Validation of Microbiological Tests

The variety of microbiological tests makes it difficult, if not impossible, to prescribe a single, comprehensive method for validating all types of tests. By their very nature, microbiological tests possess properties that make them different from chemical tests. Consequently, the well-known procedures for validating chemical tests are not appropriate for many microbiological tests. Yet, it is necessary to validate microbiological tests if they are to be useful for controlling the quality of drug products and devices. Test-method validation provides assurance that a method is suitable for its intended use. Given this definition, any rational company would want to be sure that its methods are validated.

Some tests, such as bioburden or viral titer tests, are quantitative in nature while other tests, such as those for the presence of objectionable organisms, are qualitative. As with chemical tests, these differences necessitate different validation approaches. The purpose of a test also may change the procedures for running and validating it. As an example, consider a drug that will be orally administered. Normally, sterility is not a major issue, and the specification allows for a considerable number of organisms. However, if the drug will be administered to immunocompromised cancer or AIDS patients, the bioburden level must be reduced considerably, increasing the test sensitivity required in the validation study.

The nature of the test material itself changes how a test is run and the validation protocol. Consequently, testing for objectionable organisms is different when testing a diuretic for hypertension or an antibiotic for treating pneumonia. Also, a procedure that works perfectly well for checking the bioburden of granulated sugars may fail with sodium chloride. These differences make full coverage of the topic impossible within the context of this primer. This article will present the general considerations that apply to most microbiological tests. However, three excellent publications are available to analysts preparing validation study protocols for microbiological methods (see Suggested Reading).

Note also that certain microbiological tests are already associated with well defined validation procedures. For example, the endotoxin test and USP bacterial enumeration tests have clearly defined validation procedures. In addition, individual countries may have specific requirements that modify or change standard procedures. If a test is associated with a compendial or regulatory validation procedure, workers are advised to follow that procedure unless there are clear reasons for not doing so. In such cases, the reasons should be documented and filed with the test procedure. Media The suitability of the medium used for cultivating organisms or cells obviously can have a major impact on the test results. Some organisms are extremely fastidious and require a precisely defined medium with several complex nutrients, while others grow in the presence of inorganic salt mixtures and simple carbon sources. It is commonly argued that delicate, fastidious organisms cannot survive manufacturing processes and should not be of concern, but organisms as delicate and fastidious as mycoplasmas can appear in final preparations of biologics.

In addition to the nutrient composition of the media, more general factors such as pH and ionic strength must be validated. While it is commonly believed that media in the range of pH 6.0 – 8.0 are suitable for sterility and bioburden studies, individual organisms may require a more restricted range. The same holds true for ionic strengths and osmolalities outside of the human physiological range. Shifting the pH range from 6.0 – 7.0 to 7.0– 8.0 and raising the ionic strength to 300 mOsm may select for a different set of organisms than those that would be present in the lower pH range at 150 mOsm.

Most validation schemes require the use of five or more "indicator organisms" to demonstrate the medium's ability to support growth. In addition to aerobic bacteria, anaerobic organisms, yeasts, and molds are usually included. This is an important step since a finding of "no growth detected" is meaningless if the medium was incapable of growing any organisms. This leads to two important points.

First, the indicator organisms are supposedly representative of the types of organisms that will be encountered during the testing, but this is not necessarily true. The indicator organisms are a subset of organisms that are known to grow on properly prepared media, but the organisms contaminating a manufacturing process may not belong to that subset. As a result the quality control laboratory may repeatedly face what appears to be a microbial contamination event despite monitoring cultures that show no growth. It is very important to know what organisms are normally present in the working environment and to include these environmental isolates in a validation program. There is little value in proving that a medium will support the growth of indicator organisms if the environment is full of organisms with very different cultivation requirements.

The second issue involves media handling. The qualification or validation study may require autoclaving the medium and then pouring culture plates as the autoclaved material cools. In laboratories with a low testing load, the excess material is often poured into large tubes or culture flasks to cool and solidify and then stored for future use, usually in a refrigerator. However, when future testing is done, the second heating of the medium may not be captured in the qualification or validation check and may not even be mentioned in the test procedure. If the agar is melted under gentle conditions and quickly poured, there may be no problem, but in some cases, technicians have placed the flasks in microwave ovens to heat the medium while taking a short break. With a powerful microwave oven it is easy to boil the medium for an unknown period of time. This can destroy nutrients or produce toxic or inhibitory substances. Consequently, in laboratories where this second heating is a common practice, this procedure must be captured in the validation and described exactly in the test procedures.

When preparing the validation protocol, the analyst should specify the recovery level expected for each of the indicator organisms. Generally, recovery of at least 80% of the inoculum or control is desirable. Recovery of less than 50% is usually unacceptable and should raise questions about the presence of inhibitory substances, especially when the testing is taking place in the presence of a raw material or product intermediate. It may be necessary to introduce — and validate the performance of — an agent that inactivates the inhibitor. It is important to set the specifications before the study is conducted and to hold to these specifications. If specifications are not pre-set and the test system cannot meet general acceptance specifications, it is very easy to set "acceptable" specifications that would otherwise have been unacceptable. The other problem is the "specification creep" that occurs when a recovery of 78% is found and the specification is 80%. A quality assurance or quality control worker who allows the 78% to pass will soon face the expectation that 75% should pass because it is "only slightly different from the other one." Over the course of a few years, an 80% specification can gradually turn into a 70%, then 65%, specification.

Environment The incubation temperature can have a major effect on the ability of an organism to grow in a given medium. It is well known that yeasts and molds require a different incubation temperature than bacteria in a sterility test. Similarly, cells in tissue culture are often extremely sensitive to small changes in temperature, not only for their growth but also in their susceptibility to being infected or lysed by viruses. The analyst may need to develop temperature curves to justify the incubation temperatures used for the test. It is also important to verify the incubator's ability to maintain the set temperature within the specified range. If a four-degree temperature variation can cause a significant change in the test results, the incubator's ability to hold a ±1° C range at all internal locations is critical. This may not be covered in a validation study, but it should be included in the incubator's qualification studies.

In addition to the usual range from 20 – 40° C, it may be necessary to demonstrate the ability to grow organisms at extreme temperatures. If it is necessary to monitor the presence of microbes in a hot or cold room, it will be necessary to demonstrate an ability to cultivate thermophiles or psychrophiles in addition to organisms that grow under more normal conditions. While the significance of these extremophiles may be open to question, their presence and the possibility that they may leave residues such as endotoxins must be considered.

The atmosphere in which the test system is immersed can have a major effect. Anaerobic organisms cannot grow in the presence of oxygen, and tissue cultures may require the presence of 5% CO₂ to grow well. Certain facultative organisms will adjust their metabolic paths to cope with reduced levels of oxygen. This, in turn, can affect their growth rates. When media for general purposes, such as sterility tests, are being considered, it is normal to include one medium that provides anaerobic conditions. The detection of anaerobes is important as they include toxin-producing and other pathogenic bacteria.

Quantitative Issues One of the problems with quantitative microbiological tests is that as microbe counts become smaller, straight-forward linear behavior is less common than that which follows the Poisson distribution. This is because random distribution is not even distribution. Most quantitative tests for microorganisms require the plating of dilute liquid samples, and it is normal to prepare samples to ensure the dispersion of microbes and a random distribution of bacteria or viruses. When concentrations are high, the lack of even distribution is not a problem; simple linear averaging methods can compensate for the uneven distribution. Problems arise with smaller numbers of microbes.

Consider an example where there are exactly 100,000 organisms per mL. If 0.1 mL is taken and mixed with 0.9 mL of a diluent, it is highly unlikely that the new suspension will contain exactly 10,000 organisms; it would not be surprising to have anywhere from 9,800 – 10,200 organisms. Back-calculating the result produces a range from 98,000 – 102,000 organisms in the original sample, and, if there were enough replicates, the results could be averaged to obtain a number indistinguishable from 100,000. This is the result that would be expected based on linear thinking.

However, if there were only 10 organisms per mL, it is quite possible that a 0.1 mL aliquot would not contain any organisms at all. In fact, in this situation about one third of the aliquots will not contain a single organism. This could lead to the conclusion, on averaging, that the sample only contained 6.7 organisms per mL, which is a significant deviation from the true value.

A transition occurred from a high density that produces a fairly smooth, homogeneous distribution of organisms to a low density that results in organisms that are distributed with significant distances between them. Under these conditions, the suspension behaves according to the Poisson distribution and assumptions related to a normal distribution no longer hold. The Poisson distribution is an exponential function. The problem is that parameters such as the standard deviations may be logarithmic in nature, and when attempts are made to make these numbers "real" by taking the antilogarithms, the results may actually have no "real" meaning. This can cause great difficulties when attempting to validate quantitative microbial test procedures.

When it is necessary to deal with the Poisson distribution, it is wise to consult a statistician who is versed in the use of this distribution. It appears that the transition to the Poisson distribution occurs when approximately 100 colonies or plaques are counted. This is unfortunate because at this level many analysts will declare a colony or plaque count to be "too numerous to count" (TNTC) to avoid the tedium of these measurements. Therefore, most colony or plaque counting procedures actually operate under the Poisson distribution and calculations based on the normal distribution will be incorrect.

Revalidation The frequency of revalidation is a contentious question. There are many tests, such as the growth promotion test on culture media, that are essentially self-validating and are run frequently. It could be argued that if performance parameters (for example, percent recovery of indicator organisms) are monitored via control charting and no significant changes are seen, revalidation is unnecessary. However, control charting usually does not measure all the parameters included in validation studies. Consequently, it is wise to revalidate tests after any major change in constituents or procedures; in fact, revalidation may be needed to justify the changes. Changes in suppliers (especially of media components) and changes in the composition of test samples have resulted in major changes in microbiological tests. Finally, it is probably wise to revalidate procedures approximately every second year to protect against unseen or unreported changes. A media supplier may change its own suppliers or change its processing procedures without notifying customers. The supplier may have no idea of the impact these changes could have on the end use of their product. In addition, personnel changes in the laboratory and the maturing of analysts' techniques can have an effect.

Suggested Reading Carroll MC. A multifaceted look at the microbial limits test. In: R Prince, editor. Microbiology in Pharmaceutical Manufacturing. Baltimore, MD: PDA; 2001. pp. 519–535.

PDA. Evaluation, validation and implementation of new microbiological testing methods: PDA Technical Report No. 33. PDA Journal of Pharmaceutical Science and Technology 2000; 54(Suppl. TR33).

Petitti DM. Practical considerations for the development, validation, and transfer of analytical test methods. In: R Prince, editor. Microbiology in Pharmaceutical Manufacturing. Baltimore, MD: PDA; 2001. pp. 723–746.

Steven S. Kuwahara, Ph.D., is the principal consultant and founder of GXP BioTechnology LLC, PMB 506, 1669-2 Hollenbeck Avenue, Sunnyvale, CA 94087-5042, 408.530.9338

Validating Analytical Methods for Biopharmaceuticals, Part 2: Formal Validation

By: Stephan Krause, PhD
BioPharm International

Stephan O. Krause, Ph.D.

When developing a new method for a new biopharmaceutical product, or when changing a release method for a licensed product, many development and validation elements should be considered. Currently, these are incompletely covered by regulatory guidelines.^1-4 Analytical method validation (AMV) follows analytical method development (AMD), which we described in the October issue of BioPharm International.⁵ Often, identifying and fully developing an appropriate test methodology is the critical task in the overall process.

The AMV protocol and report should formally verify that the method is valid (from a quality and product-release perspective) and validated (from a compliance perspective).^6,7 The AMV protocol contains a summary of AMD results for the new method, and, for changed methods, historical data (AMV and release data) generated using the current method. It also provides current or expected in-process and product specifications, which determine whether the new method is suitable for comparing product quality attributes to specifications.

Validating Analytical Methods for Biopharmaceuticals, Part 2: Formal Validation Table 1. Summary of Minimum AMD/AMV Requirements for a New Method Based on ICH Q2B Close Window Table 1. Summary of Minimum AMD/AMV Requirements for a New Method Based on ICH Q2B

Portions of the AMD data that are summarized in the AMV protocol may not need to be repeated during validation as long as the AMD data were generated under GMP conditions. Therefore, AMV should not be used to modify or change critical assay elements (for example, statistical data reduction). We must be careful not to invalidate the AMD data that were used to establish robustness and system suitability criteria and which were likely used to derive some of the acceptance criteria for the AMV protocol.^8,9

Validating Analytical Methods for Biopharmaceuticals, Part 2: Formal Validation Table 2. AMV Execution Matrix Close Window Table 2. AMV Execution Matrix

All ICH validation characteristics should be evaluated during AMV. Table 1 lists all ICH characteristics that may apply to a particular test procedure, including the corresponding minimum requirements, reported results, and acceptance criteria (see also the first table in Reference 5). Some AMD and AMV elements were added to the ICH characteristics. In practice, more data may need to be generated. For example, three spike levels may not be sufficient to evaluate accuracy and repeatability precision over the valid assay range. Multiple critical elements of the AMV protocol are discussed in more detail below.

INTERMEDIATE PRECISION It is only necessary to evaluate one product batch to determine intermediate precision within the AMV protocol. We are not evaluating production process variability, so controllable factors should be held constant to obtain meaningful results for variable factors (for example, different operators). AMD is the proper time to evaluate several product batches to provide an overall estimate of batch-to-batch precision.

Validating Analytical Methods for Biopharmaceuticals, Part 2: Formal Validation Figure 1. Sources of AMV Acceptance Criteria Close Window Figure 1. Sources of AMV Acceptance Criteria

The overall intermediate precision validation result (expressed in % Coefficient of Variation, CV) can be provided to the production process control unit for production process monitoring. This estimate reflects the expected variability contributed by the test system at any given day. Often, the intermediate precision of the analytical method is the most critical component of the overall observed production process variability .

Cleaning Validation for Biopharmaceutical Manufacturing at Genentech, Inc. Part 1

ABSTRACT
Biopharmaceutical manufacturing and cleaning equipment must be designed for effective and consistent cleaning to avoid cross-contamination and the cleaning processes must be verified as effective. A cleanability study is essential before introducing a new product into the manufacturing equipment. Part 1 of this article provides background on cleaning validation and the associated regulations, cleaning methods, and the validation strategy. It also describes Genentech's approach for new product introduction using laboratory-scale and representative-scale studies. Part 2 will cover the other aspects of the cleaning validation program such as grouping strategy, validation sampling, acceptance criteria, change control, and revalidation.

Cleaning validation refers to establishing documented evidence providing a high degree of assurance that a specific cleaning process will produce consistent and reproducible cleaning results that meet a predetermined level. A cleaning program can be divided into three phases: cleaning process and cycle development, cleaning validation, and maintenance. The program should begin with equipment design evaluation and cycle and process development that includes, but is not limited to, the following: sanitary equipment design, selection of final rinse water, approved equipment specifications that address an evaluation of the compatibility of construction materials with product and cleaning solutions, sprayball design optimization, cleaning process design studies, cleaning sample assay validation, suitability of sampling, and recovery studies for assay and sampling methods. Without these design and development activities, validation could potentially lead to unnecessary troubleshooting and cleaning verification exercises.

The cleaning process should remove materials such as media, buffers, storage solutions, cell culture fluids, cell debris, non-active pharmaceutical ingredients containing placebos, and formulations and concentrations of drugs or active pharmaceutical ingredients (API). Selection of appropriate sampling to demonstrate that residues have been removed to an acceptable level is vital for the success of cleaning validation.

At Genentech, Inc., design and cleaning-cycle development is considered a prerequisite for cleaning validation. The purpose of cleaning validation at Genentech for biopharmaceuticals is to:

• Assess a new product or new equipment for cleanability before cGMP production.
• Ensure that cleaning procedures are adequate for cleaning new products or new equipment.
• Ensure that residues after cleaning of equipment are reduced to an acceptable level before the manufacture of the next run or the next product in the same equipment.
• Provide ongoing assurance that the validated cleaning procedures are in a state of control through monitoring and periodic revalidation.
• Evaluate and validate changes to cleaning processes, other manufacturing processes, and equipment to maintain these validated cleaning processes in a state of control.

REGULATORY EXPECTATIONS

Cleaning validation is driven by regulatory expectations to ensure that residues from one product will not carry over and cross-contaminate the next product. An effective cleaning program starts with appropriately designed equipment and cleaning processes, followed by validation and maintenance. The following are some good manufacturing practice (GMP) cleaning validation requirements for the biopharmaceutical industry.

US Food and Drug Administration 21 CFR Part 211: Current GMP for Finished Pharmaceuticals

§ 211.63 Equipment design, size, and location:
Equipment used in the manufacture, processing, packing, or holding of a drug product shall be of appropriate design, adequate size, and suitably located to facilitate operations for its intended use and for its cleaning and maintenance.¹

§ 211.67 Equipment cleaning and maintenance:
(a) 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 beyond the official or other established requirements. (b)(3)(5) Protection of clean equipment from contamination before use.¹

§ 211.182 Equipment cleaning and use log:
A written record of major equipment cleaning, maintenance, . . . and use shall be included in individual equipment logs that show the date, time, product, and lot number of each batch processed.¹

Basic European Union GMP Requirements for Medicinal Products
EudraLex, volume 4, Medicinal Products for Human and Veterinary Use: Good Manufacturing Practice, chapter 3, Premises and Equipment:
Principle: Premises and equipment must be located, designed, constructed, adapted, and maintained to suit the operations to be carried out. Their layout and design must aim to minimize the risk of errors and permit effective cleaning and maintenance to avoid cross-contamination, build up of dust or dirt and, in general, any adverse effect on the quality of products.²

EudraLex, volume 4, Medicinal Products for Human and Veterinary Use: Good Manufacturing Practice, annex 15, Qualification and Validation:
Cleaning Validation: Cleaning validation should be performed in order to confirm the effectiveness of a cleaning procedure. The rationale for selecting limits of carry over of product residues, cleaning agents, and microbial contamination should be logically based on the materials involved. The limits should be achievable and verifiable.²

International Conference on Harmonization Q7, Good Manufacturing Practice Guide for Active Pharmaceutical Ingredients
The ICH Q7 was developed jointly by the European Union, Japan, and the United States for active pharmaceutical ingredient manufacturing.³ API is the drug substance before final formulation; section 12.7 contains cleaning validation requirements for APIs.

Other Guidance Documents
Additional guidance documents have been established by regulatory agencies and industry associations, such as the FDA, the Pharmaceutical Inspection Convention and Pharmaceutical Inspection Co-operation Scheme (PIC/S), the Canada Health Products, and the World Health Organization .^4–7

BIOPHARMACEUTICAL MANUFACTURING PROCESSES AT GENENTECH

Genentech manufactures biopharmaceutical products from E. coli and Chinese hamster ovary host cells using multiproduct, dedicated, and single-use equipment. Product manufacturing involves cell culture and bacterial fermentation processes, with the associated recovery processes (harvesting, initial and final purification), followed by formulation, aseptic filling or lyophilization, and capping.

Genentech's manufacturing processes include steps for manufacturing and purification of the API, and steps for manufacturing and packaging of the finished drug product. Steps up to and including final purification of the drug substance are considered API manufacturing; the formulation of the drug substance into finished product and the packaging of that product is considered finished drug product manufacture. This is consistent with regulatory expectations for these different categories of manufacturing, with cleaning validation requirements including predetermined acceptance criteria, which may differ for each type of manufacturing. Two separate cleaning validation master plans have been created: one for the API and one for the finished drug product.

CLEANING METHODS

Cleaning is performed to remove materials introduced into equipment during the manufacturing process. These materials may include media, buffers, storage solutions, cell debris, non-API-containing placebos, and any formulation or concentration of a given drug product or API. Manufacturing and cleaning equipment must be designed for effective and consistent cleaning. The cleaning of manufacturing equipment surfaces at Genentech uses automated, semi-automated, and manual cleaning processes. For larger, enclosed equipment, an automatic or semi-automatic clean-in-place (CIP) process is typically used. Cleaning process parameters include cleaning agent concentration, temperature, flow rates, volume, and time.

Equipment cleaning procedures use cleaning agents to aid removal of process soils. The cleaning agents may be categorized as caustic, acidic, neutral, or oxidizing. Some equipment at Genentech is cleaned with water for injection only, using no cleaning chemicals. A typical CIP process includes an initial water pre-rinse, a washing step with one or more cleaning agents, and a final rinse. Before conducting residue removal testing in cleaning validation, installation qualification and operational qualification are performed on the equipment to be cleaned and on the equipment used for the cleaning process. Manufacturing equipment is exposed to cleaning solutions by fully submerging the component (i.e., clean-out-of-place washer or manual cleaning methods); by fully flooding the product-contacting surfaces (i.e., transfer lines or manually cleaned tanks); or by directing fluids by use of spray devices such as spray balls, spray wands, and washer nozzles.

For equipment containing a spray device, qualifications include identifying and documenting the device, noting its proper orientation and alignment, and performing a spray coverage test to assure complete coverage. Spray device coverage verification testing for vessels that are cleaned in place is conducted according to an approved procedure. This procedure involves the use of a visual marker (e.g., riboflavin solution, which fluoresces under ultraviolet light) and spray devices. For glassware that is cleaned in washers, verification of coverage may be conducted with process soils, rather than riboflavin, if process soils are readily visible against translucent glass surfaces.

CLEANING VALIDATION STRATEGY

The cleaning processes for product-contact surfaces for all products manufactured in GMP equipment must be demonstrated to be effective. Product-contact surfaces are surfaces that make direct contact with product or materials introduced into equipment as part of the normal manufacturing process by their very design. Indirect-product-contact surfaces (such as buffer tanks), where there is a significant risk of residues on surfaces contaminating a subsequently manufactured product, also undergo cleaning validation.

To demonstrate the effectiveness of a cleaning process, the process is challenged. This challenge involves at least three consecutive successful cleaning process runs, after which residues are measured and results are compared to predetermined acceptance criteria.

Mock soiling is also used. Mock soiling refers to the soiling of equipment by a process other than routine manufacturing that creates a dirty equipment state equivalent to that following routine manufacturing. Mock soiling of equipment for validation purposes can be performed when equipment is not available for manufacturing soiling. Mock soiling procedures must be adequately described to simulate normal manufacturing processes.

Cleaning validation includes the establishment of dirty hold times and clean hold times. Dirty hold time is the amount of time between the end of the use of the equipment and the start of equipment cleaning. Clean hold time is the amount of time between the completion of the equipment cleaning and the next cycle of use. Cleaning processes are challenged for maximum dirty hold times during cleaning validation runs.

For clinical products, infrequently made products, or infrequently used equipment, a cleaning verification approach may be used in lieu of cleaning validation.

Single-use product-contact equipment (used once and then discarded) is excluded from cleaning validation. Single-use items include beakers, pipettes, weigh boats, silicone tubing, sample tubes, storage bags, and normal-flow filtration filters.

Product-dedicated refers to equipment that is used for a single product and then is removed as part of changeover procedures. Product-dedicated items, such as chromatography resins and tangential-flow filtration membranes, are used with one product only. The requirement for residues in dedicated equipment may differ from that for residues in equipment used for multiple products; nevertheless, the cleaning of product-contact surfaces of dedicated equipment requires cleaning validation. The validation of product-specific resin and membrane cleaning is captured in process validation protocols.

Multi-use equipment may be used to process one or more products or media components. At Genentech, the main emphasis of the equipment cleaning validation program is on multi-use equipment, because this equipment type has the highest risk of process contamination (run-to-run or product-to-product).

NEW PRODUCT INTRODUCTION

Before introducing a new product into equipment used for manufacturing a marketed product, a cleanability study is performed to determine the effectiveness of the cleaning process, using the new product on similar equipment surface types. The new product introduction (NPI) method has two purposes: to avoid cross-contamination of commercial products, and to collect development data on new products.

The cleanability study is divided into two parts: the laboratory-scale study, and the representative-scale runs. The cleanability study starts with an evaluation of the characteristics of the product and soiling at laboratory scale to determine the effectiveness of the rinse, swab, and visual inspection methods. Results of the laboratory-scale study are verified at representative scale. Representative-scale runs include three successful consecutive cleaning runs, conducted on equipment used for marketed products, which include sampling and analysis for residues, and comparison to predetermined acceptance criteria.

Laboratory-Scale Study
As part of sampling suitability testing, process residues of the new product are evaluated for recoverability by rinse and swab sampling methods. In this study (also known as recovering organic carbon by rinse and swab) total organic carbon (TOC) is analyzed to determine the sampling method that is appropriate for cleaning validation testing.

Soils from fermentation, initial purification, and final formulated bulk are used in this study. Testing is performed on each surface type (e.g., stainless steel and glass). Before spiking, soils are adequately mixed before use (by gentle inverting of the sample tube for fermentation soils or by vortexing for recovery soils). Coupons are prepared (cleaned and dried) and are spiked with protein soils at TOC concentrations similar to those in the cleaning validation acceptance criteria limit. The soiled coupons are dried for at least 24 hours, or for the specified dirty hold time, and are sampled using the rinse or the swab method. Positive and negative controls are generated, and swab and rinse water recoveries are calculated.

For highly soluble proteins, the average results of rinse and swab sampling recovery studies for fermentation, initial purification, and final bulk soils usually vary between 80% and 120%. If average recovery results for rinse or swab sampling methods is outside the acceptable range, an investigation is undertaken and a correction factor is applied for less-than-minimum recovery when reporting the equipment validation TOC results. WHO has set the following recovery levels: greater than 80% is good; greater than 50% is reasonable; and less than 50% is questionable.⁷ However, the key to recovery is consistency between samples, not just total recovery.

Representative-Scale Runs
The overall study challenges the ability of the standard cleaning procedure to remove the new product soil from representative equipment surfaces.

The cleaning process is challenged by including the maximum dirty equipment hold time.

The cleaning process may also be challenged by reducing one or more cleaning process variables—such as cleaning time, flow rate, or volume—during each run.

Sampling for residues includes rinse sampling, swab sampling, and visual inspection. An evaluation is performed to determine suitability of swab and rinse methods for validation sampling.

Results
The product residue acceptance criteria in a cleanability study are calculated using the same principles and calculations as for a validation protocol for equipment used to make marketed products. Acceptable results in the cleanability study allow a new product to be introduced and validated in equipment for marketed products; acceptable results also increase confidence in successful validation runs. Cleaning validation of the major multi-use product-contacting equipment is executed concurrent with manufacturing. Acceptable results in triplicate runs of a cleanability study in one facility constitute an acceptable basis for introducing the product into the same combination of equipment configurations and product-contact surface types in any other facility, after equivalence of equipment, cleaning methods, sampling, and acceptance criteria has been established. This equivalency should be documented in the validation protocol or in a technical report. Currently, data from full-scale cleaning validation and new product introduction methods are being generated at Genentech to determine worst-case situations and to justify reduced testing.

CONCLUSION

Cleaning validation is driven by regulatory requirements to ensure that residues from one product will not carry over and cross contaminate the next product. Appropriate design of cleaning equipment and cycle development increases success rate and reduces validation execution time. At Genentech, the cleaning program consists of equipment design and qualification, cleanability study, sampling evaluation, and meeting predetermined validation protocol acceptance criteria. Dirty and clean hold times are established during cleaning validation. Cleaning validation is supported by approved procedures and by training programs for personnel who perform the cleaning operations in the production areas and who collect validation samples. Part 2 will discuss implementation of the cleaning validation program—grouping strategy, various types of sampling and their acceptance criteria, training, change control, and revalidation.

ACKNOWLEDGEMENTS

The author is thankful to corporate quality management at Genentech, Inc., for support, and to Jenna Carlson and Ahmed Bassyouni for reviewing the manuscript and providing comments.

A. Hamid Mollah, PhD, is a senior technical manager for corporate quality and validation at Genentech, Inc., South San Francisco, CA, 650.467.1095, mollah.hamid@gene.com

REFERENCES

1. US Food and Drug Administration. Guidance for industry. Current good manufacturing practice for finished pharmaceuticals. Rockville, MD; 2006 Apr.

2. European Commission, Enterprise Directorate General. EudraLex, vol.4, Medicinal products for human and veterinary use: Good manufacturing practice. Office for Official Publications of the European Communities: Luxembourg; 2007 Mar.

3. International Conference on Harmonization. Q7, Good manufacturing practice guide for active pharmaceutical ingredients. Geneva, Switzerland; 2000 Nov.

4. US Food and Drug Administration. Guide to inspections of validation of cleaning processes. Rockville, MD; 1993 July.

5. Pharmaceutical Inspection Convention and Pharmaceutical Inspection Co-operation Scheme. Validation master plan installation and operational qualification: Non-sterile process validation. Cleaning validation. Geneva, Switzerland; 2004 July.

6. Canada Health Products and Food Branch Inspectorate. Guidance Document. Cleaning validation guidelines: Drug and health products. Health Canada: Ottawa, Canada; 2002 Spring.

7. World Health Organization. Supplementary guidelines on good manufacturing practices: Validation. Geneva, Switzerland; 2005.

Cleaning Validation for Biopharmaceutical Manufacturing at Genentech, Inc. Part 2

ABSTRACT

A cleaning process should remove materials such as media, buffers, storage solutions, cell culture fluids, cell debris, non-active pharmaceutical ingredient, and formulations and concentrations of active pharmaceutical ingredients. Manufacturing and cleaning equipment must be designed for effective and consistent cleaning to avoid cross-contamination and the cleaning processes must be verified as effective. Part 1 of this article provided background on cleaning validation and the associated regulations, cleaning methods, validation strategy, and new product introduction. Part 2 covers Genentech's grouping strategy, validation samples, acceptance criteria, clean hold time, training, change control, and revalidation.

Cleaning validation refers to establishing documented evidence providing a high degree of assurance that a specific specific cleaning process will produce consistent and reproducible cleaning results that meet a predetermined level. A cleaning program can be divided into three phases: cleaning process and cycle development, cleaning validation, and maintenance. The program begins with equipment design evaluation such as sanitary equipment, sprayball, rinse water, and compatibility of construction materials with product and cleaning solutions, followed by cleaning process development and cleanability studies. Cleaning validation must be performed using a pre-approved protocol. Selection of appropriate sampling to demonstrate that residues are removed to an acceptable level is vital for the success of cleaning validation. In addition, use of sampling techniques such as recovery study for swab and rinse and thorough visual inspection can reduce the number of samples required for cleaning validation. Ongoing monitoring, change control, and revalidation constitute the maintenance program. This article covers Genentech's grouping strategy, validation samples, acceptance criteria, clean hold time, training, change control, and revalidation.

GROUPING OF EQUIPMENT

To simplify cleaning validation, similar equipment may be grouped into equipment families. These families are based on equipment design, construction material, geometry, complexity, functionality, or cleaning procedure. Such families involve only the equipment for manufacturing similar products that are cleaned by the same or similar cleaning processes. Grouping may apply to equipment that is cleaned by an automated clean-in-place (CIP) process, a semi-automated CIP process, a manual cleaning process, or an automated parts washer. Grouping into equipment families must be justified and documented.

Grouping may involve separately validating the extremes of a group (for example, the largest and smallest portable tanks in a group), or it may involve testing only the worst case in a group (for example, the most difficult to clean transfer line). The following are some examples of equipment families: bracketed equipment, identical equipment, small equipment or parts cleaned manually, and small equipment or parts cleaned in an automated parts washer. Bracketed equipment such as portable stainless steel tanks, fermentors, glass vessels, transfer lines, filler parts, and glass carboys may vary in scale. Identical equipment such as lyophilizers, 400-liter fermentors, transfer pumps, and 120-liter freeze-thaw tanks, are of the same scale.

Equipment that is validated individually and not as a family, because of significant differences in design and cleaning processes, is called unique equipment or unique systems. Examples of unique equipment include large-scale harvest cell culture systems, centrifuge systems, and chromatography systems.

GROUPING OF PRODUCTS

Cleaning following the manufacture of products may be validated for individual products or may be validated by product group. Grouping by products includes considerations of potency, toxicity, and cleaning difficulty. Products in groups must be manufactured using the same equipment categories and cleaned by the same or similar cleaning processes. Chemical and physical properties of ingredients (including excipients) must be considered when grouping by products; excipients may be more difficult to clean.

Cleaning following the manufacture of buffers, media, and similar indirect product-contacting surfaces may be validated individually or by product group. Acceptable validation of extreme or worst case constitutes acceptable validation for all group members. Grouping must be justified and documented.

VALIDATION SAMPLING

Sampling depends on the characteristics of soiling and cleaning agents. At Genentech, swabbing and visual inspection are used to inspect product-contact surfaces directly for assessment of surface cleanliness. Visual inspection and surface Fourier transform infrared spectroscopy (FTIR) are sometimes called "real" direct surface sampling. Rinsate sample testing for pH, conductivity, total organic carbon (TOC), bioburden, and endotoxin are indirect testing methods. Both direct and indirect sampling methods should be used to measure residues in cleaning validation. Establishing limits for final rinse water based solely on compendial water specification (such as final rinse meeting conductivity specification for water for injection) is not acceptable; however, a risk-based method can be applied to determine appropriate sampling type.¹ Both rinse and swab samplings are considered acceptable methods of sampling in cleaning validation guidance documents.^2,3

In the early 1990s, there was an inclination toward swab sampling for cleaning validation. This was possibly because at that time, equipment was designed to be disassembled for effective cleaning, and this made swab sampling very convenient. More recently, as more large equipment has been designed for CIP cleaning and therefore designed not to be disassembled, it makes less sense to require tank entry to perform swabbing. Opening up the system for entry—as opposed to depending on rinse sampling alone for cleaning validation purposes—leads to concerns about operator safety, as well as concerns about equipment cleanliness and resulting product quality. The use of a remote camera to inspect the interior of a large tank (e.g., a 20,000-liter bioreactor) is being introduced at Genentech.

In biotech manufacturing, protein actives are degraded during the cleaning process using hot aqueous alkaline cleaning solutions. This means that the specific analytical method for measuring the native protein may not be an appropriate method for measuring residues following cleaning. Thus, TOC is a good measure of the overall cleanliness of equipment following a cleaning process. A TOC assay will detect organic carbon in product residues including degraded protein, cell culture or fermentation media, buffers with organic carbon, and other organic materials, including organic components of formulated cleaning agents. Rinse sampling is less technique-dependent, but swab sampling is like manual cleaning in that it is highly operator-dependent. Collecting a swab sample requires that the equipment surface be exposed to the environment, often by equipment disassembly, and be exposed to the sample-collection technician. These situations can cause false positive TOC results that require further investigation. Equipment surfaces that can be examined must be visually clean after cleaning procedures are performed. Visually clean means that the surfaces have no visible residues when viewed under appropriate lighting. A visual residue limit provides a nonselective cleaning assessment and visual detection limits should be established for residues.

Removal of the cleaning agent is demonstrated through selection of a freely rinsable cleaning agent, establishment of a correlation between analytical method and concentration, and sensitivity of the analytical method. Indicator species are measured to detect residual cleaning agent levels. For example, residual CIP200 is indicated by phosphorus or rinsate conductivity. If water alone is used for the cleaning process, no acceptance limit is established for a cleaning agent. If the cleaning agent is solely a chemical species that is subsequently used in manufacturing as a process chemical (e.g., sodium hydroxide for pH adjustment), then complete removal of the species as part of a cleaning validation may not be applicable.

Sampling techniques must be appropriate for the equipment surfaces and for the nature of the study, and they may include swab sampling, rinse sampling, or both. Swab sampling sites are readily accessible and include any worst-case locations, as well as locations representative of different functional parts and different construction materials. Rinse samples are collected in a manner representative of potential residues that may be on the product-contact surfaces of equipment. A laboratory sampling recovery for protein residues must be performed for each combination of chemical residue, sampling method, and sampled surface material of construction specified in a validation protocol. Recovery studies are not appropriate for bioburden and endotoxin measurements in cleaning validation. Validated analytical methods are used at Genentech to measure each residue for which an acceptance limit is established. Compendial methods do not require validation.

When it is established during a cleanability study that rinsate TOC and visual inspection can effectively detect residual carbonaceous materials and that rinse recovery is greater or equal to swab recovery, swab sampling is not required in cleaning validation studies. Justifications for not performing swab sampling such as swab results from cleanability and visual inspections of hard-to-clean (worst-case) locations, are documented. Note that swab sampling can nevertheless be used in cases where incomplete cleaning solution coverage is suspected and for investigation purpose when visual inspection fails. Genentech biopharmaceutical products are water-soluble proteins in aqueous-based solutions, and rinse water sampling has been shown to be an effective method for collecting cleanliness data. It has been found at Genentech that swab sampling routinely exhibits lower recovery levels than rinse sampling (the typical rinse recovery is greater than or equal to 80%).

ACCEPTANCE CRITERIA

Residue acceptance criteria are established for the active pharmaceutical ingredient (API), the cleaning agent, the bioburden, and the endotoxin after cleaning. These acceptance criteria are based on process capabilities or industry practices. Because of the purification that occurs during the processing steps of the API, upstream process acceptance criteria may be less stringent than for downstream processes. In accordance with the ICH Q7 principle for API manufacturing, if residues from cleaning for earlier manufacturing steps are removed by subsequent purification steps, then those earlier cleaning processes may not require cleaning validation. At Genentech, process characterization and validation demonstrate removal of process- and product-related residues in the purification steps. However, for process efficiency reasons, validation is required for fermentation and purification equipment.

Maximum allowable carryover (MAC) must be evaluated, and the rationale for choosing that MAC should be justified and documented. MAC calculation is typically performed on worst-case equipment in formulation and filling areas. For a finished drug product, the acceptance limit for an API residue on cleaned equipment surfaces should be no more than 0.001 of the normal therapeutic dose of an API that appears in a maximum dose of a subsequently manufactured product. Normal therapeutic dose means the recommended minimum daily dose of the active drug substance for an average-size patient. Measured TOC in analytical samples is treated as if it were all from the API, which represents a worst-case condition. If the protein is to be measured by TOC, the limit for the protein may be converted to TOC by multiplying the limit for the protein by the fraction of carbon in the protein. If the API has unusual health effects such as being cytotoxic, or being a reproductive hazard, the safety concerns should be evaluated in setting residue limits for the protocol. This evaluation may result in the need for limits at the boundary of detection of the protein, or in the need to manufacture the product using dedicated equipment.

The final rinse step is aimed at complete removal of cleaning agents. For a cleaning agent containing toxic chemicals, the acceptance limit for the cleaning agent on cleaned equipment surfaces is determined using calculations in Parenteral Drug Association Technical Report 29.⁴ Control of the bioburden through adequate cleaning and storage of equipment is important to ensure that subsequent sterilization or sanitization procedures achieve the necessary assurance of sterility. There should be documented evidence that routine cleaning and storage of equipment do not allow microbial proliferation. Hence, bioburden is monitored during cleaning validation and clean hold time studies. Bioburden acceptance criteria are based on the equipment process step, final rinse water quality, and the capability of the cleaning and sampling processes. Depending on the system and sampling technique, it may not be feasible to achieve final rinse water bioburden quality in a grab sample. The endotoxin acceptance limit for any rinse sample in final purification equipment and fill or finish equipment is derived from rinse water quality.

Water-Fill Carryover Studies

Validation sampling and testing methods are used for determining equipment cleanliness, but they may not measure the actual carryover of cleaning process residues from one use of the equipment train to the next use. Because of very low concentrations of active ingredients in biopharmaceuticals, a MAC calculation using the surface areas of the entire equipment train may not be feasible. Water-fill carryover studies can be conducted at the end of cleaning or in conjunction with postcleaning hold time validation studies, and can express their results in terms of worst-case carryover into a minimum volume subsequent batches. Water is used to mimic the next batch (i.e., filling product vials using fill or finish equipment), as all biochemical processes use water-soluble solutions. These studies are very useful in documenting actual process carryover, and they are typically performed in fill or finish areas at Genentech.

CLEANED EQUIPMENT STORAGE AND HOLD TIMES

The duration between the end of equipment cleaning and the start of subsequent operations (e.g., autoclave, sterilization-in-place [SIP], or production usage) is called clean hold time. Following cleaning, equipment to be reused should be stored to protect it from contamination. Storage instructions are specified in a document such as that delineating the cleaning procedure or the storage procedure.

Equipment should be stored dry following cleaning. There should be no visible water pool in the equipment or line after draining (including air blowing) when viewed under appropriate lighting conditions. An exception to the dry storage recommendation occurs when equipment is stored in solution. If equipment undergoes autoclave (or SIP) or production usage after CIP within a manufacturing shift (or for approximately eight hours), then a clean hold time need not be established, provided the circumstances are justified and documented. Clean hold time validation is not required for indirect product-contacting equipment that undergoes autoclave or SIP, when operational controls are in place to minimize bioburden, and when a documented risk assessment demonstrates no risk to product quality from potential accumulation of bioburden and endotoxin as a result of prolonged storage.

A validation study is used to establish an expiry period. The study includes measuring bioburden and endotoxin levels in the equipment after a predetermined storage time. One protocol study, comprising three individual runs, for validation of an expiry period for a given equipment family may apply to all pieces of equipment in the family, to all products using that equipment, and to all cleaning processes for that equipment, provided the final state of the cleaned equipment and the storage conditions are consistent. The bioburden criteria for clean hold times takes into account the relevant microbial control procedures that may occur subsequent to cleaning and storage condition. Therefore, clean hold time bioburden criteria may exceed the end-of-cleaning (time-zero) bioburden criteria. The justification for the bioburden acceptance criteria should be documented. If the validated clean hold time elapses, the equipment must be cleaned again before use.

CHANGE CONTROL AND REVALIDATION

Changes to a validated cleaning process, and changes to a manufacturing process or equipment that may affect a validated cleaning process, must be made in accordance with approved change control procedures. Such a change may result in additional testing to demonstrate that cleaning processes remain in a state of control. Revalidation of cleaning processes is performed following any significant change to a cleaning process that may affect its validated state. A change evaluation process determines the extent of validation required.

Periodic review and revalidation are methods by which the performance of a validated cleaning process is evaluated to ensure that a state of control is maintained. At Genentech, a risk-based approach is used for setting periodic review and revalidation frequencies. The rationale for the revalidation frequencies should be appropriately documented and justified. The revalidation frequency for product-contact surfaces (e.g., bioreactor and pool tanks) and manual cleaning should be higher than for indirect product-contact surfaces (e.g., media and buffer tanks).

A periodic review is performed on each combination of cleaning process and equipment (or equipment family) according to an established frequency. Such a review includes an assessment of cleaning-process documentation, including changes implemented under the change control program since prior revalidation to determine if processes are still in a state of control. The periodic review should be documented.

In addition to a periodic document review, one successful cleaning validation run is conducted for each unique equipment or system on an established frequency, provided that the equipment has been used to manufacture a product that year. Such a validation run may include any product manufactured using the unique system. For each equipment family cleaned by the same or similar cleaning procedures, one successful cleaning validation run is also conducted on an established frequency using one equipment item from the applicable equipment family. This validation run may include any product manufactured using the equipment family. Each major equipment item in each family is included in cleaning validation runs in a predetermined period. Major equipment refers to product-contacting equipment that serves a significant purpose in the manufacture of product (i.e., the main equipment used in process unit operation). Examples include fermentors, hold tanks, purification equipment, and lyophilizers.

TRAINING

Training regarding approved processes or protocols used for cleaning validation studies such as cleaning processes and sampling processes, is performed and documented by approved training policies or procedures. Personnel who collect samples for cleaning validation and who perform visual inspections must be trained before these collections and inspections. Operators are routinely retrained for validated manual cleaning procedures, particularly when there has been a change in any validated cleaning procedure.

CONCLUSION

Cleaning validation is driven by regulatory requirements to ensure that residues from one product will not carry over and cross contaminate the next product. The cleaning program consists of equipment design and qualification, a cleanability study, sampling evaluation, and meeting predetermined acceptance criteria. Dirty and clean hold times are established during cleaning validation. Cleaning validation is supported by approved procedures, training, change control, monitoring, and revalidation. A cleaning validation strategy that is based on the evaluation of potential risks increases success rate and reduces execution time.

ACKNOWLEDGMENTS

The author is thankful to Lara Collier for management support and to Jenna Carlson and Ahmed Bassyouni for reviewing the manuscript and providing comments.

A. Hamid Mollah, PhD, is a senior technical manager for corporate quality and validation at Genentech, Inc., South San Francisco, CA, 650.467.1095, mollah.hamid@gene.com

REFERENCES

1. Mollah AH, White EK. A risk based cleaning validation in biopharmaceutical API manufacturing. BioPharm International 2005;18(11):54-67.

2. US Food and Drug Administration. Guide to inspections of validation of cleaning processes. Rockville, MD; 1993 Jul.

3. Pharmaceutical Inspection Convention and Pharmaceutical Inspection Co-operation Scheme. Validation master plan installation and operational qualification: Non-sterile process validation. Cleaning validation. Geneva, Switzerland; 2004 Jul.

9. Parenteral Drug Association Office of Science and Technology. Technical report no. 29: Points to consider for cleaning validation. Bethesda, MD; 1998 Aug.

A Guide for Testing Biopharmaceuticals Part 1: General StrPart 1: General Strategies for Validation Extensionsategies for Validation Extensions

ABSTRACT

Several gaps in current regulatory guidelines that govern the analytical method life cycle for the testing of biopharmaceuticals are identified. Strategic guidance on how to monitor and control the life cycle of an analytical test method is provided in this article. Analytical method transfer, analytical method component equivalency, and analytical method comparability protocols are discussed in light of risk-based strategies for validation extensions. The use of an analytical method maintenance program is suggested to control over time the predictable risk to patients and firm.

The successful completion of analytical method transfer (AMT) is a regulatory expectation for the extension of the validation status to other laboratories. The demonstration of equivalent test results and, therefore, an acceptable level of reproducibility when testing at a different location, can limit the potential risk to the patient (hence the regulatory expectation). Acceptable reproducibility also limits the risk of failing test results for the biopharmaceutical firm as established probabilities of passing specifications can be maintained. Similar, postvalidation changes in method components should be monitored and controlled to avoid significant (negative) changes for material or product release probabilities.

Analytical method validation (AMV) guidelines exist from several recognized sources.^1–6 Detailed validation guidelines for alternative microbiological test methods also exist.^7–8 In addition, a series of practical tips and discussions for AMV and related topics was recently published.^9–15 However, some topics are currently not sufficiently covered in recognized sources. For example, how can we demonstrate method comparability for new methods, extend the validation status onto other laboratories or other test method components, and maintain this validation status over time? What are acceptable levels for differences in method performance and when is a method no longer suitable?

This two-part series focuses on all postvalidation work that may be required to ensure process and product quality over time. This article discusses practical concepts on how to ensure successful validation extensions. Part II, to be published in the October issue, will include practical tools to ensure a validation continuum (maintenance) for validated methods. The second part will also include case studies for deriving meaningful and risk-based acceptance criteria for validation extensions and validation maintenance and will, furthermore, include a case study on how to reduce analytical variability in validated systems.

When replacing approved test methods with improved ones, analytical method comparability (AMC) data should be submitted together with the method description and validation results.¹³ Once a method is approved and in routine use, it should be maintained in an analytical method maintenance (AMM) program that can be administered through the validation master plan (VMP).¹⁴ If done well, this will ensure—like all postvalidation activities—consistent (accurate and precise) production process and product quality measurements.¹⁴ What exactly are the critical elements of good validations, validation extensions, or suitable validation maintenance? The answer lies mostly in the preset acceptance criteria for method performance and, of course, the actual validation results obtained. For example, if changes in analytical method components cause a change in test results and, therefore, in process or product quality measurements, we should capture when we will have exceeded method suitability limits. In other words, if the analytical method change will cause a predictable shift or spread of results with respect to specification(s), and therefore negatively impact the probability of releasing material, we should monitor this. To monitor and possibly compensate, we must first set reasonable suitability limits, then continuously control the overall method performance. Often, the most difficult part may be to estimate the associated risk of changed results with respect to both patient and firm, and from this, to set reasonable acceptance criteria. Once we truly understand why and when there will be a need for method improvement, we will likely know what should be done to compensate for the difference.

Each production process has an associated probability for the rate of rejections that can be readily calculated by relating specifications and production process performance. However, instead of having to deal with only two probabilities (pass or reject) that are "visible" and monitored by statistical process control (SPC), we should consider two additional possibilities for all reported results. Therefore, there is a total of four possible cases for releasing product or material, of which three should be avoided as often as practically possible. The four cases for reported test results are illustrated here.

Measured results are within established specifications.

• Case 1A: results are true.
• Case 1B: results are not true.

Measured results are outside established specifications (OOS).

• Case 2A: results are true.
• Case 2B: results are not true.

Cases 1A and 2A are routinely monitored by SPC. Cases 1B and 2B originate from other uncertainties such as imperfect test method performance or poor sampling and are not readily visible by SPC. Cases 2A and 2B are obviously not desirable because the firm cannot process nor sell this product or material. Case 1B constitutes a risk primarily to patients, but also means a risk to the firm if adverse product-related reactions or over- or under-dosing would actually occur. Case 2B constitutes a loss solely to the firm and should also be avoided mainly for profit reasons although other problems may also arise from this situation.

For our validation extension acceptance criteria, we should primarily set acceptable protocol limits from SPC with relation to specifications. We should consider the likelihood and impact for cases 1B and 2B, and avoid as much as possible measurement errors as part of the AMM program. Inaccurate or imprecise measurements will always cause a lower than ideal probability of observing results within specifications. The acceptance criteria for AMV and its continuum requirements must, therefore, ensure the low likelihood for all cases but 1A.

To meaningfully estimate risk to patients and the firm, we must understand our process data and integrate test measurement aspects into our risk-based validation strategies. Good risk management tools will dictate how much assay performance characteristics can deviate from the ideal. This will then set limits on how much we can tolerate over time for a test method to deviate from ideal (100% accurate and precise). It should also now become apparent why it is so important to maintain our validation status with an AMM program. When this is ignored, we negatively affect all four cases. (Negative here means increased risk to patient or firm). Although undetected, negative effects will occur for the "invisible" cases 1B and 2B because measurement errors are not captured by regular SPC. This may also cause the lack of process understanding and control, and may also lead to conflicts with current regulatory expectations (process analytical technology [PAT]) and may impact a firm's profits in the long run.¹⁵

ANALYTICAL METHOD TRANSFER

A Guide for Testing Biopharmaceuticals Part 1: General Strategies for Validation Extensions Table 1. Analytical method transfer (AMT) execution matrix. Close Window Table 1. Analytical method transfer (AMT) execution matrix.

Validated analytical methods can be transferred from one laboratory to another without the need for revalidation at the receiving laboratory.^9,16 A typical AMT is accomplished by testing at the sending and receiving laboratories in a round-robin format. Testing is performed on three different product lots over three days, using two operators and two instruments in each laboratory.^9,16 Reproducibility of test results, within and between laboratories, is demonstrated in Table 1 by evaluating intermediate precision (different operators, instruments, days and product lots at each site) using an analysis of variance (ANOVA) and by comparing the differences in mean results for each lot between both sites.^9,16 For each AMT, preset acceptance criteria for intermediate precision and for the absolute differences between sites are derived and justified from the validation at the sending laboratory.⁹

The AMT reports should include descriptive statistics (means, standard deviations and coefficients of variance), comparative statistics (ANOVA ρ-values) for inter-laboratory results, and the differences-of-mean values for both (or each) laboratories. Each report documents evidence that the transferred test method is suitable (qualified) for testing at the receiving laboratory.

For cases where the ANOVA ρ-value is less than 0.05, secondary acceptance criteria should be established for the comparison-of-means and variability of the results to demonstrate the overall lab-to-lab reproducibility of test results. It is advisable to include a numerical fall-back limit (or percentage) because the likelihood of observing statistical differences may increase with the precision of the test method. In addition, some differences (bias) between instruments, operator performances and days are expected.⁹ We should tailor our acceptance criteria for overall (intermediate) precision and for the maximum tolerated difference between mean laboratory results (accuracy or matching) to minimize the likelihood of obtaining OOS results (2A and 2B) or 1B results.⁹ The setting and justification of all acceptance criteria must strike a balance and is a critical part of each protocol. A detailed AMT case study was presented elsewhere.⁹

ANALYTICAL METHOD COMPARABILITY

A Guide for Testing Biopharmaceuticals Part 1: General Strategies for Validation Extensions Table 2. General guidance for using appropriate statistics to assess method comparability from validation characteristics per ICH Q2A/B. Close Window Table 2. General guidance for using appropriate statistics to assess method comparability from validation characteristics per ICH Q2A/B.

As we need to demonstrate equality or improvement whenever approved methods are replaced, which and how are method performance characteristics compared? Table 2 provides guidance on which validation characteristics to use for comparability protocols for each assay type per ICH Q2A/B. All qualitative tests should contain a comparison of hit-to-miss ratios (for "specificity") between the approved method and the new method. If a qualitative limit test is exchanged, the detection limit (DL) of the new method should be compared and should be equal or lower for the new method. For all quantitative methods, the method performance characteristics accuracy and precision (intermediate precision) should be compared.¹³It is of great regulatory concern whether results may change overall by drifting (change in "accuracy" or "matching") or by an increase in data spreading ("intermediate precision"). An increase in data spreading or lack of precision will mostly increase the likelihood of observing cases 1B or 2B and should be avoided. A drift in results or "lack of matching" may require a change in the specifications. This drift in release results can occur in two directions, lower or higher results. Both directions are not acceptable outcomes for the demonstration of accuracy, and testing for equivalence between methods is therefore correct.¹³ The goal of comparisons of other characteristics (e.g., DL) is different such that two outcomes (equal or better) are acceptable. For example, for the comparison of DLs, the two outcomes of having either an equal or lower DL would both be acceptable.¹³ A third comparison category is the demonstration of noninferiority and is usually the easiest to pass for comparability. However, we should keep in mind that the use of any of the comparability categories (noninferiority, equivalence, superiority) using ICH E9 and Committee for Proprietary Medicinal Products (CPMP) guidance documents should be properly chosen and justified.^13,17–19 In other words, noninferiority testing may be justified for the comparison of some primary characteristic such as DL if other secondary criteria (e.g., increased number of tests or test samples) can compensate for the small level of inferiority of the primary comparison characteristic.¹³

Quantitative limits (QLs) could also be compared. However, both QLs would have to be estimated by the same principle (e.g., estimated by regression analysis). A low QL is desirable as it will let us quantitatively report and monitor low-value results by SPC. There are several ways to compare QLs. For example, we could compare the regression coefficients of both linear assay response curves to estimate both QLs and would also get a general idea how accuracy and precision characteristics compare over the assay range. Table 2 constitutes a general guidance. Particular examples for noninferiority, equivalence, and superiority testing to demonstrate method comparability were provided and discussed elsewhere.¹³

No matter which comparability category we may use for a statistical comparison (with ρ = 0.05), a protocol should provide the design of experiments to be done and the pre-specified value for the allowable difference in results. The prespecified maximum allowable difference is illustrated in CPMP's Points to Consider On The Choice Of Non-Inferiority Margin.¹⁹ The allowable difference should be set similar to AMV or AMT. The difference should be set and justified by relating specifications to SPC data and considering the likelihood of observing any of the four cases (1A, 1B, 2A, and 2B).¹³

Stephan O. Krause, PhD, is the manager of QC Technical Services and Compendial Liaison at Bayer HealthCare , LLC, Berkeley, CA 94701, tel. 510.705.4191, stephan.krause.b@bayer.com

REFERENCES

1. Guideline for Industry Text on Validation of Analytical Procedures, ICH Q2A, 60, 1995. http://www.fda.gov/cder/guidance/ichq2a.pdf

2. Guidance for Industry Q2B Validation of Analytical Procedures: Methodology, ICH Q2B, 62, 1996. http://www.fda.gov/cder/guidance/1320fnl.pdf

3. The Fitness for Purpose of Analytical Method, Eurachem, Teddington, UK (1998). http://www.eurachem.ul.pt/guides/valid.pdf

4. Traceability in Chemical Measurement, Eurachem/CITAC, Teddington, UK (2003). http://www.eurachem.ul.pt/guides/EC_Trace_2003.pdf

5. Guidance for Industry, Bioanalytical Method Validation (2001). http://www.fda.gov/CDER/GUIDANCE/4252fnl.htm

6. Draft Guidance for Industry, Analytical Procedures and Methods Validation (2000). http://www.fda.gov/cder/guidance/2396dft.htm

7. Technical Report 33, Evaluation, Validation and Implementation of New Microbiological Testing Methods (PDA, Bethesda, MD, USA).

8. Alternative Methods For Control of Microbiological Quality, EP. Supplement 5.5 [07/2006:50106] (December 2005). http://www.pheur.org/

9. S.O. Krause, BioPharm Int. 17(3), 28–36 (2004).

10. S.O. Krause, BioPharm Int. 17(10), 52–61 (2004).

11. S.O. Krause, BioPharm Int. 17(11), 46–52 (2004).

12. S.O. Krause, BioPharm International Validation Guide, a supplement to BioPharm Int. 18(3) (2005).

13. S.O. Krause, BioPharm International Guide to Bioanalytical Advances, a supplement to BioPharm Int. 18(9) (2005).

14. S.O. Krause, BioPharm Int. 18(10), 52–59 (2005).

15. Guidance for Industry PAT — A Framework for Innovative Pharmaceutical Development, Manufacturing, and Quality Assurance (2004). http://www.fda.gov/cder/guidance/6419fnl.pdf

16. ISPE Good Practice Guide: Technology Transfer (International Society for Pharmaceutical Engineering, Tampa, FL, 2003).

17. Statistical Principles for Clinical Trials, ICH E9 (1998). http://www.emea.eu.int/pdfs/human/ich/036396en.pdf

18. Points to Consider on Switching Between Superiority and Non-Inferiority, CPMP (2000). http://www.emea.eu.int/pdfs/human/ewp/048299en.pdf

19. Points to Consider On The Choice Of Non-Inferiority Margin, CPMP (2004). home.att.ne.jp/red/akihiro/emea/215899en_ptc.pdf