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DaltonTx launches AI antibody platform that folds millions of structures per hour

DaltonTx launches AI antibody platform that folds millions of structures per hour

New Capabilities

London startup's Dalton platform folds 87,000 antibody structures an hour, and a Gates Foundation grant now extends the same decision engine to tuberculosis

October 1st, 2026: Dalton platform launches with antibody discovery capabilities

Overview

Updated Oct 20

On October 1, DaltonTx launched Dalton, a chat-driven platform that folds 87,000 antibody structures per hour. The London company says it folded the 2.6 million paired sequences in the Observed Antibody Space in hours.

DaltonTx has since won a Gates Foundation grant to apply the same decision engine to tuberculosis drug discovery with nonprofit Ersilia. The company says Dalton also handles multispecific antibodies, antibody-drug conjugates (antibodies carrying a drug payload) and single-domain antibodies. Sygnature Discovery is testing whether the platform would have reached a cancer candidate with fewer compounds built.

Why it matters

If shape-based screening holds up, labs can spend less time building antibodies that fail and more on ones with a real shot.

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Key Indicators

87,000
Antibody structures folded per hour
Throughput achieved when Dalton folded the full 2.6 million paired OAS antibody space.
2.6 million
Paired antibody sequences folded
Entire Observed Antibody Space dataset folded in hours, not days or weeks.
2
Customers announced
Sygnature Discovery signed at the October launch; Bonito Biosciences announced its collaboration in May.
1
Gates Foundation grant
Awarded to apply Dalton to tuberculosis drug discovery with nonprofit Ersilia.

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People Involved

Garry Pairaudeau
Garry Pairaudeau
Co-founder and chief executive officer, DaltonTx
Leading DaltonTx through platform launch
 Charlotte Deane
Charlotte Deane
Co-founder and chief AI officer, DaltonTx
Leads AI model development; senior author of FlashABB
 Anthony Bradley
Anthony Bradley
Co-founder and chief scientific officer, DaltonTx
Leads scientific strategy and antibody structure work

Organizations Involved

DaltonTx
DaltonTx
AI drug discovery company
Launched Dalton in October 2026 and won a Gates Foundation grant for tuberculosis drug discovery

London-based startup building AI decision engines for drug discovery in both biologics and small molecules.
Sygnature Discovery
Sygnature Discovery
Contract research organization
Launch customer testing Dalton in oncology program

UK contract research organization integrating Dalton into its computational and medicinal chemistry toolkit.
Bonito Biosciences
Bonito Biosciences
Biotechnology company
Customer using Dalton to design delivery ligands for CNS therapies

Oligotherapeutic drug developer using Dalton to design precision delivery ligands for central nervous system targets

Timeline

2025 October 2026

4 events Latest: October 1st, 2026 · 1 month ago
Tap a bar to jump to that date

  1. Dalton platform launches with antibody discovery capabilities

    Latest Launch

    DaltonTx launches integrated antibody design, structure prediction and validation workflow; folds 2.6 million paired OAS sequences at 87,000 structures per hour. Sygnature Discovery and Bonito Biosciences announced as customers.

  2. DaltonTx wins Gates Foundation grant for tuberculosis drug discovery

    Funding

    DaltonTx won a Gates Foundation grant to apply its Dalton decision engine to tuberculosis drug discovery. It will work with nonprofit Ersilia, which will share validated models and workflows through its Model Hub.

  3. FlashABB antibody structure model announced

    Product

    University of Oxford-developed FlashABB structure prediction model announced, generating hundreds of thousands of structures per hour.

  4. DaltonTx emerges from stealth

    Founding

    Company launches with mission to build adaptive AI drug discovery platforms, led by Garry Pairaudeau and Charlotte Deane.

Scenarios

1

Dalton's structural screening becomes standard practice in antibody discovery

Possible Resolves by Oct 1, 2027

Discussed by: DaltonTx leadership; Sygnature Discovery collaboration

If the Sygnature retrospective evaluation shows Dalton could have reached candidate selection with meaningfully fewer compounds synthesized, other CROs and pharma companies may adopt the platform. DaltonTx's position as a neutral tool provider—not a drug developer—would help it integrate into existing workflows rather than compete with them. The company's claim that data and models stay compartmentalized per program addresses a real industry concern about proprietary data use in AI environments.

2

Dalton remains a niche tool adopted by a handful of early customers

Possible Resolves by Oct 1, 2027

Discussed by: Pharmaphorum market analysis

The AI drug discovery field is crowded. Rivals like Recursion Pharma, Insilico Medicine and Schrödinger, plus tech giants such as NVIDIA and Alphabet's Isomorphic Labs, all offer competing toolkits. Dalton's differentiation rests on its decision-logging interface and structural-throughput claims. If early results are mixed or customers keep results private, the platform may not gain enough traction to move beyond its initial users.

3

FlashABB and structural convergence become an academic standard

Possible Resolves by Jan 1, 2028

Discussed by: University of Oxford researchers; structural biology community

FlashABB's open integration into Dalton could also push structural convergence—comparing candidates by 3D paratope shape rather than sequence identity—into wider academic use. Charlotte Deane's lab remains connected to Oxford and continues evaluating emerging antibody modeling approaches. If the method's results get published in peer-reviewed venues and adopted by other groups, Dalton could benefit from academic validation even if commercial adoption lags.

4

Shared industry developability models squeeze Dalton's differentiation

Possible Resolves by Q1 2027

Discussed by: Ginkgo Datapoints, Apheris, AbbVie, argenx, Lundbeck, Takeda via Drug Discovery News

On September 29, Ginkgo Datapoints and Apheris announced the Antibody Developability Consortium, with AbbVie, argenx, Lundbeck and Takeda as founding members. Members contribute antibody sequences; Ginkgo runs high-throughput wet-lab characterization and trains a foundation developability model, with the first dataset expected by early 2027. If big pharma comes to trust a pooled, consortium-trained model for spotting risky antibodies early, Dalton's developability screening competes with a shared industry resource.

Historical Context

2 moments from history that rhyme with this story — and how they unfolded.

November-December 2020

AlphaFold2 (2020)

DeepMind's AlphaFold2 won the CASP14 protein structure prediction competition, accurately predicting protein 3D structures from amino acid sequences for the first time at scale. The system's accuracy was a leap over prior methods, which had plateaued for decades.

Then

The protein structure prediction field was transformed; DeepMind released the AlphaFold Protein Structure Database covering nearly all known proteins.

Now

Structure prediction became a routine computational step in biology, and a generation of faster, more specialized models followed, including antibody-specific ones like FlashABB.

Why this matters now

Dalton's speed advantage—87,000 structures per hour for antibodies specifically—extends the AlphaFold trajectory from predicting single proteins to screening entire repertoires in hours, making shape-based selection practical for the first time.

January 2020

Exscientia's AI-designed drug enters trials (2020)

Exscientia and Sumitomo Dainippon Pharma announced the first AI-designed drug candidate to enter human clinical trials, an obsessive-compulsive disorder treatment called DSP-1181. Exscientia's systems designed the molecule after roughly 12 months of work, a fraction of the typical 4-5 years.

Then

The announcement validated that AI could meaningfully accelerate the design phase of drug discovery, attracting investment and attention to the field.

Now

Exscientia later merged with Recursion Pharmaceuticals in 2024. Garry Pairaudeau, DaltonTx's co-founder and CEO, was Exscientia's CTO before the merger.

Why this matters now

DaltonTx is the next step in the same thesis Pairaudeau pursued at Exscientia: instead of just generating candidates faster, Dalton tries to make the decision process itself faster and more transparent.

Sources

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GlobeNewswire Pharmaphorum Sygnature Discovery DaltonTx (LinkedIn) AI Future Front Dealroom Biopharma Boardroom AllSci Drug Discovery News DaltonTx BioProcess International Superpower Daily DaltonTx Biopharma Boardroom DaltonTx Pharmaphorum