Application of a System Model for Continuous Manufacturing of an Active Pharmaceutical Ingredient in an Industrial Environment
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Abstract
Purpose In pharmaceutical manufacturing, understanding and quantifying how process conditions impact product quality is pivotal to guaranteeing process profitability with sustained product yield. We describe an integrated system model for a commercial-scale continuous manufacturing process of a high-value active pharmaceutical ingredient (API) and its use to optimize process conditions to maximize yield with assured product quality. Methodology Global sensitivity analysis (GSA) was used to assess different process parameters' impacts on API yield in order to guide the selection of decision variables for yield optimization. We then formulated different scenarios for optimization within approved process parameter ranges to propose optimal process conditions to increase API yield. Results Within the considered parameter space, varying only key initial starting material and feed reagent mass fractions within their allowed parameter ranges showed potential for + 0.2% yield improvement while varying all process parameters could allow + 0.4% yield improvement. Conclusions The general modelling framework to guide control strategies, highlight process improvements in silico, and reduce experimental burden can be applied to multiple pharmaceutical products across different manufacturing modalities and operating modes.
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Affiliations
- GlaxoSmithKline (GSK)
- Nexeon Ltd
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Classification Areas
- API
- Modeling