Abstract
Quality by digital design (QbDD) utilizes data-driven, mechanistic, or hybrid models to define and optimize a manufacturing design space. It improves upon the QbD approach used extensively in the pharmaceutical industry. The computational models developed in this approach identify and quantify the relationship between the product's critical quality attributes (CQAs) and the critical process parameters (CPPs) of unit operations within the manufacturing process. This chapter discusses the QbDD approach in developing and optimizing unit operations such as in vitro transcription, tangential flow filtration, affinity chromatography, and lipid nanoparticle (LNP) formulation in mRNA vaccine manufacturing. QbDD can be an efficient framework for developing a production process for a disease-agnostic product that requires extensive experimental and model-based process-product interaction characterization during the early process development phase.
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