Ex-J&J CEO Alex Gorsky joins $60M funding for Causaly's speed-reading drug discovery AI

Often, when a pharmaceutical company or biotech researcher wants to develop a new drug for a specific condition, they have to sift through mountains of published clinical data to identify a promising target, diagnostic biomarkers associated with the condition and a compound that’ll be able to reach and interact with the target. The process can take weeks, months or even years—unless Causaly has anything to say about it.

The U.K.-based company is developing an artificial intelligence-based platform that plows through scientific literature at superhuman speeds, compiling its findings into “knowledge graphs” that pinpoint genes, proteins and other biological quirks linked to specified conditions and the mechanisms of action that have the best chance of treating them.

Causaly already works with a dozen of the top 20 pharma companies—plus researchers from the FDA, the National Institutes of Health and more—and recently tripled its revenues, and it’s still raking in support. The company announced Thursday that it has closed a $60 million funding round that’ll go toward the continued development of its platform and the expansion of its partnerships.

ICONIQ Growth led the series B financing, which was also joined by individuals including former Johnson & Johnson CEO Alex Gorsky and Datadog CEO Olivier Pomel, as well as VC firms Index Ventures, Marathon Venture Capital, EBRD, Pentech Ventures and Visionaries Club.

“Recent advances in AI open completely new possibilities, and there is a great need for transparent AI systems that science leaders can trust,” Yiannis Kiachopoulos, Causaly’s co-founder and CEO, said in the announcement. “Knowledge is the lifeblood of research organizations, and we are committed to our mission to make it discoverable, working with our customers to make sense of their scientific data and apply insights to enable evidence-driven decisions.”

In total, Causaly has now raised more than $90 million since its 2018 founding.

After using Causaly’s AI to identify potential drug targets, biomarkers and pharmaceutical approaches, biopharma developers can continue using the platform to design experiments.

Meanwhile, researchers like those at the NIH’s National Institute of Environmental Health Sciences can query the AI to scour published research for connections between health conditions and the environment or other external factors. Regulators at the FDA may task the technology with helping to determine a new drug’s safety profile, compiling a list of adverse reactions and side effects linked to specific compounds.

Altogether, according to Causaly, its technology can help boost its partners’ productivity tenfold, enable the discovery of novel new drugs and improve the overall success rate of the drug development process.

In Thursday’s announcement, Carlos Gonzalez-Cadenas, a partner at Index Ventures, called Causaly’s technology “one of the clearest real-life applications of AI today.”