Former Healthcare Investor Raises $27.5 Million for AI Drug Development Fund
Sahir Raoof has raised $27.5 million for his first solo venture fund, Proximal Ventures, according to TechCrunch, which reported the close on November 10, 2026. Raoof, a former investor at SignalFire, is backing startups that apply AI to drug development, including companies building tools, infrastructure and services that support the process.
Before founding Proximal, Raoof spent two years as a principal at SignalFire. Earlier in his career he led business development at Iterative Health and oversaw partnerships at Flatiron Health, two organizations that sit where healthcare data meets clinical operations, meaning the day-to-day running of clinical trials and patient care. That operating background is the thread connecting the fund's thesis to its selection criteria.
The fund plans to invest in pre-seed and seed-stage companies, the earliest rounds a startup raises, with checks ranging from $500,000 to $1.5 million. Those amounts are small next to later-stage rounds in therapeutics. They position Proximal as an early participant that will depend on follow-on capital from other investors as companies move toward clinical milestones, such as the points at which a candidate drug enters or completes testing in humans.
Proximal has already backed six startups. One of them is ChronicleBio, co-founded by former OpenAI executive Fidji Simo. ChronicleBio uses AI to analyze biological and medical data in order to understand chronic diseases and identify potential treatments.
The fund's backers include SignalFire, Kleiner Perkins, Bertelsmann Healthcare Investments, Dimension Capital co-founders Nan Li and Zavain Dar, and Amy Abernethy. Abernethy is co-founder of Highlander Health and a former principal deputy commissioner of the FDA. Her presence gives the fund a direct line into regulatory thinking at a time when AI-derived candidates face the same evidentiary standards as any other compound.
In my view, the composition of that backer list says more about the fund's intended role than the headline figure does. A pre-seed and seed fund in this category succeeds or fails on whether its early bets reach the point where regulators and pharmaceutical partners take them seriously. That stage is governed by trial design, data provenance (where the data came from and whether it can be traced) and validation, not by model benchmarks. Having a former FDA official and a healthcare-focused strategic investor among the backers suggests the partners are betting on that gap being bridged.
The broader context here is a crowded field. Many funds and corporate investors now pursue AI-enabled drug discovery, and a number of startups in the space are competing for the same early capital and the same pharmaceutical collaborations. What distinguishes a debut fund in this environment is less the size of the pool than the quality of its judgment about which technical claims will survive contact with biology.
The opportunity, if the thesis holds, is practical. Tooling and data infrastructure that shorten the time between a hypothesis and a testable candidate could change how small teams spend their runway, the months of funding they have before they must raise again. A fund focused on that layer gives founders an investor who understands both software and wet-lab timelines. Whether Proximal's first six bets bear that out will become visible only over the coming years of clinical and commercial progress.
