![]() ![]() The more adept manufacturers are at process modeling, the better able they are to monitor and control the CPPs that determine a product’s critical quality attributes (CQAs). Process modeling is a manufacturing discipline for understanding the effects of process inputs (raw materials) and CPPs on final products. This article describes advanced process modeling, introduces three use cases for it, and offers guidelines to boost the likelihood of success with its use. In addition, the quality and R&D functions can upgrade product and process parameters during the next R&D cycle. ![]() With these insights, plant operators can adjust critical process parameters (CPPs) such as temperature or pH and improve decision making during production. In addition to these tangible benefits, advanced process modeling deepens manufacturers’ understanding of their production processes. Leading companies that use this tech-enabled approach to process modeling have seen a reduction in deviations (for example, products outside specifications) of more than 30 percent and have cut the overall cost of quality by 10 to 15 percent. This article is a collaborative effort by Álvaro Carpintero, Evgeniya Makarova, Miguel Ángel Morán, Matthias Spiegl, and Vanya Telpis, representing views from McKinsey’s Life Sciences and Operations Practices.Ĭompanies can leverage these models to improve performance and quality-even beyond what regulators may require-and save time and resources.
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