10x ScienceWinter 2026Active☆Watch⊞Compare

10x Science is one of 233 Biotech companies tracked from San Francisco, CA, USA, on record since 2026. By capital raised it ranks mid-pack (ahead of 67% of sector peers), and mid-pack by modeled valuation est..

Ranking is computed against this company's own sector cohort — reported capital is fact; valuation tiers are modeled.

AI analyst read est. — model-extracted from this company's public description, not a verified fact. 30%

operates a technology-led product inferred from public copy

Grounded in: “You are a venture analyst”

The AI-native platform for next-generation protein characterization.

10x Science develops frontier AI models with deep memory to redefine how scientists understand and engineer biology across the life sciences, starting with drug development. AI-powered drug discovery is flooding the pipeline with new candidates faster than ever. But before any of them can advance to the clinic, scientists must deeply characterize the protein therapeutic to understand whether it will work. Today, that process takes months of manual, error-prone analysis that cannot keep pace with discovery. Our AI-native platform automates it, giving drug developers the confidence to advance the right candidates and stop the wrong ones early. We have strong commercial traction with enterprise pharma customers. Our founding team built the field of next-generation protein characterization out of Carolyn Bertozzi's Nobel laureate lab at Stanford. Collectively, we have 18+ years of collective domain expertise, 47+ scientific publications, and a 2x YC Founder. We move at the highest velocity and are positioned to lead the next generation of modern AI development in the life sciences.

As reported in public records reported — not modeled.

Solid bars are reported offering amounts reported; hatched bars are the modeled post-money valuation est. — both on one shared scale so you can read raise-vs-worth at each round directly. Use the toggles to overlay data labels and the niche-peer / market average value lines.

No round amounts on record to chart.

No staged rounds to sequence.

Round size and date are reported; the stage label is inferred from round size. Valuation is modeled from stage benchmarks. Directional, not a quoted figure.

Not enough modeled valuation points to chart a trajectory.

Benchmarked against 233 companies in Biotech. Each bar is a median (the middle company, not an average — outliers don't skew it). Two yardsticks: real money raised (reported on Form D) and modeled value (our estimate est.). These are whole-sector medians across all stages, except the per-stage row.

Raised more than 67% of sector peers (real $). Modeled value above 67% of peers (estimate).

Stage is inferred from round size est., not reported on the filing — a round's dollar size maps to a bucket: Pre-Seed <$1.0M · Seed $1.0M–$4.0M · Series A $4.0M–$15M · Series B $15M–$40M · Series C $40M–$100M · Series D+ $100M–$400M · Growth/Late >$400M.

Predictive signals are modeled est. from this company's own cadence and step-up, plus sector benchmarks — directional, not advice. Peer set and a CSV export live in your analyst workspace.

10x Science is an official record sourced from the U.S. Securities and Exchange Commission (SEC). U.S. data is aggregated from SEC Form D filings.

Nearest neighbours across the whole database — matched on sector, stage and capital scale, and on shared operators (officers or directors named at both companies in public filings). A discovery shortlist, not a valuation cohort — verify before acting, the same way modeled figures are directional.

Matched by meaning, not labels — a local language model reads each company's name, sector and description and ranks the closest in that learned space. This catches look-alikes that cross sector boundaries; the structured list above explains its matches, this one trusts the text. Directional, like every modeled signal here.

See where 10x Science sits in the wider market — its sector, location and stage cohorts, each with their own leaderboards and capital-flow timelines.

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