BenevolentAI partners with the Helix Group at Stanford University to advance research on AI-driven drug discovery

BenevolentAI and the Helix Group — led by Professor Russ Altman — will research more effective methods to extract knowledge from biological and clinical information.

London, 3 February 2022, BenevolentAI, a leading clinical-stage AI-drug discovery company, today announced details of an AI research collaboration with the Helix Group, a Stanford University-based research lab led by Professor Russ Altman. The partnership aims to discover more effective methods to extract knowledge from biological and clinical information and ultimately extend the potential of artificial intelligence in helping scientists discover and develop better medicines.

Prof. Russ Altman, Professor of Bioengineering, Genetics, & Medicine at Stanford and Director of The Helix Group, and Scientific Advisor at BenevolentAI, commented; “Scientific researchers are generating more data than ever before, and there is an immediate need to extract information from this data to discover better medicines, faster. Our partnership with BenevolentAI aims to represent this information more precisely, to enhance the downstream target and drug predictions made by machine learning models, and ultimately help scientists translate algorithmic advances into medical breakthroughs.”

Daniel Neil, Chief Technology Officer at BenevolentAI, commented, “Both BenevolentAI and Stanford University are leaders in using AI to tackle the biggest challenges in biology and medicine. By pooling our collective experience with the world-leading researchers at Stanford, we can help to advance state-of-the-art research and deliver technological innovations that will transform patients’ lives.”

Tapping into the potential of AI to improve drug discovery efforts has become a focus in both academia and industry. The use of AI in drug discovery and development, however, has many challenges. AI can extract information from literature and data, in the form of relationships between biomedical entities such as genes, chemicals and diseases. The characteristics of these relationships, however, can often appear contradictory, which may be because the relationships are contingent on the biological context in which they occur. In response to these challenges, BenevolentAI and Stanford will focus their research on the role of context in information extraction. The team are planning to develop a state of the art context extraction model, which will add more confidence and accuracy to machine learning models used to identify novel drug targets and therapeutics.

Please Don’t Use This Sentence Out Of Context

BenevolentAI and Stanford University review progress in their AI research partnership, which looks at the role of ​​co​​ntext in information extraction.

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