Multiphysics simulations are highly effective for developing pharmaceutical processes, but their computational cost limits scalability.
Physics-Informed Neural Networks (PINNs), trained on multiphysics simulation data, can retain comparable detail and complexity while being far less computationally intensive, enabling faster development and highly scalable process modeling.
Florian Ries, Principal Research Scientist I, AbbVie
