Model‐based risk analysis of coupled process steps

Abstract

A section of a biopharmaceutical manufacturing process involving the enzymatic coupling of a polymer to a therapeutic protein was characterized with regards to the process parameter sensitivity and design space. To minimize the formation of unwanted by-products in the enzymatic reaction, the substrate was added in small amounts and unreacted protein was separated using size-exclusion chromatography (SEC) and recycled to the reactor. The quality of the final recovered product was thus a result of the conditions in both the reactor and the SEC, and a design space had to be established for both processes together. This was achieved by developing mechanistic models of the reaction and SEC steps, establishing the causal links between process conditions and product quality. Model analysis was used to complement the qualitative risk assessment, and design space and critical process parameters were identified. The simulation results gave an experimental plan focusing on the "worst-case regions" in terms of product quality and yield. In this way, the experiments could be used to verify both the suggested process and the model results. This work demonstrates the necessary steps of model-assisted process analysis, from model development through experimental verification.