A Tolerance-based Approach for Validating Analytical Methods Using Design of Experiments

Abstract

Purpose

Statistically reliable analytical method validation is essential in pharmaceutical manufacturing to ensure accurate and reproducible test results, supporting quality assurance, regulatory compliance, and consistent production. However, traditional validation techniques often overlook dataset variations relative to the assay range or specification limits, potentially compromising assay fit-for-purpose, particularly for low concentrations of active pharmaceutical ingredients (APIs), excipients, or impurities. This study aims to address these limitations by developing and applying a tolerance-based design of experiments (DOE) approach for validating analytical methods, with a focus on polyethyleneimine (PEI), an impurity associated with lentiviral vector drug products.

Methods

The tolerance-based DOE approach identifies optimal experimental designs with minimal sample sizes, considering variability relative to tolerance or design margins rather than average values. An analytical method was validated using high-performance liquid chromatography (HPLC) to assess the accuracy, repeatability, and intermediate precision for low-concentration components. This novel framework was compared against traditional validation methods to evaluate its effectiveness.

Results

The tolerance-based approach corrected misinterpreted results for accuracy, repeatability, and intermediate precision, which are often skewed in traditional methods by calculations based on incorrect scales or averages. By measuring variability relative to tolerance limits, the method provides a more accurate reflection of data variations, enhancing the fitness-for-use of the assay. These results support more informed decision-making and ensure reliability and accuracy across the validation process.

Conclusion

This study demonstrates that a tolerance-based DOE approach effectively overcomes the limitations of traditional validation methods. By correctly analyzing and presenting accuracy and precision, this method enhances quality control processes and ensures the consistent production of safe and effective pharmaceutical products, offering significant advancements in validation practices, particularly for low-concentration analyses.