20nWinter 2015Inactive☆Watch⊞Compare

20n is one of 233 Biotech companies tracked from San Francisco, CA, USA, on record since 2014. 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”

Using AI to predict biochemistry for manufacturing and therapeutics

The next decade is going to see a biotech revolution fueled by three technologies: ability to read DNA (sequencing), ability to write DNA (synthesis), and computational systems that predict what DNA to read and write. With sequencing and synthesis being mainstream now [1], 20n provides the computational systems that predict DNA design for novel industrial biotech and health applications. At 20n, we are taking a fresh look at turning biological data into information. We approach it as a big data learning problem, and bring to bear techniques from machine learning, distributed systems, AI planning, program synthesis, data mining, and natural language processing. With the support of DARPA [2], we are building a team of computer scientists, and bioengineers to look at biology in fundamentally new ways. Our current customers include industrial biotech firms that are leading the charge in transitioning us from traditional unsustainable means of manufacturing to sustainable biological processes leading to advanced fuels, materials, therapeutics, and flavors and fragrances. 20n’s technology helps them enter markets previously thought inaccessible for biology. [1] Sequencing DNA costs $4k/genome (http://www.genome.gov/sequencingcosts/) and is expected to go down to $1k/genome. Synthesizing DNA is at 20cents/bp, and is expected to go down to 0.1cents/bp. [2] DARPA in the past supported work that led to the internet, stealth planes, GPS, and even Douglas Engelbart’s mother-of-all-demos.

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.

20n 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 20n sits in the wider market — its sector, location and stage cohorts, each with their own leaderboards and capital-flow timelines.

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