A three-day conference on AI-driven innovations in drug discovery has begun in Kathua

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Jammu/Kathua: A three-day conference-cum-workshop on AI-driven innovations in drug discovery and agriculture, organised by the CSIR–Indian Institute of Integrative Medicine (IIIM), began on Wednesday at the Industrial Biotech Park in Kathua district of Jammu and Kashmir, officials said.

The event aims to showcase the transformative impact of artificial intelligence in advancing drug discovery and agriculture, with particular focus on innovations such as semiconductor devices, electronic tongues, and adulteration-detection sensors.

Inaugurating the event at the BioNEST Incubator, P. C. Panchariya, Director of the Central Electronics Engineering Research Institute (CEERI), Pilani, highlighted AI’s expanding role in medical diagnostics and expressed interest in collaborations with CSIR-IIIM and BioNEST. He also noted CEERI’s progress in developing semiconductor devices, electronic tongues, and sensors for detecting adulteration in dairy products and edible oils.

“AI-driven innovations can accelerate scientific breakthroughs, optimize processes, and support sustainable development across healthcare and agriculture,” he said.

IIIM Director Zabeer Ahmed said the conference aims to foster innovation, capacity building, and entrepreneurship in AI-based drug discovery and agricultural research. He added that CSIR-IIIM has already integrated AI tools to speed up research and crop improvement, and that hosting the event at the Biotech Park would encourage greater local engagement with science and technology.

According to the organisers, 75 participants from across India are attending the workshop, including 15 students from GDC Kathua and Jammu University’s Kathua Campus, who received free registration.

The programme includes technical sessions, keynote lectures, and hands-on workshops on AI applications in drug design, molecular screening, and agricultural data analytics. Day one featured sessions on AI models for genomics, cheminformatics for anticancer drug discovery, and machine learning frameworks for predicting molecular interactions, officials said.

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