Excelsior科学公司融资9500万美元，借助人工智能加速小分子药物研发

Core Insights - Excelsior Sciences has raised $95 million for the development of machine and artificial intelligence technologies aimed at accelerating the research and testing of small molecules, with the goal of shortening drug development cycles by several years [1][3] Funding Details - The company completed a $70 million Series A funding round led by Deerfield Management, Khosla Ventures, and Sofinnova Partners, along with a $25 million grant from the Empire State Development [1][3] Market Context - Small molecule drugs account for the majority of approved drugs in the U.S., with approximately 60% of newly approved drugs by the FDA still being small molecules, despite the rise of antibody and cell therapies [4] Development Challenges - The research and preparation process for small molecule drugs is slow and costly, often exceeding 10 years and requiring billions of dollars due to the need for customized synthesis processes [4] Technological Innovation - Excelsior Sciences employs a "smart bloccs" approach, described as a new modular language that helps AI more accurately predict how to develop and optimize new therapies [4][5] Efficiency Improvements - A typical process previously took about 4 months or longer, often requiring coordination across multiple contractors in the U.S. and Asia; the new automated facility can reduce this to approximately two weeks [5] - The same process can be scaled for subsequent production, potentially saving an additional 1 to 18 months before clinical trials begin [5] Future Plans - The company plans to demonstrate the full operational capabilities of its platform within 12 months and apply it to at least one drug development project [5]