Producing cGMP biopharmaceutical products requires controlled, consistent performance of the manufacturing process. cGMP also requires controlled, consistent performance of analytical test methods. cGMP validation studies are conducted to confirm the performance capabilities of the process or the analytical methods under expected operational conditions.
The FDA defines validation as “The process of demonstrating, through documented evidence, that a process, procedure, piece of equipment, analytical method, or facility will consistently produce a product or result that meets predetermined specification and quality attributes.”
However, a validation study is a snapshot in time; what really matters is how the process or analytical methods continue to perform after validation, according to Nadine Ritter, PhD, president and analytical advisor, Global Biotech Experts, LLC, will discuss this issue next Tuesday at the BioProcess International Conference in Boston. Her presentation is entitled “Value of Tracking and Trending Method Performance after Validation.”
Evidence of a controlled, consistent manufacturing process may be based on product lots that are within their quality specifications. Lots that fail specification suggest problems with the process. But what provides evidence of controlled, consistent test method performance? How can a lab routinely monitor the accuracy and reliability of validated test methods?
“Although the principles of validation are applicable to processes and test methods, the way that you execute a process validation is substantially different than the way that you carry out a method validation,” she told GEN. “And even among analytical test methods, the experimental designs of validation studies differ across method technologies and specified intended uses (e.g., quality attributes of different products).
“Defined method validation parameters were codified in the late 1990’s by ICH Q2A and Q2B (ICHQ2(R1), and they’ve recently been updated for the first time in 2023 (ICHQ2(R2). Those are the well-known method performance parameters we confirm in a validation study: Specificity, Accuracy, Linearity/Range, LOQ/LOD (where applicable), Precision (Intra-Assay), Precision (Inter-Assay), and Robustness. The purpose is to experimentally prove the methods we have developed and (hopefully!) optimized are in fact capable of reliable routine performance for the measurements that they make.”
Technical challenge
A big technical challenge in validating methods for biopharmaceutical products is how to appropriately interpret the ICHQ2 performance parameters for the diversity of analytical technologies using different product quality attributes, noted Ritter.
“Product quality attributes such as identity, potency, content/concentration, purity, degradants, process impurities, and process contaminants utilize very different methodologies” she said. “But they all require technically correct method validation, or else the validation exercise is useless.
“Validation experiments should be designed to confirm that the entire method procedure—from the preparation of reagents, materials, standards, and test samples all the way to the final reportable result of the test—is capable of suitable performance in the intended laboratory.”
Ritter went on to explain that after validation, several of these parameters can (should) be incorporated into the validated method SOP as system suitability measures. This is Continuous Method Verification (CMV), which is analogous to Continuous Process Verification (CPV). USP General chapter <1220> “Analytical Procedure Life Cycle” refers to post-validation method monitoring as “Ongoing Procedure Performance Verification (OPPV).”
For CMV/OPPV, each time the method is run, she continued, the analyst reviews the data generated by the validated system suitability measures incorporated into the SOP. If an analyst sees one or more failures of those method system suitability criteria, the procedure has failed to generate a reliable result, i.e., it is an invalid run.
An invalid run does not mean the test sample failed its QC specifications, stated Ritter. It means the method failed to perform reliably enough to trust the accuracy of the test sample results.
“Invalid method runs in QC labs can be for assignable causes like an analyst dropped a pipette, made the wrong solution, or the instrument lamp blew out,” she said. “There are lots of operational glitches that can impact method performance. If invalid runs are due to assignable operational causes, they don’t necessarily reflect an inherent flaw in the method itself.
“Rather, they may be indicating management issues in the lab, such as the need for better instrument maintenance, more frequent calibration checks, better analyst training, or even more analysts to manage heavy workloads. These are corrective actions we can take.”
However, if there are no clear assignable operational causes for invalid results, it may suggest flaws in the method procedure itself. Perhaps the method was not adequately optimized for robustness, or the SOP was not written clearly enough for consistent execution, or changes in critical reagents shifted the method performance range.
“Building appropriate system suitability measures into every method SOP, then tracking/trending the frequency and nature of invalid runs, is a key tool to assure problems are found quickly, the right assignable causes are found, and corrective actions are meaningful and durable,” said Ritter, who will expand further on the “Value of Tracking and Trending Method Performance after Validation” and provide specific examples during next week’s presentation.
