Revealing the Unseen: AI's Role in Novel Target Discovery for High Unmet Needs Areas Through Multi-Omics Integration

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• Namshik Han, Head of Computational Research & AI, Milner Therapeutics Institute, University of Cambridge
• Monday 21 October 2024, 12:00-12:30
• Computer Lab, FW11.

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The role of AI and data-driven methodologies is set to play a huge part in the drug discovery industry, allowing intricate details of a multitude of disease mechanisms and improving the way for the streamlined development of therapeutics. The focus of this seminar would give an overview of how AI and Multi-Omics are shaping betterment in the area of the improved identification and profiling of therapeutic targets.

I will describe the general AI principles and show how they apply to drug discovery in a manner that can be followed by a wide audience. This should give the participants with even the barest understanding of the technical background an understanding of the value that this tool adds in drug discovery. I shall take our research using AI and machine learning coupled with advanced mathematical models. Integrative analysis of multi-omics datasets enabled identifying new targets and pathways that may suggest new avenues for their use in understanding complex biological questions.

The presentation also focuses on how such academic insights work out in the domain of commerce and further reflected through my experiences of founding and running AI-driven Startups: Kure.ai Therapeutics and CardiaTec Biosciences. The second one will bring out examples that evidently show the relevance of our findings in practical scenarios of developing innovative solutions in the area of cardiovascular diseases.

The talk concludes with a Q&A session and gives a very succinct but also very full picture of the role of AI and data-driven methods in modern drug discovery. It is in this regard that the subject of the seminar will put forth how these emerging technologies are enablers for increased precision and efficiency in the development of therapeutics today or will be, thus allowing an informed discussion among participants hailing from academia to biotech to big pharmaceuticals.

This talk is part of the ML@CL Ad-hoc Seminar Series series.

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