WORKSHOP CURRICULUM

March 23 – March 25, 2026 | 9:30 PM IST | 11:00 AM CDT

Session 1: The AI Drug Discovery Toolkit
📅 March 23 | ⏰ 9:30 PM IST / 11:00 AM CDT
  • What AI can do in drug discovery
  • Predict molecular properties and generate molecules
  • Find similar compounds and predict protein structures
  • Introduction to RDKit, DeepChem and ChEMBL
  • Understanding when to use each tool
  • RDKit basics in Google Colab
  • Load molecules from SMILES
  • Visualize molecular structures
  • Calculate basic molecular properties
Session 2: Running Your First ML Model
📅 March 24 | ⏰ 9:30 PM IST / 11:00 AM CDT
  • Understanding molecular property prediction
  • Predicting solubility, toxicity and drug-likeness
  • How machine learning models learn from data
  • Using pre-trained DeepChem models
  • Preparing molecules for prediction
  • Running predictions in Google Colab
  • Interpreting prediction results
  • Practice predicting properties for multiple molecules
  • Understanding model confidence and limitations
Session 3: Expanding Your Toolkit
📅 March 25 | ⏰ 9:30 PM IST / 11:00 AM CDT
  • Molecular similarity search for compound discovery
  • Finding aspirin analogs and interpreting similarity scores
  • Using no-code tools like ADMETlab and SwissADME
  • Introduction to GitHub for drug discovery tools
  • Exploring repositories such as RDKit and DeepChem
  • Mini project: analyze a drug candidate
  • Calculate properties using RDKit
  • Predict ADMET using online tools
  • Identify similar approved drugs and present findings