Criteria Bio Ventures

Criteria Bio maintains a dedicated computational biology unit that engages directly with academic principal investigators at major research institutes — particularly in Catalonia and the Mid-Atlantic US — often structuring company creation before a formal Series A process begins. This internal unit evaluates algorithm-driven drug discovery platforms in-house, giving the firm early technical visibility into labs that competing firms typically encounter only after a startup has already incorporated. The firm's Barcelona and Philadelphia presences are positioned specifically for proximity to these academic clusters.

Criteria Bio concentrates on clinical-stage biotech companies, primarily at Phase I and Phase II, writing initial checks between $15 million and $30 million with reserves for follow-on through Series C. The firm explicitly avoids preclinical science risk, requiring validated biomarkers and human data before committing capital. It does not pursue late-stage private equity or pre-IPO crossover rounds.

The firm invests almost exclusively through direct equity financings, often serving as a lead or co-lead investor. Public record does not indicate that Criteria Bio operates a fund-of-funds program or makes LP commitments to other venture firms. Its co-investment syndicates have included Fidelity Biosciences, OrbiMed, and Deerfield Management, per the firm's official communications.

Criteria Bio has not publicly disclosed its full partnership roster or named a single chief investment officer. What is known, per the firm's official communications, is that its investment committee operates alongside an internal computational biology unit that holds veto authority over every portfolio decision. This means scientific leadership inside the firm can block a deal regardless of the investment team's conviction.

The firm targets oncology, neurodegenerative disease, and rare metabolic disorders — three areas where computational modeling has demonstrated the ability to reduce late-stage clinical failure rates. Criteria Bio selects these verticals specifically because their biological complexity has historically made drug development expensive and failure-prone, creating room for algorithmic approaches to produce an edge over traditional discovery methods.