Validating Analytical Methods for Biopharmaceuticals, Part 2: Formal Validation - The development and optimization process can improve a method but validation cannot. Validation is a final-step proof


Validating Analytical Methods for Biopharmaceuticals, Part 2: Formal Validation
The development and optimization process can improve a method but validation cannot. Validation is a final-step proof that regulations are met.

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.

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

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.

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 (see also the AMV Acceptance Criteria section of this article).

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