Developing Process Performance Qualification (PPQ) Acceptance Criteria for a Large Molecule Product with Limited Data

• Activity Number: 114
• Type: Topic Contributed
• Date/Time: Monday, August 4, 2014 : 8:30 AM to 10:20 AM
• Sponsor: Biopharmaceutical Section
• Author(s): Brenda Ramirez*+
• Companies: Amgen
• Keywords: PPQ ; Acceptance Criteria ; Exponential Growth Model ; Tolerance Intervals ; Monte Carlo Simulation

Abstract

The new FDA Process Validation guidance recommends a lifecycle approach for process validation by allowing the manufacturer to incorporate process and product understanding into the timing and size of the validation campaign (referred to in the FDA document as Process Performance Qualification or PPQ). This presentation focuses on two statistical approaches for setting PPQ acceptance criteria with limited process characterization data. In particular, we utilize Monte Carlo simulations to establish PPQ acceptance criteria based upon the output from statistically designed experiments and empirical models that include scale effects and estimates of manufacturing variation. We also discuss how to incorporate prior knowledge from other large molecules when limited data are available from engineering, qualification, and confirmation runs. In this case, PPQ acceptance criteria are determined using tolerance intervals, where the mean and variance are informed by physical models and variation from other molecules.