The Use of Bayesian Hierarchical Logistic Regression in the Development of a Modular Viral Inactivation Claim.

Low pH inactivation of enveloped viruses has historically been shown to be an effective viral inactivation step in biopharmaceutical manufacturing. To date, most statistical analyses supporting modular low pH viral inactivation claims have used descriptive statistical analyses, which in many cases do not allow for probabilistic characterization of future experimental log reduction values (LRVs). Using Bayesian hierarchical logistic regression modeling, probability statements regarding the likelihood of successful low pH viral inactivation based on only certain process parameter settings can be derived.