Phil Rivers Tech Raises Eight-Figure Series A1 to Advance AI4S-Driven Drug Innovation

Phil Rivers Tech Raises Eight-Figure Series A1 to Advance AI4S-Driven Drug Innovation

Published:December 16, 2025
Reading Time:2 min read

Want to read in a language you're more familiar with?

Phil Rivers Tech has raised an eight-figure Series A1 round to accelerate AI4S-powered drug discovery and push multiple innovative therapies into clinical development.

December 16, 2025 — Beijing-based Phil Rivers Tech, an AI for Science (AI4S) company, has completed an eight-figure Series A1 financing round. The round was led by Guoke Investment, with participation from Zeyuan Fund and Ruidi Wisdom Medicine. The new capital will be used to advance core drug pipelines, expand global intellectual property portfolios, and upgrade the company’s computational medicine platform.

Founded in 2015 and incubated at the Institute of Computing Technology, Chinese Academy of Sciences, Phil Rivers Tech operates on an “AI4S + disease” model, distinguishing itself from traditional “AI + molecule” approaches. Its proprietary computational medicine platform leverages a multi-agent (Agents) technology framework to enable three major breakthroughs: discovery of novel drug targets, identification of new mechanisms for known targets, and drug repurposing.

A key innovation is the company’s “digital twin of biological functions” technology, which enables simulated “virtual clinical trials.” In collaboration with Beijing Cancer Hospital, the platform’s drug response predictions for eight patients matched actual clinical outcomes with 100% accuracy.

Currently, the company’s first-in-class pancreatic cancer drug candidate PR00012 has entered Phase I clinical trials, generating more than 200 high-value insights into potential therapeutic targets. In parallel, newly identified indications for CDK4/6 inhibitors are also advancing into clinical-stage development.

Looking ahead, Phil Rivers Tech plans to deepen its “computational medicine + industry collaboration” strategy, aiming to transform pharmaceutical R&D from an experience-driven, artisanal process into a scalable, engineering-based production model.