Comparison of Methods for Setting Acceptance Criteria in a Multi-Staged Pharmaceutical Manufacturing Process

• Activity Number: 469
• Type: Contributed
• Date/Time: Wednesday, August 3, 2011 : 8:30 AM to 10:20 AM
• Sponsor: Section on Quality and Productivity
• Author(s): Richard Montes*+ and Jorge Quiroz and David Christopher
• Companies: Merck Research Laboratories and Merck Research Laboratories and Merck Research Laboratories
• Keywords: acceptance criteria ; multi-staged process ; tolerance interval ; risk minimization ; variation transmission ; autoregressive model

Abstract

Pharmaceutical manufacturing processes consist of a series of stages (e.g., reaction, work-up, isolation) to generate the active pharmaceutical ingredient (API). Outputs at each stage need to be controlled within acceptance criteria to assure final drug product quality. In this paper, two methods based on tolerance interval to derive such acceptance criteria will be evaluated. The first method is SERIAL WORST-CASE, an industry risk minimization strategy, wherein input process parameters and materials of a stage are fixed at worst-case settings, the procedure serially repeated throughout next stages until the final output. The second method is the VARIATION TRANSMISSION USING AUTOREGRESSIVE MODEL wherein variation transmitted through ith stage is estimated accounting for the recursive structure of the errors at each stage. Computer simulations at varying extent of variation transmission and process variability are performed and the resulting confidence coefficients and average tolerance interval lengths in the two methods are compared. The second method performs better and is recommended for setting in-process and API streams in a multi-staged pharmaceutical manufacturing process.