Analytical Method Transfer Conditions Used by Global Biologics Manufacturers

Published on: 
BioPharm International, BioPharm International-10-01-2015, Volume 28, Issue 10
Pages: 22–30

The authors present the results of a survey of biologics manufacturers to evaluate how these manufacturers transfer analytical methods.

Although guidance can be found in available best practice documents (1–3), limited information exists about how exactly larger biological manufacturers are transferring analytical methods. The author conducted this brief survey of how manufacturers transfer analytical methods as it was expected that a significant variation exists. Specifically, the preferred pre- and post-licensure analytical method transfer (AMT) options for the execution model, sample size, and acceptance criteria were surveyed. A total of eight large pharma/biotech manufacturers, representing the three major regulatory regions of the United States, the European Union (EU), and Asia, provided answers. All eight manufacturers have global operations, multiple commercial biological products, and more than 3000 employees. This survey was intended to evaluate how these manufacturers handle internal versus external AMTs as well as pre- and post-licensure AMTs. 

The manufacturers’ representatives were contacted directly by the author via a detailed email survey request and instructions. At total of 15 manufacturers were contacted and eight responded with complete answers. Subject matter experts, responsible for AMTs, typically answered the survey questions. Only one email response was received from each of the eight participants.

Description of AMTs
AMTs may occur at any point in a method and product lifecycle. An AMT transfer may be associated with transfer of the entire manufacturing process during product development, may occur after product licensure, and/or may be a portion of a larger technology transfer process. Or, an AMT may be required to implement the use of a new laboratory for quality-control release and/or stability testing, either within or outside the company (e.g., contract laboratory). Using Parenteral Drug Association (PDA) Technical Report (TR) 57 as the reference point for AMT models, execution matrices, sample size calculations, and acceptance criteria, the following options and conditions were provided so that each manufacturer’s information could be part of the evaluation (1). Most of the surveyed manufacturers follow TR 57 for AMT execution matrices and sample-size calculations. The strategy used for AMTs can vary, and several possible options, per PDA TR 57, are described as follows:

A. Co-validation-Sending and receiving laboratories participate in the analytical method validation study execution. This may be used early in the lifecycle of a test method when appropriate.

B. Comparative study-AMT study performed concurrently by sending and receiving laboratories. Acceptance criteria determine the equivalence of the two laboratories. Historical and validation data may be used when appropriate for parts of the method transfer study. The sending laboratory typically has collected a significant amount of historical data for test method performance results in addition to test results for the samples to be tested at the receiving laboratory. Acceptance criteria are typically set based on relevant product or material specifications with consideration of the previous validation/qualification studies and/or recent routine quality control (QC) testing data. See the following B-1 and B-2 options:

  • B-1. Fixed AMT execution matrix-The fixed AMT execution matrix does not integrate known test method result variation and has therefore an identical set of comparative data generated between both laboratories for each method transfer executed. A fixed execution matrix can be more advantageous when transferring multiple products to/from multiple locations.

  • B-2. Variable execution matrix-The variable execution matrix does consider test method result variation and may require a larger data comparison set for highly variable test methods. A variable execution matrix may be advantageous when transferring bioassays with a relatively high degree of test-result variation.

C. Performance verification-The receiving laboratory may already perform the method for a similar product or for another type of sample for the same product. In this case, a formal method transfer may not be required. Any reduced prospective study considered should be properly justified.

D. Waiver-The receiving laboratory may already perform the method for a similar product or for another type of sample for the same product. In this case, a transfer may be waived. Any waived study should be properly justified using available data.

Besides AMT options A-D, PDA TR 57 provides recommendations to use an intermediate precision-type AMT execution matrix and detailed instructions for risk-based acceptance criteria. In addition, for the option of using a variable execution matrix, sample-size calculations and a detailed AMT example are given. Although the AMT process is conceptually similar for pre- and post-validation transfers as well as for internal vs. external transfers, PDA TR 57, as well as other available guidance by the International Society for Pharmaceutical Engineering (ISPE) and the US Pharmacopeial Convention (USP), is more focused on post-validation AMT.



Survey Questions
Because limited specific guidance exists for pre-validation AMTs, and they may not be visible to the chemistry, manufacturing, and controls (CMC) assessors, the survey questions were posed to manufacturers to understand the variation among manufacturers frequently transferring analytical methods. A total of five possible AMT cases that include pre- and post-validation transfer stages and possible sending units (SU) and receiving units (RU) were evaluated for the preferred AMT model use. To ensure that the data can be fully evaluated and compared, the questions were also provided in tabular format. Survey results for the four questions are summarized in Tables I–V.

The questions were as follows:


1. Which different model, sample size(s), and/or acceptance criteria do you use for:

  • a. Clinical vs. commercial AMT studies?

  • b. Internal vs. external (to/from contract manufacturing organization [CMO]) AMT studies?

  • c. To/from CMO vs. in-country batch release lab AMT studies? (In-country batch release lab = non-US regulatory-approved labs to release commercial product into their respective countries/regions)

2. What are the total number of samples/replicates tested by both labs, SU and RU? Are you using a fixed AMT execution matrix (e.g., n=6, n=12, n=18, n=24, or n=36 at each site, SU and RU) or a variable execution matrix (calculated sample size which considers test method variation?

3. Was an intermediate precision-type comparison used (at least two critical variation factors selected)?

4. What is the acceptance criterion for RU used: fixed or risk based (e.g., fixed: ≤ 1.0 SD difference between SU and RU; risk based: calculated primarily by considering specification and process capability and maximum acceptable result drift from SU to RU and result variation at RU)?

Results for preferred use of AMT model(s) were somewhat surprising in that two of the eight manufacturers make use of all or most of the available models regardless of the stage of product development. Six of the eight limit the model options to only two, with two of the six using only model B for any of the five possible AMT cases. All manufacturers use model B, and this option is by far the most often used model. As the author expected that option B would be the most frequently used option, the question of whether the fixed (B-1) or variable (B-2) comparison models were used was therefore further evaluated, and the results are shown in Table II.

Six of the eight manufacturers stated that they use fixed execution matrices for pre-validation AMTs, which offer the advantage that the SU and RU always know how much testing is to be planned and executed regardless of product-type and/or product experience. A lot of the master plan’s and AMT protocol’s content can thus be readily copied to reduce the master plan and protocol generation time. For post-validation AMTs, this ratio changes in favor of using a variable execution matrix for three manufacturers. This change to a more rigorous AMT planning and execution process can be justified, as the investment of more rigorous AMT process steps is commensurable with the product development stage(s). The biological product is more valuable at the commercialization stage(s) as both successful clinical and product/process validation studies were completed. Overall, the results show significant variation among the eight survey participants with all four cases (only B-1; only B-2; only B-1 and B-2; and B-1 changing to B-2 for post-validation AMTs) represented.

An appropriate sample size can be determined using the risk-based approach outlined in PDA TR 57. Based on the sample size n, the study plan should ideally be designed so that at least two independent factors (e.g., analysts and/or days) known to (potentially) impact test method results are investigated during the transfer. Statistical equivalence testing is usually performed to confirm that the transfer study results are acceptable and fall within preset limits.

Results for sample size varied significantly in that the typical AMT sample sizes can range from a minimum of n=3 to as much as n=24. Two of the manufacturers surveyed use n=24 for all post-validation AMTs regardless of whether methods are transferred internally or externally. Most of the manufacturers surveyed tend to increase the sample size for post-validation AMTs, which again can be explained by the increase in “product value” and the level of confidence in the AMT results for late-stage/commercial products.

In an intermediate precision matrix study, at least two independent factors (e.g., analysts and/or days) are deliberately varied to better estimate routine testing conditions. Intermediate precision at the RU could be evaluated from this data set; however, when a more detailed result interpretation is desired at the RU, a more extensive set-up may produce test result variation that is more representative of the variation that typically occurs with routine testing. Only one manufacturer surveyed indicated that it might use repeatability-type precision for pre-validation AMTs. All manufacturers surveyed use at least two independent variation factors for post-validation AMTs.

For post-validation AMTs, more than half of the AMT acceptance criteria are risk based and calculated primarily by considering specifications and process capability and the maximum acceptable result drift (from SU to RU) and result variation at RU. The survey suggests further that some manufacturers integrate more risk-based acceptance criteria for post-validation AMTs.

It is the author’s experience that a large data set for the product- and method-specific performance capabilities may not exist prior to method validation. The potentially large level of uncertainty in the required method performance as well as product/process capability in early product development stages can lead to setting fixed acceptance criteria. In late-stage, post-validation stages, ideally, the maximum acceptable differences between laboratories for the method performance characteristics of quantitative methods such as accuracy and intermediate precision are estimated based on product-specific historical data with respect to the specifications.

Other approaches-such as setting the acceptance criteria based on previous validation/qualification studies and/or recent routine QC testing data with respect to the relevant product or material specifications--may also be used. When using fixed acceptance criteria such as a standard deviation-based limit for the maximum allowed difference between SU and RU, recent SU historical, product-specific data are usually not considered. Each approach has its advantage(s). The risk-based approach in PDA TR 57 evaluates risks to both patient and manufacturer.

Figure 1 highlights the two primary sources to be considered to set risk-based acceptance criteria for analytical method performance. To be truly risk-based, from a patient and data-continuity perspective, investigators should use the product specifications and existing knowledge of product and process capabilities (1). Typically, in early-stage product development, the specifications and product/process performance can be estimated from historical data of similar products. In late-/commercial-stage product development, more product-specific historical data exist so that product-specific, risk-based acceptance criteria can be set using product-specific specifications and process/product capabilities.

The AMT acceptance criteria should be set to balance patient and manufacturer’s expectations. First, if a high level of method capability is desired within the given specifications and expected process capability, setting tight acceptance criteria may be appropriate. Fulfilling the second driver-which involves setting protocol acceptance criteria ranges wide enough to ensure successful AMT completion-may be in direct opposition with the expectations of the patient. Acceptance criteria may be set unsuitably wide to assure that all criteria are readily passed. The method performance may therefore be considered validated, compliant, and acceptable, although the actual method performance may not be suitable with respect to specifications and/or overall process capability expectations. It is therefore important to set risk-based and balanced acceptance criteria intended to satisfy both drivers as much as possible (1).

Uncertainty and test-result variation result in risks to patient and firm. This relationship should be understood and used to set acceptance criteria to ensure the continued suitability for use of the analytical method following an AMT. Simplified, the relationship of the primary variation sources are shown in Equation 1. As specifications are for the observed manufacturing process variation, we should therefore control result drifting and variation at RU through risk-based acceptance criteria.

The demonstration of equivalence in average test results (accuracy and/or matching) and similar precision (intermediate precision) performance between the laboratories is of primary interest in the evaluation of quantitative methods. A comparison of additional validation characteristics (such as quantitation or detection limits) may be considered for particular method types. Statistical tests can be used to demonstrate equivalence between laboratories. Equivalence testing by two one-sided t-tests (TOST) is generally applicable in most cases (1). The TOST results are statistically satisfactory and AMT results pass if the confidence interval for the difference in means between the two laboratories falls within an acceptable interval [-Θ, + Θ]. The interval should define the largest difference that could be accepted between the laboratories while not significantly impacting the suitability of the transfered analytical method (1).

In summary, the survey results provide valuable insight into how large biologics manufacturers are transferring analytical methods in different situations. Some significant variation was observed among the eight manufacturers, specifically in the use of AMT models, sample size, and setting of acceptance criteria.

Analytical method transfers are becoming more important as biological products transfers are occurring more frequently and increasingly more globally. More practical global guidance could help to harmonize current method transfer practices. This again would ensure that product approval could occur faster which is in the interest of all stakeholders.

1. Krause et al., PDA Technical Report 57, “Analytical Method Validation and Transfer for Biotechnology Products,” (PDA, 2012).
2. International Society for Pharmaceutical Engineering, Good Practice Guide: Technology Transfer (ISPE, Tampa, FL, 2003).
3. USP, General Chapter <1224> “Analytical Method Transfer,” USP 35 (US Pharmacopeial Convention, Rockville, MD, 2012).

About the Author
Stephan O. Krause, AstraZeneca Biologics, Frederick, MD, USA

Article Details
BioPharm International
Vol. 28, No. 10
Pages: 22–30

Citation: When referring to this article, please cite it as S. Krause, “Analytical Method Transfer Conditions Used by Global Biologics Manufacturers,” BioPharm International 28 (5) 2015.