- In silico API design
- Continuous manufacturing
- Pharmaceutical formulation design
- Large-scale process simulations
- Artificial intelligence and machine learning
Pharmaceutical companies have started to embrace digital design of products, and especially “big pharma” is leading the way in using advanced computational methods for a wide variety of objectives, including target identification, in silico API design and prediction of API properties, as well as biopharmaceutics. Formulated product design and the effect of processing have received less attention, yet are increasingly becoming embedded in modern product development pathways. In my talk I will present state-of-the-art methods for the design of pharmaceutical formulations (e.g., with respect to stability or biopharmaceutics) and for the analysis and control of pharmaceutical manufacturing operations, with a focus on continuous manufacturing.
These methods combine molecular design approaches with large-scale process simulation methods (e.g., high-fidelity discrete element methods coupled to advanced CFD, including smoothed particle hydrodynamics of Lattice-Boltzmann methods), as well as state-of-the-art control methods. Examples are given (e.g., hot-melt extrusion, fluid bed operations, blending, bioreactor technology) and open challenges are highlighted. Also the promises of AI are critically reviewed.