Identifying Hidden Chemotherapy Drug Action Using Universal Physics-Informed Neural Networks

The core message of this work is to integrate machine learning in the form of Universal Physics-Informed Neural Networks (UPINNs) with Quantitative Systems Pharmacology (QSP) models in order to identify unknown drug actions within QSP models, using both synthetic and in-vitro experimental data.