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Network Bio

United StatesBiology data and toolsPalo Alto, California, United StatesPrivate

Website · network.bio ↗

Links academic medical centres' biobanks under shared sample and data standards and trains disease models on patient tissue, paired blood, molecular data and clinical outcomes; its first model, Exai-1, reads cell-free RNA in blood.

Disclosed total$50M
Rounds on record1
Latest round$50MRound (unnamed) · 2026-08-19
Last stated valuationNone stated
Investors named6
Research on record1highest level 3 · Checked against existing evidence

Money and evidence

Moneyeach round in US dollars; ≈ converted at its date2026$50MEvidencelevel of each research entry12345
Closed roundResearch entry, at its level

Latest round, Round (unnamed), 2026-08-19: the record then held 1 research entry, highest level 3. The first research entry is dated 2025-12-10; the highest level so far is 3 (Checked against existing evidence).

Rounds and research, on one timeline

  1. 2026-08-19Round (unnamed)
    Round

    $50M

    For: expand its life sciences platform for training AI models on multimodal patient data

    Models and platformData generation

    The launch financing; the release names no lead or stage. Read as reproduced by SynBioBeta and Pulse 2.0, since Business Wire's page refuses automated readers; the company's own site lists the release. Headquarters is as AI Weekly reports from the WSJ's story.

    Section 32Thiel BioFounders FundBreyer CapitalBlue Venture FundJSL Health Capital

    On the deal: Mike Pellini (Managing Partner; Chairman of Network Bio's board; spoke for the firm, Section 32, joins the board); Morgan Cheatham (Partner; spoke for the firm, Breyer Capital)

    By this date the record held 1 research entry, highest level 3

    Announced by the company · synbiobeta.com ↗On the timeline →

  2. 2025-12-10
    Research

    Level 3 · Checked against existing evidence

    Exai Bio's Exai-1, a model trained on small RNA fragments in blood, makes cancer classifiers work from fewer samples

    A blood test for a rare cancer usually fails for lack of patient samples to train on. A model pretrained on many people's blood that lets a classifier learn from a few dozen cases is what would make such tests buildable. The same representation also let a classifier trained on plasma keep working on serum, where the raw-feature classifier dropped from 0.74 to 0.56. Network Bio, which Goodarzi co-founded, now presents Exai-1 as its first model.

    Timeline entry →doi.org ↗

Research entries are the timeline's graded entries that name this company. A level grades one claim, not the company, and a blank can mean the record has not caught up rather than that nothing was published.

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Its investors also backed

Other companies on this page whose rounds name the same investor.