleaning Processes (Rockville, MD, July 1993).
5. L. Ray et al., Pharm. Eng. 26 (2), 54–64 (2006).
6. PDA, Technical Report 29, "Points to Consider for Cleaning Validation" (PDA, Bethesda, MD, Aug. 1998).
7. G.L. Fourman and M.V. Mullen, Pharm. Technol. 17 (4), 54–60 (1993).
8. ICH, Q2 Validation of Analytical Procedures: Text and Methodology, Step 5 version (1994).
9. R.J. Forsyth, J.C. O'Neill, and J.L. Hartman, Pharm. Technol. 31 (10), 102–116 (2007).

Figure 1: (ALL FIGURES ARE COURTESY OF THE AUTHORS)
Table I: High-performance liquid chromatography (HPLC) operating conditions.
Figure 2
Figure 3
Figure 4
Table II: Grouping of material surface of construction.
Figure 5

Table III: Swab recovery of three new materials of construction compared with controls from each representative group.

GMPs for Method Validation in Early Development: An Industry Perspective (Part II)

IQ Consortium representatives explore industry approaches for applying GMPs in early development.

The authors, part of the International Consortium on Innovation and Quality in Pharmaceutical Development (IQ Consortium), explore and define common industry approaches and practices when applying GMPs in early development. A working group of the consortium aims to develop a set of recommendations that can help the industry identify opportunities to improve lead time to first-in-human studies and reduce development costs while maintaining required quality standards and ensuring patient safety. This article is the second in the paper series and focuses on method validation in early-stage development.
The International Consortium on Innovation and Quality in Pharmaceutical Development (IQ) was formed in 2010 as an association of over 25 pharmaceutical and biotechnology companies with a mission to advance science-based and scientifically-driven standards and regulations for medicinal products worldwide. In the June 2012 issue of Pharmaceutical Technology, a paper was presented which described an overview of IQs consolidated recommendations from the Good Manufacturing Practices (GMPs) in Early Development working group (WG) (1). The focus of this IQ WG has been to develop recommended approaches on how to apply GMPs in early phase CMC development activities covering Phase I through Phase IIa. A key premise of the GMPs in Early Development WG is that existing GMP guidances for early development are vague and that improved clarity in the definition of GMP expectations would advance innovation in small-molecule pharmaceutical development by improving cycle times and reducing costs, while maintaining appropriate product quality and ensuring patient safety.
A consequence of the absence of clarity surrounding early phase GMP expectations has been varied in interpretation and application of existing GMP guidances across the industry depending on an individual company's own culture and risk tolerance. Internal debates within a company have frequently resulted in inappropriate application of conservative "one-size-fits-all" interpretations that rely on guidelines from the International Conference on Harmonization (ICH) that are more appropriate for pharmaceutical products approaching the point of marketing authorization application. In many cases, erroneous application of these commercial ICH GMP expectations during early clinical development does not distinguish the distinct differences in requirements between early development and late-stage development (Phase IIb and beyond). A key objective of this IQ WG, therefore, has been to collectively define in early development—within acceptable industry practices—some GMP expectations that allow for appropriate flexibility and that are consistent with existing regulatory guidances and statutes (2).
As outlined in the previous introductory paper, the efforts of the GMPs in Early Development WG have focused on the following four areas of CMC activities: analytical method validation, specifications, drug-product manufacturing, and stability. The initial scope of these efforts has been limited to small-molecule drug development which supports First in Human (FIH) through Phase IIa (Proof-of-Concept) clinical studies. A series of papers describing a recommended approach to applying GMPs in each of these areas is being published within this journal in the coming months. In this month's edition, the authors advocate for a life-cycle approach to method validation, which is iterative in nature in order to align with the evolution of the manufacturing process and expanding product knowledge space.
A pharmaceutical industry collective perspective on analytical method validation with regard to phase of development has not been published since 2004 (3). Genesis of the 2004 paper occurred during a set of workshops sponsored by the Analytical Technical Group of the Pharmaceutical Research and Manufacturers of America (PhRMA) in September 2003. The referenced paper summarized recommendations for a phased approach to method validation for small-molecule drug substance and drug products in early clinical development. Although a few other reviews on method validation practices have been published (4), this paper provides a current, broad-based industry perspective on appropriate method validation approaches during the early phases of drug-product development.
This broad industry assessment of method validation also uncovered the need to clearly differentiate the context of the terms of "validation" and "qualification." Method qualification is based on the type, intended purpose, and scientific understanding of the type of method in use during the early development experience. Although not used for GMP release of clinical materials, qualified methods are reliable experimental methods that may be used for characterization work, such as reference standards and the scientific prediction of shelf-life.
A perspective on some recent analytical method challenges and strategies, such as genotoxic impurity methods, use of generic methods, and methods used for testing toxicology materials or stability samples to determine labeled storage conditions, retest periods and shelf life of APIs and drug products are also presented. The approach to method validation described herein is based on what were considered current best practices used by development organizations participating in the IQ consortium. In addition, this approach contains some aspects which represent new scientifically sound and appropriate approaches that could enable development scientists to be more efficient without compromising product quality or patient safety. These science-driven acceptable best practices are presented to provide guidance and a benchmark for collaborative teams of analytical scientists, regulatory colleagues, and compliance experts who are developing standards of practice to be used during early phases of pharmaceutical development. The views expressed in this article are based on the cumulative industry experience of the members of the IQ working group and do not reflect the official policy of their respective companies.
Early-phase method parameters requiring validation


Table I: Summary of proposed approach to method validation for early- and late-stage development.
In early development, one of the major purposes of analytical methods is to determine the potency of APIs and drug products to ensure that the correct dose is delivered in the clinic. Methods should also be stability indicating, able to identify impurities and degradants, and allow characterization of key attributes, such as drug release, content uniformity, and form-related properties. These methods are needed to ensure that batches have a consistent safety profile and to build knowledge of key process parameters in order to control and ensure consistent manufacturing and bioavailability in the clinic. In the later stages of drug development when processes are locked and need to be transferred to worldwide manufacturing facilities, methods need to be cost-effective, operationally viable, and suitably robust such that the methods will perform consistently irrespective of where they are executed. In considering the purpose of methods in early versus late development, the authors advocate that the same amount of rigorous and extensive method-validation experiments, as described in ICH Q2 Analytical Validation is not needed for methods used to support early-stage drug development (5). This approach is consistent with ICH Q7 Good Manufacturing Practice, which advocates the use of scientifically sound (rather than validated) laboratory controls for API in clinical trials (6). Additionally, an FDA draft guidance on analytical procedures and method validation advocates that the amount of information on analytical procedures and methods validation necessary will vary with the phase of the investigation (7). IQ's perspective regarding which method parameters should be validated for both early- and late-stage methods is summarized in Table I. In this table, identification methods are considered to be those that discriminate the analyte of interest from compounds with similar (or dissimilar) structures or from a mixture of other compounds to assure identity. This category includes, but is not limited to identification methods using high-performance liquid chromatography (HPLC), Fourier transform infrared spectroscopy (FTIR), and Raman Spectroscopy. Assay methods are used to quantitate the major component of interest. This category includes, but is not limited to drug assay, content uniformity, counter-ion assay, preservative's assay, and dissolution measurements. Impurity methods are used for the determination of impurities and degradants and include methods for organic impurities, inorganic impurities, degradation products, and total volatiles. To further differentiate this category of methods, separate recommendations are provided for quantitative and limit test methods, which measure impurities. The category of "physical tests" in Table I can include particle size, droplet distribution, spray pattern, optical rotation, and methodologies, such as X-Ray Diffraction and Raman Spectroscopy. Although representative recommendations of potential parameters to consider for validation are provided for these physical tests, the specific parameters to be evaluated are likely to differ for each test type.
When comparing the method-validation approach outlined for early development versus the method-validation studies conducted to support NDA filings and control of commercial products, parameters involving inter-laboratory studies (i.e., intermediate precision, reproducibility, and robustness) are not typically performed during early-phase development. Inter-laboratory studies can be replaced by appropriate method-transfer assessments and verified by system suitability requirements that ensure that the method performs as intended across laboratories. Because of changes in synthetic routes and formulations, the impurities and degradation products formed may change during development. Accordingly, related substances are often determined using area percentage by assuming that the relative response factors are similar to that of the API. If the same assumption is used to conduct the analyses and in toxicological impurity evaluation and qualification, any subsequent impurity level corrections using relative response factors are self-corrective and hence mitigate the risk that subjects would be exposed to unqualified impurities. As a result, extensive studies to demonstrate mass balance are typically not conducted during early development.
In addition to a smaller number of parameters being evaluated in preclinical and early development, it is also typical to reduce the extent of evaluation of each parameter and to use broader acceptance criteria to demonstrate the suitability of a method. Within early development, the approach to validation or qualification also differs by what is being tested, with more stringent expectations for methods supporting release and clinical stability specifications, than for methods aimed at gaining knowledge of processes (i.e., in-process testing, and so forth). An assessment of the requirements for release- and clinical-stability methods follows. Definitions of each parameter are provided in the ICH guidelines and will not be repeated herein (5). The assessment advocated allows for an appropriate reduced testing regimen. Although IQ advocates for conducting validation of release and stability methods as presented herein, the details are presented as a general approach, with the understanding that the number of replicates and acceptance criteria may differ on a case-by-case basis. As such, the following approach is not intended to offer complete guidance.
Specificity. Specificity typically provides the largest challenge in early-phase methods because each component to be measured must be measured as a single chemical entity. This challenge is also true for later methods, but is amplified during early-phase methods for assay and impurities in that:
  • The chemical knowledge regarding related substances is limited.
  • There are frequently a greater number of related substances than in commercial synthetic routes.
  • The related substances that need to be quantified may differ significantly from lot-to-lot as syntheses change and new formulations are introduced.
A common approach to demonstrating specificity for assay and impurity analysis is based on performing forced decomposition and excipient compatibility experiments to generate potential degradation products, and to develop a method that separates the potential degradation products, process impurities , drug product excipients (where applicable), and the API. Notably, requirements are less stringent for methods where impurities are not quantified such as assay or dissolution methods. In these cases, specificity is required only for the API.
Accuracy. For methods used in early development, accuracy is usually assessed but typically with fewer replicates than would be conducted for a method intended to support late-stage clinical studies. To determine the API in drug product, placebo-spiking experiments can be performed in triplicate at 100% of the nominal concentration and the recoveries determined. Average recoveries of 95–105% are acceptable for drug product methods (with 90–110% label claim specifications). Tighter validation acceptance criteria are required for drug products with tighter specifications. For impurities, accuracy can be assessed using the API as a surrogate, assuming that the surrogate is indicative of the behavior of all impurities, including the same response factor. Accuracy can be performed at the specification limit (or reporting threshold) by spiking in triplicate. Recoveries of 80—120% are generally considered acceptable, but will depend on the concentration level of the impurity. For tests where the measurements are made at different concentrations (versus at a nominal concentration), such as dissolution testing, it may be necessary to evaluate accuracy at more than one level.
Precision. For early-phase methods, only injection and analysis repeatability is examined. Area % relative standard deviation (RSD) is typically determined from 5 replicates. Repeatability is determined at 100% of nominal concentration for the API with impurities being evaluated at the reporting threshold using the API as a surrogate. Acceptance criteria of 1% RSD (injection repeatability) or 2% RSD (analysis repeatability) for API are frequently targeted. For impurities, higher precision limits (e.g., 10–20%) are acceptable and should consider the level of the impurity being measured (injection and analysis repeatability). For tests where the measurements are made at different concentrations (versus at a nominal concentration), such as dissolution testing, it may be necessary to evaluate repeatability at more than one level.
Limit of detection and limit of quantitation. A sensitivity assessment is necessary to determine the level at which impurities can be observed. Using the API as a surrogate, a "practical" assessment can be made by demonstrating that the signal of a sample prepared at the reporting threshold produces a signal-to-noise ratio of greater than 10. A limit of quantitation can be determined from this assessment by calculating the concentration that would be required to produce a signal to noise ratio of 10:1. Similarly, a limit of detection can be calculated as the concentration that would produce a signal-to-noise ratio of 3:1. However, it is emphasized that the "practical limit of quantitation" at which it is verified that the lowest level of interest (reporting threshold) provides a signal at least 10 times noise and thus can be quantitated, is of paramount importance.
Linearity. Linearity can be determined from 3-point calibration curves at test concentrations of 70, 100, and 130% of nominal (API) for assay or from 3 points ranging from the reporting threshold to 130% of the specification limit for impurities. API is used as the surrogate analyte for impurities. For both analyses, a validation criterion can be established as R 2 > 0.995. For tests where the measurements are needed over broader concentration ranges, such as dissolution testing, a broader linear range may be examined using a 3-point calibration.
Range. As for late-phase methods, the range is inferred from the accuracy, precision, and linearity studies.
Robustness. Full robustness testing is not conducted during early development. However, an assessment of solution stability should be conducted to demonstrate the viable lifetime of standards and samples. Specifically, solutions should be considered stable when the following conditions are met:
  • The API assay changes by not more than 2%
  • No new impurities greater than the reporting threshold are observed
  • Impurities at the reporting threshold change by not more than 30%; impurities at levels between the reporting threshold and the specification limit change by not more than 20%; and impurities at or above the specification limit change by not more than 15%.
Notably, if validation is performed concurrently with sample analysis as an extended system suitability, solution stability must be assessed separately. This assessment is typically conducted as part of method development.
Early-phase methods requiring validation
During discussions held to develop this approach to early-phase method validation, it was evident that the context of the terms "validation" and "qualification" was not universally used within all the IQ member companies. To facilitate a common understanding of this approach, the authors will therefore refer to "validated methods" as those methods which perform as expected when subjected to the series of analytical tests described in this approach. "Qualified methods" are considered to be analytical methods which are subjected to less stringent testing to demonstrate that they are scientifically sound for their intended use. In the following sections, the authors recommend which types of methods typically employed in early development require either validation or qualification.
Methods for release testing and to support GMP manufacturing. In early development, specifications are used to control the quality of APIs and drug products. Consideration of specifications places great emphasis on patient safety since knowledge of the API or drug product process is limited due to the low number of batches produced at this stage of development. Specifications typically contain a number of different analytical tests that must be performed to ensure the quality of the API or drug product. Typical material attributes, such as appearance, potency, purity, identity, uniformity, residual solvents, water content, and organic/inorganic impurities, are tested against established acceptance criteria. The API and drug-product specific methods for potency, impurity, uniformity, and others should be validated as described above and demonstrated to be suitable for their intended use in early phase development prior to release. If compendial methods are used to test against a specification (e.g., FTIR for identification and Karl Fischer titration [KF] for water content), they should be evaluated and/or qualified to be suitable for testing the API or drug product prior to use without validation. Materials used in the manufacture of GMP drug substance and drug product used for early-phase clinical studies for which specifications are not outlined in a regulatory filing (e.g., penultimates, starting materials, isolated intermediates, reagents, and excipients) need only to be qualified for their intended use. Method transfer is less rigorous at this early stage of development and may be accomplished using covalidation experiments or simplified assessments.
As mentioned, method qualification is often differentiated from method validation. The experiments to demonstrate method qualification are based on intended purpose of the method, scientific understanding of the method gained during method development and method type. It is an important step in ensuring that reliable data can be generated reproducibly for investigational new drugs in early development stages. The qualified methods should not be used for API or drug product release against specifications and concurrent stability studies. However, reference material characterization may be done with qualified methods.
Generation of process knowledge in early development is rapidly evolving. Numerous samples are tested during early development to acquire knowledge of the product at various stages of the process. The results from these samples are for information only (FIO) and methods used for this type of testing are not required to be validated or qualified. However, to ensure the accuracy of the knowledge being generated, sound scientific judgment should be used to ensure the appropriateness of any analytical method used for FIO purposes.
"Generic" or "general" methods. A common analytical strategy often employed in early development is the use of fit-for-purpose generic or general methods for a specific test across multiple products (e.g., gas chromatography for residual solvents). These methods should be validated if they are used to test against an established specification. The suggested approach to validating these methods in early development is typically performed in two stages. Stage 1 involves validating the parameters that are common for every product with which the method can be used. Linearity of standard solutions and injection repeatability belong to this stage. Stage 2 of the validation involves identifying the parameters that are specific to individual product, such as accuracy. Specificity may be demonstrated at Stage 1 for nonproduct related attributes and at Stage 2 for product related attributes. Stage 1 validation occurs prior to GMP testing. Stage 2 validation can happen prior to or concurrent with GMP testing. This approach to validation of fit-for-purpose methods can provide efficiency for drug development by conserving resources in the early phases of development and can ensure reliability of the method's intended application.
Methods for GTI and tox batch qualification. The need for analytical methods to demonstrate the control of genotoxic impurities (GTI) has developed recently because of expectations and guidances provided by regulatory authorities (8, 9). Often, these methods require high sensitivity with limits of quantitation in the parts-per-million (ppm) range. Although the control levels for GTIs (referred to as the threshold of toxicological concern) is less stringent for early clinical studies (e.g., patient intake < 50 ug/day for clinical studies < 30 days vs 1.5 ug/day for longer clinical studies), regulatory authorities expect that GTI control is demonstrated during early development. Depending on when a GTI is potentially generated during an API synthesis, GTIs may be listed in specifications. Validation of these methods is again dependent upon the intended use of the method. Methods used for assessment may be qualified unless they are used to test against a specification as part of clinical release. Method qualification is also considered appropriate if the method is intended for characterization or release of test articles for a toxicology study.
Methods for stability of APIs and drug products. Batches of API and drug product are typically exposed to accelerated stress conditions and tested at timed intervals to assess whether any degradation has occurred. The shelf-life of the API or drug product—that is, the time period of storage at a specified condition within which the drug substance and drug product still meets its established specifications, is based on analytical data generated from these studies. For this application, analytical methods need to be stability-indicating (e.g., capable of detection and quantitation of the degradants) to ensure quality, safety, and efficacy of a drug substance and drug product. Often, the analytical methods used to perform stability tests are the same methods used to test against a specification for release testing; these methods should be validated. However, if additional tests are performed which are not included in the established specification, they may be qualified for their intended use, rather than validated.
In-process testing methods. In-process testing (IPT) during manufacturing of drug substance and drug product can be done on-line, in-line, or off-line. The results generated from IPT are used to monitor processes involving reaction completion, removal of solvents, removal of impurities, and blend content uniformity. Manufacturing parameters may be adjusted based on IPT results. IPT methods are often very limited in scope. In early development, the primary benefit of performing IPTs is the generation of process knowledge, and not as a control or specification. As a result, even though IPT is essential for manufacture of drug substance and drug product, method qualification for an IPT method is appropriate in early-phase development.
Documentation and other requirements. The extent of documentation and associated practices in early development should be aligned with the appropriate level of method validation as discussed above. In this paper, the authors provide a perspective on the appropriate level of documentation, protocol and acceptance-criteria generation, instrument qualification, and oversight of the quality assurance unit for early-phase method validation and qualification. This approach provides development scientists with flexibility to efficiently adapt to the dynamic environment typical within early phase pharmaceutical development, while ensuring patient safety and the scientific integrity of the validation process.
With respect to documentation, it the IQ perspective that the raw data which is generated during early phase method validation should be generated and maintained in a compliant data storage format. The integrity of raw data should be controlled such that it can be retrieved to address future technical and compliance-related questions. Proper documentation of data and validation experiments should also be considered an important aspect of early phase validation. The availability of electronic notebook (ELN) systems has provided a viable, more efficient alternative to the use of traditional bound-paper notebooks. In developing policies to implement ELNs, the goal should not be that all documentation practices used with paper notebooks are replicated. Rather, the ELN should possess sufficient controls for the intended use of the data. In many cases, electronic systems such as ELNs will transform the work process, and the controls it provides will be achieved in a completely novel manner compared to the outdated system being replaced.
Although data needs to be documented as described above, it is the authors' position that formal, detailed method and validation reports are not required to ensure compliance in early development. Adequate controls need to be in place to ensure method parameters used to execute validated methods are equivalent to parameters used during validation. Generation of brief method and validation summary reports are required only when needed to fulfill regulatory filing requirements or to address requests or questions from health authorities. Validation summaries are not required to present all of the validation data, but rather a summary of the pertinent studies sufficient to demonstrate that the method is validated to meet the requirements of its intended use. Once reports are generated and approved internally, approved change control procedures should be available and followed to maintain an appropriate state of control over method execution and report availability.
Although the authors' perspective is that a validation plan needs to exist for early phase method validation, analytical organizations could consider different mechanisms to fulfill this need. For example, internal guidelines or best practice documents may sufficiently outline validation requirements such that a separate validation plan need not be generated for each method. In the absence of such a guideline or procedure, a validation plan could be documented in a laboratory notebook or ELN which includes a brief description of validation elements and procedures to be evaluated. Validation plans should ensure that the method will be appropriate for its intended use. The use of strict validation criteria within the validation plan should be limited at these early stages of development. Validation studies for early development methods may be performed on fit-for-purpose instruments which are calibrated and maintained, but not necessarily qualified or under strict change-control standards.
The role of the pharmaceutical quality system and the oversight over early phase method validation practices and documentation is another area for consideration. In the pharmaceutical industry, quality management is overseen by a "Quality Unit" that qualifies and oversees activities in the areas of GMP materials such as laboratory controls. In practice, the size and complexity of the Quality Unit overseeing GMP manufacturing varies based on a manufacturer's size and stage of drug development. Regardless, the basic aspects of a quality system must be in place. In early development, IQ's position is that, because API and drug-product manufacturing processes are evolving, the analytical methods do not yet require full validation as prescribed in ICH Q2. Correspondingly, the quality system implemented during early phases could consider that evolving analytical methods are intrinsic to the work being performed to develop the final API and drug product processes and could allow flexibility to readily implement method changes during early development. For example the Quality Unit should delegate oversight for validation plan approval, change control, approval of deviations and reports to the analytical departments prior to finalization and performing full ICH Q2 validation of the analytical methods. This approach would be consistent with Chapter 19 of ICH Q7A. However, analytical departments must ensure that early phase validation studies are conducted by qualified personnel with supervisory oversight who follow approved departmental procedures. Clearly, agreements between Quality Units and analytical departments to implement an appropriate strategic, phase-based quality oversight system would provide many benefits within the industry.
Conclusions
Within this paper, IQ representatives have presented an industry perspective on appropriate requirements and considerations for early phase analytical method validation. A suggested outline of acceptable experiments that ensure analytical procedures developed to support API and drug product production of early phase clinical materials are suitable for their intended use has been presented. Additionally, the authors have provided a position on phased approaches to other aspects of method validation such as documentation requirements, generation of method validation plans, validation criteria, and the strategic involvement of quality unit oversight. When applied appropriately, this approach can help to ensure pharmaceutical development organizations provide appropriate analytical controls for API and drug product processes which will serve the ultimate goal of ensuring patient safety. Although the extent of early-phase method validation experiments is appropriately less than employed in the later stages of development, we view that any risks related to this approach will not be realized, especially when considering the overall quality and safety approach used by pharmaceutical companies for early phase clinical studies.
It is the authors' hope that providing such an approach to early-phase method validation, along with the approaches outlined in this series of early-phase GMP papers, will serve as a springboard to stimulate discussions on these approaches within the industry and with worldwide health authorities. To encourage further dialogue, this IQ working group is planning on conducting a workshop in the near future to promote robust debate and discussion on these recommended approaches to GMPs in early development. These discussions will ideally enable improved alignment between R&D development, Quality, and CMC regulatory organizations across the pharmaceutical industry, and most importantly with worldwide regulatory authorities. Agreement between industry and health authorities regarding acceptable practices to applying GMPs in the early phases of drug development would clearly be beneficial to CMC pharmaceutical development scientists and allow for a more nimble and flexible approach to better address the dynamic environment typical of the early phases of clinical development, while still guaranteeing appropriate controls to ensure patient safety during early development.
Donald Chambers is in analytical sciences at Merck Research Laboratories, Gary Guo is in analytical R&D at Amgen, Brent Kleintop* is in analytical and bioanalytical development at Bristol-Myers Squibb Co., Henrik Rasmussen is in analytical development at Vertex Pharmaceuticals, Steve Deegan is in GMP Quality Assurance Operations at Abbott, Steven Nowak is in NCE Analytical R&D, Global Pharmaceutical R&D, at Abbott, Kristin Patterson is in emerging markets R&D at GlaxoSmithKline, John Spicuzza is in analytical development at Baxter, Michael Szulc is in analytical development at Bioden Idec, Karla Tombaugh is in R&D/Commercialization Quality, Merck Manufacturing Division, at Merck & Co., Mark D. Trone is in analytical development, small molecule, at Millennium Pharmaceuticals, and Zhanna Yuabova is in analytical development, US, at Boehringer Ingelheim Pharmaceuticals.
*To whom all correspondence should be addressed.
References
1. A. Eylath at al., Pharm. Technol. 36 (5) 54–58 (2012).
2. FDA, Guidance for Industry: cGMP for Phase 1 Investigational Drugs (July 2008 FDA).
3. S.P. Boudreau et al., Pharm. Technol. 28 (11) 54–66 (2004).
4. M. Bloch, "Validation During Drug Product Development – Considerations as a Function of the Stage of Drug Development," Method Validation in Pharmaceutical Analysis, a Guide to Best Practice, Eds. J. Ermer, J.H. Miller (Wiley, 2005), pp. 243–264.
5. ICH, Q2 (R1) Validation of Analytical Procedures: Text and Methodology (Nov. 2005).
6. ICH, Q7A Good Manufacturing Practice Guidelines for Active Pharmaceutical Ingredients (Aug. 2001).
7. FDA, Draft Guidance for Industry: Analytical Procedures and Method Validation, Chemistry, Manufacturing and Controls Documentation (Aug. 2000).
8. EMA, Guideline on the Limits of Genotoxic Impurities (June 2006).
9. FDA, Draft Guidance for Industry: Genotoxic and Carcinogenic Impurities in Drug Substances and Products: Recommended Approaches (2008).

Table I: Summary of proposed approach to method validation for early- and late-stage development.