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Xaira Therapeutics

United StatesDrug discoverySan Francisco Bay Area, United StatesPrivate

Builds AI models for protein and antibody design and for cell biology, trained partly on its own large perturbation datasets, and runs its own drug programs.

Disclosed total-
Rounds on record1
Latest roundmore than $1 billion in committed capitalRound (unnamed) · 2024-04-23
Last stated valuationNone stated
Investors named13
Research on record5highest level 4 · Tested in the physical world

Money and evidence

Moneyeach round in US dollars; ≈ converted at its date202420252026$1BEvidencelevel of each research entry12345
Closed roundResearch entry, at its level

Latest round, Round (unnamed), 2024-04-23: the record then held no research entry for the company. The first research entry is dated 2025-06-16; the highest level so far is 4 (Tested in the physical world).

Rounds and research, on one timeline

  1. 2026-10-23
    Research

    Level 4 · Tested in the physical world

    Xaira built a camera-guided arm for instruments made for human hands, and over seven days it loaded 18 plates into an HPLC, 80% more than its model of weekday hours

    Protein-design groups can now make thousands of candidates a week, and the measurement that tells them which ones worked is the step that waits for a person to open a door. Xaira's answer is vision on the arm rather than taught positions, which is what lets one arm move between instruments that were never meant to be automated, and it sidesteps the instrument maker's paid interface. The company says adapting the arm to another instrument now takes weeks rather than months.

  2. 2026-10-21
    Research

    Level 4 · Tested in the physical world

    Xaira's X-Scientist agents picked genes to perturb in liver cells, and 7.1% of its picks reversed the TGF-beta signal against 6.9% for its own scientists and 0.9% at random

    TGF-beta drives scarring in chronic liver disease, and which genes to perturb against it is the kind of choice a biologist spends a morning on. The measurement here is of the model's picks, not of the model's own score: every nomination was made, perturbed and read out in cells. Three of its hits outside the known TGF-beta pathway beat the median of the ones inside it, and none were in the scientists' list, which is what the loop is for, since a list of known pathway genes is one a scientist already has.

  3. 2026-10-02
    Research

    Level 3 · Checked against existing evidence

    Xaira says X-Design Vega took its XA-1 nanobody from DNA synthesis to a lead in 7 weeks, and made an antagonist for a GPCR that library screening and llama immunisation failed on

    It tests two questions for de novo design: can it shorten hit-to-lead (XA-1 reached a selective, developable lead), and can it open targets where other methods failed (XA-4 gave a working antagonist, not just a binder). Limits: targets undisclosed, so outsiders cannot judge how hard they are; in-house assays, no independent replication; no paper, so method and benchmark go unreviewed; XA-1's epitope was chosen in advance, so it shows design and optimisation, not finding a binding site.

  4. 2026-03-18
    Research

    Level 2 · Computed

    Xaira's X-Cell, trained on 25.6 million perturbed cells, beats earlier virtual-cell models up to five-fold on its own held-out genes, but its test loss barely improves with scale

    A virtual cell is a bet that a model can stand in for some perturbation experiments, and this tests it on genes and cell types it never saw, not only new cells. The five-fold lead is on Xaira's own held-out set, the baselines were not retrained at its scale, and the flat test loss says more parameters alone will not buy accuracy: the authors say data is the limit. No prediction was tested in a new experiment. The 55M model is released under a non-commercial licence; the 4.9B one is not.

  5. 2025-06-16
    Research

    Level 1 · Exists

    Xaira releases X-Atlas/Orion, a genome-wide Perturb-seq atlas of eight million cells, with the platform that made it

    Xaira makes its own perturbation data and shares part of it. A dataset and method paper: no drug target, no working model shown.

  6. 2024-04-23Round (unnamed)
    Round

    more than $1 billion in committed capital

    For: build the AI research, data generation and drug development platform

    Models and platformData generation

    Launch financing described as committed capital, not a named series; incubated by ARCH and Foresite Labs.

    Co-lead · ARCH Venture Partners ✓Co-lead · Foresite Capital ✓F-Prime ✓NEA ✓Sequoia Capital ✓Lux CapitalLightspeed Venture Partners ✓Menlo Ventures ✓Two Sigma Ventures ✓Parker Institute for Cancer ImmunotherapyByers CapitalRsquaredSV Angel

    On the deal: Robert Nelsen (Managing Director and Co-founder, ARCH Venture Partners, joins the board); Scott Gottlieb (Partner, NEA, joins the board); Stephen Knight (President & Managing Partner, F-Prime, joins the board); Vikram Bajaj (Managing Director, Foresite Capital, joins the board)

    The investor's own page says · Lightspeed Venture Partners: 2024, Seed

    The investor's own page says · Sequoia Capital: 2024

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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On the investors' own sites

Investors that name this company on their own site, in a portfolio or their own announcement. A ✓ in a round marks the same investor.

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