– Financing will support development of a foundational machine learning model of medicinal chemistry that can accurately predict small molecule drug candidates for any protein – – Releases unprecedented dataset publicly to address critical challenges in drug discovery with machine learning – SALT LAKE CITY, April 05, 2024 (GLOBE NEWSWIRE) -- Leash Biosciences, an artificial intelligence and machine learning (AI/ML)-native biotechnology company unleashing machine learning to solve medicinal chemistry, today announced the completion of a $9.3 million seed financing round to advance its mission of revolutionizing medicinal chemistry through modern computational methods and massive biological data collection. The oversubscribed round was led by Springtide Ventures with participation from MetaPlanet, Top Harvest Capital, Mitsui Global Investment, MFV Partners, Recursion CEO and co-founder Chris Gibson, and Recursion co-founder Blake Borgeson. Leash aims to develop a foundational and generalizable machine learning model of medicinal chemistry that can accurately predict small molecule drug candidates for any protein in silico, and more broadly, interactions between any protein and any chemical. To achieve this, Leash is producing bespoke, expansive datasets of protein targets binding to chemicals. To date, the Company has physically generated over 17 billion high-quality protein-chemical interaction measurements. In its new Salt Lake City headquarters, Leash plans to screen 500+ protein targets against many millions of machine learning-designed, proprietary chemicals by 2025. "ML improvements in chess, Go, image recognition, language translation, text generation, and protein folding all were driven by the collection and curation of massive datasets. We believe a similar strategy will revolutionize how we approach medicinal chemistry," said Ian Quigley, CEO of Leash Biosciences. "We are thrilled to have the support of ...