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The newly updated FDA Guidance for Industry on Process Validation: General Principles and Practices ushers in a life cycle approach to process validation. While the guidance no longer considers the use of traditional three-batch validation appropriate, it does not prescribe the number of validation batches for a prospective validation protocol, nor does it provide specific methods to determine it. This potentially could leave manufacturers in a quandary. In this paper, I develop a Bayesian method to address the issue. By combining process knowledge gained from Stage 1 Process Design (PD) with expected outcomes of Stage 2 Process Performance Qualification (PPQ), the number of validation batches for PPQ is determined to provide a high level of assurance that the process will consistently produce future batches meeting quality standards. Several examples based on simulated data are presented to illustrate the use of the Bayesian method in helping manufacturers make risk-based decisions for Stage 2 PPQ, and they highlight the advantages of the method over traditional Frequentist approaches. The discussions in the paper lend support for a life cycle and risk-based approach to process validation recommended in the new FDA guidance., Lay Abstract: The newly updated FDA Guidance for Industry on Process Validation: General Principles and Practices ushers in a life cycle approach to process validation. While the guidance no longer considers the use of traditional three-batch validation appropriate, it does not prescribe the number of validation batches for a prospective validation protocol, nor does it provide specific methods to determine it. This potentially could leave manufacturers in a quandary. In this paper, I develop a Bayesian method to address the issue. By combining process knowledge gained from Stage 1 Process Design (PD) with expected outcomes of Stage 2 Process Performance Qualification (PPQ), the number of validation batches for PPQ is determined to provide a high level of assurance that the process will consistently produce future batches meeting quality standards. Several examples based on simulated data are presented to illustrate the use of the Bayesian method in helping manufacturers make risk-based decisions for Stage 2 PPQ, and THEY highlight the advantages of the method over traditional Frequentist approaches. The discussions in the paper lend support for a life cycle and risk-based approach to process validation recommended in the new FDA guidance.

Parallelism is a prerequisite for the determination of relative potency in bioactivity assays. It involves the testing of similarity between a pair of dose-response curves of reference standard and test sample. The evaluation of parallelism is a requirement listed by both the United States Pharmacopeia (USP) and European Pharmacopeia (EP). The revised USP Chapters 〈1032〉 and 〈1034〉 suggest testing parallelism using an equivalence method. However, implementation of this method can be challenging for laboratories that lack experience in statistical analysis and software development. In this paper we present a customized assay analysis template that is developed based on a fully good manufacturing practice (GMP)-compliant software package. The template allows for automation of the USP-recommended equivalence parallelism testing method for 4PLmodel in bioassays. It makes the implementation of the USP guidance both practical and feasible. Use of the analysis template is illustrated through a practical example., Lay Abstract: Parallelism is a prerequisite for the determination of relative potency in bioactivity assays. It involves the testing of similarity between a pair of dose-response curves of reference standard and test sample. The evaluation of parallelism is a requirement listed by both the United States Pharmacopeia (USP) and European Pharmacopeia (EP). The revised USP Chapters 〈1032〉 and 〈1034〉 suggest testing parallelism using an equivalence method. However, implementation of this method can be challenging for laboratories that lack experience in statistical analysis and software development. In this paper we present a customized assay analysis template that is developed based on a fully good manufacturing practice (GMP)-compliant software package. The template allows for automation of the USP-recommended equivalence parallelism testing method for 4-parameter logistic model in bioassays. It makes the implementation of the USP guidance both practical and feasible. Use of the analysis template is illustrated through a practical example.