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CSIR holds three-day workshop on AI tools for drug discovery at Ghaziabad centre
CSIR trained scientists in AI-driven drug discovery at a three-day Ghaziabad workshop in April 2026. Sessions covered machine learning, molecular docking, and simulation tools that can cut drug development timelines.
CSIR Workshop Trains Scientists in AI-Driven Drug Discovery
The CSIR-Human Resource Development Centre in Ghaziabad ran a three-day workshop from April 7-9, 2026, teaching CSIR scientists and technical officers how to use artificial intelligence tools in drug discovery. The program addressed a gap: most pharmaceutical researchers lack formal training in AI applications despite the technology's growing role in their field.
Drug development typically takes 10 to 15 years and costs billions of dollars. AI-powered computational models can compress timelines and reduce costs by automating early-stage screening and predicting which molecules are likely to succeed, said Prof. G. N. Sastry of IIT Hyderabad during the workshop's opening session.
What the Workshop Covered
Sessions focused on practical applications rather than theory alone. Speakers from institutions including NIPER, IBAB, and IIT Delhi covered:
- Machine learning algorithms for predicting how proteins and drug molecules interact
- Deep learning models for screening drug candidates
- Molecular docking and scoring techniques
- Biomarker identification using AI
- Biomolecular simulation tools that reduce the need for lab experiments
Participants learned to use simulation tools that cut experimental work while improving accuracy-a significant advantage when testing thousands of potential compounds.
Why This Matters for Indian Pharma
India's pharmaceutical sector is worth over $50 billion but lags behind competitors in adopting AI for research. Building expertise among government scientists positions India to compete in drug discovery markets where speed and efficiency determine success.
The workshop was part of CSIR's effort to build capacity in emerging technologies. Organizers said feedback from participants will inform future training programs.
For scientists looking to develop these skills, AI for Science & Research courses cover applications in laboratory research and optimization.