Korea's Hits raises $13M Series B to launch AI co-scientist for drug discovery
What's the deal? South Korean drug discovery startup HitsDealroom has a profile for this one. Try Dealroom → has raised US$15.3M in a Series B round. Premier PartnersDealroom has a profile for this one. Try Dealroom →, Korea Investment PartnersDealroom has a profile for this one. Try Dealroom →, and Yuanta InvestmentDealroom has a profile for this one. Try Dealroom → took part.
What's the endgame? Founded in 2020 by KAISTDealroom has a profile for this one. Try Dealroom → chemistry professor Kim U-yeon, Hits builds AI tools for finding and designing new drug candidates. Its flagship platform is HyperLab, and it recently commercialised K-Fold, a bio AI model developed with KAIST researchers. The new capital will advance its technology and expand sales to pharmaceutical and bio firms.
What's the product? Hits will launch an "AI Co-Scientist" in November that bundles specialised models — for protein structure prediction, toxicity analysis, and molecular design — into a single research flow. It assigns tasks such as literature search and data analysis to multiple AI agents. The company plans to link the system to automated lab equipment and deliver results by 2027.
Why now? New drug research runs through several stages, from target selection to hypothesis revision. Hits says its edge is a team that spans both biology and AI: of 36 employees, 19 hold master's or PhD degrees.
What could go wrong? In research, the basis for an answer matters as much as the answer. "In general chat, incorrect facts might be glossed over, but in research they can be fatal," said Hits researcher Jeong Won-ho. The company cross-checks hypotheses against papers, biological databases, and knowledge graphs to guard against errors.
Hits raised a cumulative US$8.64M through a 2024 Series A bridge, bringing its total to US$24M with this round.
The signal: The round sits in the top half of comparable deals by size, a modest but notable raise in a field racing toward autonomous research. Hits is betting that domain-specific AI agents, not general-purpose models, will move drug discovery from software into the lab.
Read more: biz.chosun.com
Image credit: Enzymlogic
