Putting large language models into action for target Identification

BenevolentAI has developed a unique approach to address the complexity of disease through its validated AI-augmented drug discovery platform. In this talk Dr Dunbar will detail the comprehensive representation of disease biology built by combining many orthogonal data modalities and how this powers BenevolentAI’s target identification technology. This includes the integration of a vast amount of scientific literature using NLP and a large-scale proprietary molecular signature atlas for over 200 diseases. The Benevolent PlatformTM enables scientists to efficiently discover novel biology rooted in patient data, build hypotheses on the mechanisms on which to focus, and prioritise novel targets using all the evidence available using a purpose built proprietary LLM based framework. Dr Dunbar will describe how the platform is being put into action to tackle the complexity of disease and efficiently identify and validate novel drug targets.