This collaboration has brought together the world’s leading researchers from India and Sweden to leverage AI and advanced computational biology to develop therapeutics targeting pneumonia-causing pathogens. A funding of ₹52.2 lakh from India and 2.8 million SEK from Sweden has been sanctioned for research and faculty/students mobility between the two countries, demonstrating strong support from both nations for advanced biomedical research.
Among the researchers from India, Dr. Docent N. Arul Murugan will lead as Principal Investigator, with Prof. G. P. S. Raghava and Dr. Vibhor Kumar serving as Co-Principal Investigators from the Department of Computational Biology at IIIT-Delhi. On the Swedish side, the team will be headed by Dr. Docent Vaibhav Srivastava from the KTH Royal Institute of Technology as Principal Investigator, along with Dr. Docent Ujwal Nyogi as Co-PI from the Karolinska Institute.
The project focuses on developing artificial intelligence-based peptide therapeutics to fight against pneumonia-causing pathogens. It is anticipated to be a more efficient and cost-effective drug discovery process. The procedure will include researchers developing machine learning models that can predict key peptide properties, such as antimicrobial activity, allergenicity, and toxicity. Generative AI will be employed to propose novel peptide therapeutics.
Commenting on this prestigious collaboration opportunity to revolutionise the healthcare industry by leveraging advanced technology, Dr. Docent N. Arul Murugan said, “In the coming years, biomedical discovery will be heavily transformed by artificial intelligence’s contribution. This India-Swedish collaboration displays IIIT-Delhi’s commitment to utilising computational biology, AI, and Gen-AI to address critical health challenges on a global scale. The integration of advanced machine learning and experimental validation can accelerate the discovery of peptide therapeutics to combat pneumonia-causing pathogens.”
Ultimately, the purpose of this research partnership is to shorten drug discovery timelines while delivering cost-effective therapeutic solutions for pneumonia and other respiratory diseases. This approach will demonstrate the evolutionary potential of artificial intelligence in biomedical healthcare innovation.
