Webinar Overview
Webinar Overview
This webinar demonstrates how Machine Learning (ML) accelerates drug discovery by replacing manual trial-and-error with systematic, automated model selection.
The Case Study: Researchers modeled a CNS disease pathway, successfully correlating in vitro binding data with in vivo efficacy to identify a lead clinical candidate.
The ML Advantage: Unlike traditional sequential modeling, the ML engine scans an entire "landscape" of candidate models and covariates in parallel, identifying the most efficient mathematical structure to explain the data.
Balancing Accuracy & Stability: To prevent overfitting, the team used penalty functions and external validation. This ensures the model isn't just "matching noise" but is robust enough to predict outcomes for new compounds.