Material Detail

An open educational resource module delivering a rigorous foundation in Pharmaceutical Engineering. Covers formulation design, bioprocess scale-up, Quality by Design (QbD), continuous manufacturing, and regulatory compliance (GMP, FDA, EMA). Integrates classical transport phenomena and reactor design with contemporary 2026 computational paradigms, including Physics-Informed Neural Networks (PINNs) for non-Newtonian hot-melt extrusion and drying, DeepONets for bioreactor glycosylation kinetics, and edge-deployed machine learning for inline Process Analytical Technology (PAT) tablet rejection. Features a multi-step crystallizer scale-up calculation under constant volumetric power dissipation, a structured systems engineering trade-off matrix, an interactive USP dissolution simulator, and three tiers of structured self-assessment modules with full quantitative solutions.

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