🔴 Expanded & Enhanced Training Content 🔴
🧪 Core Drug Discovery & Research Modules
- 🔹 Introduction to Drug Discovery & Development Pipeline (Preclinical to Clinical)
- 🔹 Target Identification vs Target Validation: Case Studies & Tools
- 🔹 Hit to Lead & Lead Optimization
- 🔹 Structure-Activity Relationship (SAR) & QSAR Fundamentals
🖥️ Computational Tools & Software Training
- 🔹 Overview of Widely Used Tools (e.g., PyRx, AutoDock, SwissADME, VMD, GROMACS)
- 🔹 Open Source vs Licensed Tools: Which to Use and When
- 🔹 Installing & Managing Computational Tools on Windows/Linux
🤖 AI & ML in Drug Design – Deep Dive
- 🔹 Introduction to Cheminformatics
- 🔹 Dataset Preparation for ML/AI (SMILES, Fingerprints, Feature Engineering)
- 🔹 Building Simple ML Models with scikit-learn for Molecular Property Prediction
- 🔹 Introduction to Deep Learning in Drug Design (e.g., using TensorFlow or PyTorch basics)
🔬 Molecular Modeling & Simulation
- 🔹 Homology Modeling of Target Proteins
- 🔹 Ligand & Protein Preparation Workflow
- 🔹 Introduction to Quantum Mechanics in Drug Discovery
- 🔹 Enhanced Sampling Techniques in Molecular Dynamics
📈 Data Analysis & Research Reporting
- 🔹 Generating & Interpreting Drug-likeness and Toxicity Reports
- 🔹 How to Present Binding Affinity, Pharmacokinetics, and Simulation Results
- 🔹 Tools for Scientific Plotting & Visualization (GraphPad Prism, matplotlib, seaborn)
📄 Scientific Writing & Publication Skills
- 🔹 How to Write a Research Paper (IMRAD Structure)
- 🔹 Referencing and Citation Tools (Zotero, Mendeley)
- 🔹 Choosing the Right Journal (e.g., Q1 vs Q4, impact factor insights)
- 🔹 Ethical Research & Avoiding Plagiarism
💼 Career Pathways in Drug Discovery
🔹 Guidance on Internship/Job Applications (e.g., via LinkedIn, Pharma websites)
🔹 Industry vs Academia: Where Can You Go?
🔹 Building a Career in Bioinformatics, Cheminformatics, and CADD
🔹 Resume/CV Building for the Pharmaceutical Industry
