By Kamal Choudhury
Dec 3 (Reuters) – Excelsior Sciences said on Wednesday it has raised $95 million to develop technology that uses machines and artificial intelligence to accelerate the development and testing of small molecules, aiming to cut years off drug discovery timelines.
The company announced a $70 million Series A round co-led by Deerfield Management, Khosla Ventures and Sofinnova Partners, along with a $25 million grant from New York’s Empire State Development.
It did not disclose the valuation at which the funds were raised.
Small molecules make up the majority of medicines approved in the United States. While treatments such as antibodies and cell therapies are growing, Excelsior CEO Michael Foley said around 60% of new U.S. FDA-approved drugs are small molecules.
However, discovering and making small molecules is slow and costly, often taking more than a decade and billions of dollars as each molecule requires a custom synthesis process.
Excelsior’s “smart bloccs” approach, which one of its lead investors described as a new modular language, can help AI “better predict how to create, optimize new therapies”.
Jim Flynn, managing partner at Deerfield, said a typical cycle of four months or more, often involving work split across the United States, Asia and multiple contractors, could be reduced to about two weeks in a single automated facility.
The same process can then be scaled up for manufacturing, potentially saving another year to 18 months before clinical trials begin, Flynn added.
The New York-based firm, spun out of investment firm Deerfield, expects to demonstrate its full platform working within 12 months and apply it to at least one drug discovery program.
The funding round also received backing from Eli Lilly, Cornucopian Capital, Illinois Ventures and academic institutions such as MIT and Princeton University.
(Reporting by Kamal Choudhury in Bengaluru; Editing by Vijay Kishore)
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