For companies looking to find viable therapies, the average timeline from initial discovery to human trials can stretch over a decade, with billions spent and no guarantee of success. Synfini, a Menlo Park-based startup spun out of SRI International, believes it can shorten that timeline with a tightly integrated AI and automation platform that reduces molecular design cycles from months to days.
Synfini just announced an $8.9 million expansion round led by JSL Health Capital, bringing its total raised to $53 million. The new funding will help the company scale operations, expand its engineering and scientific teams, and pursue deeper collaborations in therapeutic areas like precision oncology and GPCR-targeted drugs.
“We’re building the next generation of drug discovery infrastructure,” CEO Doug Donzelli said in a statement announcing the recent funding.
From SRI Lab Project to Standalone Company
Synfini’s origins lie in a multi-year, $40 million research initiative inside SRI International, the Silicon Valley nonprofit research institution behind historic innovations like ARPANET and Siri. With funding in part from DARPA, SRI scientists developed a suite of tools blending neuro-symbolic AI, high-throughput chemistry systems, and flow chemistry hardware to accelerate molecular synthesis.
That suite became the basis for Synfini’s product: the AI Cloud Foundry, an integrated platform that combines physical and virtual chemistry with AI-driven automation. In 2023, Synfini was formally spun out of SRI, backed by venture investors and licensing the institute’s proprietary chemistry dataset and software stack.
The founding team includes Donzelli, a veteran of software and medical device companies; VP of Finance Elizabeth Miyagi, who brings decades of operational experience; and SRI scientists Peter Madrid, Ph.D., and Nathan Collins, Ph.D., who helped architect the technology as part of SRI’s biosciences division.
A Full-Stack Approach to Faster Molecule Design
Traditional drug discovery involves a series of disjointed steps: identifying biological targets, designing molecules to hit those targets, planning chemical syntheses, running experiments, and iterating through failed leads. Each stage can take weeks or months, and the handoffs between them often introduce delays and errors.
Synfini’s pitch is that integrating all those steps within one platform drastically compresses the discovery timeline. The AI Cloud Foundry orchestrates computational molecular design, synthetic route planning, and robotic synthesis and testing in a continuous feedback loop. Its neuro-symbolic AI engine incorporates both statistical models and symbolic reasoning, enabling chemists to generate, evaluate, and optimize new compounds more efficiently.
That combination has strategic appeal for biopharma customers. Synfini says its platform has been adopted by biotech startups and large pharmaceutical companies alike, with early collaborations including Janssen, Sanofi, and cancer-focused biotech O2nix Bio. The company’s work with O2nix targets FTSJ1, an RNA-modifying enzyme linked to cancer metastasis. In this partnership, Synfini’s system is being used to rapidly design and test novel compounds based on O2nix’s biological insights.
By integrating synthetic feasibility into the early design phase, Synfini helps partners avoid dead-end molecules and pivot more effectively as new biological data emerges: a key advantage in complex or fast-moving research areas like oncology.
Long-term Success Depends on Continued ROI
Investors point to Synfini’s maturity relative to its age. Lekan Wang, Managing Partner at lead investor JSL Health, said the company is “rare” in that it emerged “fully formed” thanks to its years of development inside SRI.
“Project planning, property prediction, reaction routes and synthesis are all included and fully integrated within Synfini’s chemistry operating system,” Wang said. “This promises to dramatically increase drug pipeline velocity from hit to human trials.”
The company is now focused on scaling its vision of making the process of turning molecular ideas into synthesized, testable compounds as efficient and programmable as possible.
With new funding, it plans to grow its headcount, expand automated lab infrastructure, and deepen partnerships with biopharma firms and academic labs. Precision areas like GPCR-targeted therapeutics and metastasis-related oncology remain near-term priorities, but Synfini’s modular platform could theoretically support a broader range of chemical applications, from agrochemicals to rare disease treatments. Synfini is betting that full-stack control of both virtual and physical chemistry gives it a lasting edge
