This repository contains all materials and resources from the AI2050 H3D in-house workshop held in June 2025.
Session 1: Ready-to-use AI/ML models for drug discovery with the Ersilia Model Hub
Drug Discovery is a long and expensive process - how can AI/ML methods help?
Why is this particularly relevant in low-resource settings?
What is the Ersilia Model Hub?
Session 2: Predicting ADMET properties for your compounds of interest
ADMET properties are a fundamental consideration in drug discovery pipelines. ADMET refers to Absorption, Distribution, Metabolism, Excretion, and Toxicity. These properties determine the pharmacokinetic and safety profiles of drug candidates and play a critical role in predicting how a compound behaves in the human body.
Examples of ADMET properties are:
Blood-brain barrier penetration
Cytochrome inhibition
Predicting ADMET properties using the Ersilia Model Hub.
Session 3: Predicting bioactivity for your compounds of interest and selecting candidates to purchase
