skilldevelopment.cpe@lpu.co.in

What you'll learn

Course Description (100 words) The Foundations Certificate Course in Artificial Intelligence in Drug Discovery and Development (30 hours) equips learners with essential skills to apply AI in pharmaceutical research. Covering the drug discovery pipeline, AI-driven simulations, and safety monitoring, the course explores platforms like IBM Watson Health and BioNemo for molecular analysis, toxicity prediction, and personalized medicine. Through lectures, hands-on tutorials, and case studies, participants learn to streamline drug development, enhance safety, and leverage big data. Designed for pharmacy, biotechnology, and data science professionals, it requires basic biology/chemistry knowledge and offers practical experience with AI tools. Learning Outcomes (100 words) Understand Drug Discovery: Describe the drug discovery pipeline and AI’s role in optimizing each stage. Apply AI Techniques: Use AI platforms for molecular analysis, drug candidate identification, and efficacy prediction. Master Simulation Tools: Implement AI-driven simulations (e.g., Body Interact, SimX) for training and drug design. Analyze Public Health Data: Leverage AI for public health surveillance and big data analytics. Predict Safety/Toxicity: Employ AI to predict adverse drug reactions and molecular toxicity. Enhance Pharmacy Operations: Utilize AI for automation and medication adherence monitoring. Advance Personalized Medicine: Apply AI for precision medicine and future pharmacology trends.

  • • AI in Drug Discovery and Development • AI platforms to identify drug candidates, analyze molecular data, and predict interactions to assess drug efficacy • AI in Drug Discovery and Preclinical Testing
  • • AI modeling technologies in simulation-based learning, including student modeling and teacher modeling • AI-assisted simulation games-based education
  • • Body Interact, SimX, IBM Watson Health, Synthesia, Pictory, Animoto
  • • AI in public health surveillance • Real-World Big Data Analytics
  • • AI in Drug Safety; AI platform to predict adverse drug reactions (ADRs) and interactions, enhancing the safety profile of medications and ensuring more effective treatment regimens. • Toxicity prediction of small molecules based on chemical structure Advance AI Model Case study: Deepmind, BioNemo, Neuralink
  • • Pharmacy Automation & Medication Dispensing • Medication Adherence Monitoring (AI-enabled wearables, apps)
  • • Adverse Drug Reaction (ADR) Prediction • Leveraging AI for medicines and vaccines safety monitoring
  • AI in Personalized Medicine & Future of Pharmacology

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Dr. Kanav Khera
Professor

Working as Professor, Dept of Pharmacy Practice with more than 17 years of experience in clinical research/biomedical ethics/evidence-based medicine, antibiotic stewardship programs, pharmacovigilance, drug safety, clinical trials, and outcome research. Dr Kanav Khera is also an associate member secretory of the Institutional Ethics Committee at School of Pharmaceutical Sciences, LPU. Dr Kanav Khera had vast experience in providing pharmaceutical care services in Tertiary care hospitals and handling medication errors and related problems. Had published more than 40 research papers in national and international journals and was invited as a guest speaker at various events. Dr Kanav Khera has been honoured with Best teacher and excellence in teaching awards and and also worked as Scientist 1 in a clinical research organization conducting clinical trials


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Dr. Rahul Saha
Professor

Prof. Rahul Saha, School of Computer Science and Engineering, Research and Development Cell, LPU