Workshop Overview:
This workshop would introduce participants to the core concepts and applications of AI and machine learning in the drug discovery process, with a focus on how these technologies can accelerate research in the pharmaceutical industry.
Max no of participants: Unlimited
Venue: Main Auditorium, HSAAS UPM
Objective:
To equip participants with the understanding and tools necessary to apply AI in various stages of drug discovery, including target identification, drug design, and personalized medicine.
Key Sessions:
1. Introduction to AI and Machine Learning in Drug Discovery
- Overview of AI techniques in pharma
- Challenges and opportunities in drug discovery
2. AI in Drug Target Identification and Validation
- Machine learning models for predicting drug targets
- Case studies of successful AI-driven target identification
3. De Novo Drug Design Using AI
- Generative models (e.g., GANs) for novel drug development
- AI tools for compound screening and optimization
4. AI in Personalized Medicine
- Predicting individual drug responses through AI
- Case examples of AI-driven precision medicine in pharma
5. AI for ADMET and Toxicity Prediction
- How AI models predict drug absorption, distribution, metabolism, excretion, and toxicity
- Practical demo of using AI tools for ADMET prediction
6. Hands-on Session: AI in Drug Discovery
- Participants will work with AI tools or datasets to predict drug-target interactions or analyze molecular structures
- Real-time problem-solving with expert guidance
Tentative Workshop Schedule:
Time | Activity |
9:00 AM – 10:30 AM | Session 1: Introduction to AI in Drug Discovery – Overview of AI applications in pharmaceutical research – Machine learning vs. deep learning in drug discovery – Case studies of AI-driven drug development |
10:30 AM – 10:45 AM | Break |
10:45 AM – 12:30 PM | Session 2: Hands-on Molecular Data Processing – Introduction to molecular datasets (SMILES, PDB, SDF formats) – Data preprocessing and feature extraction for drug molecules – Hands-on: Using Python (RDKit) for molecular descriptor generation |
12:30 PM – 1:30 PM | Lunch Break |
1:30 PM – 3:00 PM | Session 3: AI Models for Drug Discovery – Basics of neural networks for drug discovery QSAR modeling using AI – Hands-on: Building a simple machine learning model for drug activity prediction |
3:00 PM – 3:15 PM | Break |
3:15 PM – 4:30 PM | Session 4: Virtual Screening & Molecular Docking – AI-powered molecular docking and virtual screening – Hands-on: Running an AI-assisted virtual screening using open-source tools – Closing & Discussion |
SPEAKER:
Prof. Dr Vannajan Sanghiran Lee
Empowering Molecular Creators and Innovators: Driving Sustainable Development through Molecular Modeling and Simulations
Affiliation: Department of Chemistry, Centre of Excellence in Quantum Information Science and Technology (UMQIST), Faculty of Science, University of Malaya, Kuala Lumpur 50603, Malaysia
E-mail: vannajan@um.edu.my, vannajan@gmail.com +60-163208906
Dr. Lee is a prominent researcher in molecular modelling, quantum science, and artificial intelligence (AI). She received the 2023 UNESCO Woman of Influence for Science and Technology award at the 1st International Congress for the Women of Influence (ICFWI) for her impactful contributions. As Head of the Centre of Excellence for Quantum Information Science and Technology (QIST) at Universiti Malaya, she leads cutting-edge research at the intersection of quantum computing, AI, and molecular simulation.
Dr. Lee, a recipient of Thailand’s prestigious Development and Promotion in Science and Technology (DPST) scholarship, earned her PhD from the University of Missouri–Kansas City, USA. Her research pushes the boundaries of quantum-enhanced modelling, AI-assisted drug discovery, and sustainable innovation.
Beyond research, Dr. Lee actively mentors the next generation of scientists as advisor to the ACS University of Malaya International Student Chapter. She also supports innovation through MolDesign, a student-founded initiative advancing molecular and AI-based creativity. As co-founder of Qubios Sdn. Bhd., a quantum-AI health tech startup under the UM Deep Tech Start-up Program, she pioneers the integration of quantum computing, AI, and data science to transform precision medicine, environment, energy, and sustainability sectors.
Click here to view all the other Pre-Conference Workshops >>