Generate:Biomedicines vs Profluent (2026)
Both design proteins with generative models and test them in their own labs. Generate:Biomedicines runs a loop of generating, building, measuring and learning, with more than 42,000 proteins made and tested, and its Chroma model generates structures and sequences conditioned on properties such as binding. It develops its own therapeutics and is clinical stage. Profluent builds on its ProGen models, and its OpenCRISPR-1 gene editor, published in Nature in 2025, matched SpCas9's on target editing while cutting off target editing from 6.1 to 0.32 percent. It licenses OpenCRISPR-1 free. Generate is a drug developer; Profluent's published output is a gene editor that others can license.
- A generate, build, measure and learn loop with more than 42,000 proteins generated, built and tested.
- Chroma, a generative model for novel protein structures and sequences conditioned on desired properties.
- A clinical stage pipeline of protein therapeutics designed on the platform.
- A published, measured result: OpenCRISPR-1's editing and off target rates against SpCas9 (Nature, 2025).
- An in house wet lab that tests what the models generate.
- OpenCRISPR-1 available to license free of charge.
This comparison is published by AI Health Index, an independent research platform that compares healthcare AI vendors objectively. Generate:Biomedicines and Profluent are each graded against the same capability taxonomy, from each vendor's own public materials and the regulatory record, under the AI Health Index verification standard. No vendor pays for placement, and no vendor has reviewed this page. How this evidence is graded
Plain facts
| Fact | Generate:Biomedicines | Profluent |
|---|---|---|
| Primary category | Drug Discovery AI | Drug Discovery AI |
| Founded | 2018 | 2022 |
| Headquarters | Somerville, MA | Emeryville, CA |
| Website | generatebiomedicines.com | profluent.bio |
Side by Side
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Product updates
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Generate:Biomedicines
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Model / architecture
Generate:Biomedicines described an agent harness its team built with Claude Code to design CAR T cell signaling domains, combining LLM reasoning with computational tools while scientists steered and inspected each design.
Source
Each vendor in one paragraph
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Clinical stage generative biology company in Somerville, Massachusetts (Nasdaq: GENB), founded in 2018 by Flagship Pioneering, that designs protein therapeutics with machine learning rather than discovering them from natural scaffolds.
Source: AI Health Index, September 2026
Protein design company in Emeryville, California, built on the ProGen family of protein language models, which grew out of research first showing that large language models can generate functional proteins across diverse families, published in Nature Biotechnology in 2023. The company pairs its generative models with task specific ones (ProseLM for structure conditioned design, Protein2PAM for the DNA motifs a gene editor recognizes) and an in house wet lab that tests what the models write.
Source: AI Health Index, September 2026
Questions buyers ask
How do Generate:Biomedicines and Profluent handle patient data?
For Generate:Biomedicines, the discovery workflow runs on protein structures, sequences and assay data from the company's own laboratories; whether a collaborator's sequences or assay results train models that serve other programs is not stated.
With Profluent, the privacy policy (last updated 1 January 2025) covers the website, its subdomains and the outputs generated through the Protein2PAM server, and lists among its purposes improving the models used on the website, so a user of that tool is told its submissions may feed the models. From the AI Health Index, drawn from each vendor's own published materials and the regulatory record, verified September 28, 2026. No vendor pays for placement.
Which settings and specialties do Generate:Biomedicines and Profluent cover?
In Generate:Biomedicines' case, the platform addresses protein therapeutics: antibodies against defined epitopes, functional antibodies that act on cell surface receptors, proteins optimized for arbitrary properties, and proteins recoded to reduce immune recognition.
For Profluent, the company states that its platform is pointed first at CRISPR and gene editing, and names applications from new therapeutics to industrial enzymes across medicine, agriculture and beyond, with designs spanning gene editors, antibodies and broader enzymes and a partnership on recombinases for genetic medicine announced in April 2026. Modality is proteins rather than small molecules, which is the real boundary. From the AI Health Index, drawn from each vendor's own published materials and the regulatory record, verified September 28, 2026. No vendor pays for placement.
What evidence is published for Generate:Biomedicines and Profluent?
With Generate:Biomedicines, the method behind the designs is in the peer reviewed literature: Chroma in Nature, November 2023, with weights released for academic and non profit use. Collaborations with Amgen and Novartis cover confidential programs first announced in January 2022 and September 2024.
In Profluent's case, the founding method paper, showing that language models generate functional proteins across diverse families, appeared in Nature Biotechnology in 2023. From the AI Health Index, drawn from each vendor's own published materials and the regulatory record, verified September 28, 2026. No vendor pays for placement.
Related comparisons
Other published head to head assessments involving these vendors or their closest peers. The full set for this category is on the Drug Discovery AI page.
Both records were reviewed on this site in September 2026. Neither publishes prices beyond Profluent's free OpenCRISPR-1 license.
Ask both what share of generated designs work in the lab.