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No matter if classical biologics or ATMPs – generic methodologies are needed to efficiently identify robust control strategies along the product life cycle.
Digital twins are a means to capture and to deploy knowledge for example for efficient experimental design, prediction of product quality or process events or also for process optimization.
This contribution shows use cases, as to how digital twins can be deployed for various modalities, also including random effects from starting material as this is an inherent challenge for ATMPs.
Last but not least we discuss prerequisites to commercialize digital twin approaches.
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