How Inexact Models and Scientific Machine Learning Can Guide Decision Making in Quantitative Systems Pharmacology


Pre-clinical Quantitiative Systems Pharmacology (QSP) is about trying to understand how a drug target effects an outcome. If I effect this part of the biological pathways, how will it induce toxicity? Will it be effective?

Recently I have been pulling in a lot of technical collegues to help with the development of next generation QSP tooling. Without a background in biological modeling, I found it difficult to explain the "how" and "why" of pharmacological modeling. Why is it differential equations, and where do these "massively expensive global optimization" runs come from? What kinds of problems can you solve with such models when you know that they are only approximate?

To solve these questions, I took a step back and tried to explain a decision making scenario with a simple model, to showcase how playing with a model can allow one to distinguish … READ MORE