Proximal Ventures Secures $27.5 Million to Back AI‑Powered Drug Discovery Startups

Proximal Ventures revealed that its first fund has been closed, raising $27.5 million to back early‑stage firms employing artificial intelligence to speed up pharmaceutical research and development.

The fund is headed by Sahir Raoof, formerly an investor at SignalFire, a venture firm focused on technology. Raoof’s skill in identifying fast‑growing tech startups shapes the firm’s plan to support entrepreneurs combining machine‑learning with biology to compress the drug‑discovery timeline.

AI‑driven drug development has become a focal point for investors in recent years, as breakthroughs in computational chemistry, protein‑folding prediction and large‑scale data analysis promise to cut the cost and risk of bringing new medicines to market. Proximal Ventures aims to fill a niche by offering not only capital but also sector expertise to help founders navigate the regulatory and scientific hurdles unique to the biotech sector.

Analysts note that the $27.5 million size of the debut fund signals both caution and optimism. While the capital pool is modest compared to larger biotech funds, it aligns with the early‑stage nature of many AI‑driven drug platforms, which often require seed‑level financing to prove core algorithms before moving into costly pre‑clinical studies.

Raoof emphasized that the firm will prioritize startups that demonstrate a clear path to integrating AI models with experimental validation. “The most compelling opportunities are those where computational insight directly informs laboratory work, creating a feedback loop that can dramatically speed up candidate selection,” he said in a briefing.

Looking ahead, Proximal Ventures plans to deploy capital over the next 12 to 18 months, targeting a diversified portfolio that spans therapeutic areas such as oncology, rare diseases and infectious diseases. The firm’s launch adds to a growing ecosystem of investors betting on AI to reshape drug discovery, and its success could signal broader confidence in the convergence of data science and pharmaceutical innovation.