FABA holds workshop on AI in pharma & biotech

Hyderabad: The Federation of Asian Biotech Associations (FABA) on Monday said it has organised a workshop on “Artificial Intelligence for Pharma and Biotech,” in collaboration with Science Gurus and the University of Hyderabad. The event which started on Monday is being held in partnership with the World Trade Center (WTC) Shamshabad, and it will end on December 16, 2023.

The workshop began with opening remarks from Prof P Reddanna, Executive president of FABA. Dr Jagath Reddy Junutula of Science Gurus and Dr Bindu Madav Reddy from the University of Hyderabad delivered the welcome address.

The first speaker Dr Krishnan Nandabalan, president and CEO of InveniAI, delivered atalk on “Artificial Intelligence for Pharma and Biotech – From Hype to Reality.” During his talk, Dr Nandabalan shed light on the ever- evolving landscape of healthcare, the integration of Artificial Intelligence and Machine Learning (AI/ML),proving to be transformative. He also emphasised that a shift towards more in-silico work and reduced wet labexperimentation holds promise. He also highlighted various applications of AI ranging frominnovating target and drug discovery to pre-IND development.

Dr Sunu Engineer, iSPIRT, delivered the key note address on “WhyDoes Intelligence Need Data? Building the AI Nation.” Dr Sunu said that there is an urgent need for safe and secure collection of information, aligned with principles of consent, purpose limitation, and privacy.

The day proceeded with the third speaker, Dr Vasudeva Varma, Principal Research Scientist, Brane Enterprises. He delivered a lecture on “Role of Gen AI and Large Language Models inHealthcare.”

Dr Varma concluded his talkwith the hurdles resulting in the adoption of Generative AI in healthcare, such as transparency, safety, ethics, and accountability.

The last speaker of the day, Dr Luca Emili, Founder and CEO of InSilicoTrials, spoke about “Applications,Modeling, and Simulation for Pharma and Life Sciences.”Dr Luca shed light on the inherent challenges faced inthe development of computational models.