Profluent

The models are the company and the proof is unusually direct. ProGen3 is a family of billion parameter generative language models trained on more than 3.4 billion protein sequences, and the company's founding scientific claim, published in Nature Biotechnology in 2023, was that large language models can generate functional proteins at all. OpenCRISPR-1 closes the argument: a working genome editor whose sequence sits 182 mutations from any natural protein in the CRISPR-Cas Atlas could not have been arrived at by screening nature, so the model is not accelerating a search, it is producing something that was not there to find.

The disclosed workflow puts experimental characterisation directly after generation rather than treating model output as a result. For OpenCRISPR the company generated candidates, selected 48 sequences and characterised them functionally in human cells, then reported both on target and off target activity against the incumbent enzyme, which is the correct shape for validating a designed molecule. Held at B because no confidence thresholds, generation to hit ratios across programmes, or published guidance on where the models are unreliable were located, so the oversight is demonstrated in one flagship case rather than specified as a standing practice.

Peer reviewed twice at the highest level and specific about architecture. The foundational demonstration that language models generate functional proteins appeared in Nature Biotechnology in 2023, and the AI designed CRISPR system appeared in Nature in 2025, so both the method and its most consequential output have been externally reviewed. ProGen3 is described concretely, as billion parameter models over 3.4 billion sequences using a sparse architecture reported to give a fourfold speedup without performance loss, accompanied by a preprint the company describes as the first wet lab evidence of scaling benefits in biological design. Subsequent work is named and characterised rather than gestured at, including E1 as a retrieval augmented model for protein engineering and Protein2PAM for programming editor recognition motifs.

Molecular evidence is excellent, clinical evidence is absent, and buyers should hold those apart. OpenCRISPR-1 was benchmarked head to head against SpCas9, the standard tool it would replace, with on target editing of 55.7 percent against 48.3 percent and off target editing of 0.32 percent against 6.1 percent, published in Nature. Comparing a designed molecule directly against the incumbent on the axis where the incumbent is weakest, and publishing the numbers, is a stronger form of evidence than most in this category offer. Operational adoption is named rather than anonymous, with commercial relationships including Revvity, Corteva Agriscience, the Rett Syndrome Research Trust and Integrated DNA Technologies. What does not exist is a therapeutic in humans; the company states bringing an AI designed therapeutic to patients as a goal, which places it behind category peers with clinical assets. Download and licence request figures are company reported.

Not applicable in the provider sense and rated accordingly rather than penalized. The models operate on protein and nucleic acid sequence data with no patient records in the workflow. The distinct safety question raised by this vendor's output is biological rather than informational and is treated on the governance axis.

Not applicable. Counterparties are pharmaceutical, agricultural, diagnostic and biomanufacturing organizations licensing molecules or model access, not covered entities transferring protected health information.

No SOC 2, ISO 27001 or equivalent attestation was located and no trust center was found. Partners entering collaborations place proprietary target and sequence information into the environment, so diligence on this axis would run through the collaboration or API agreement.

Nothing to assess rather than something assessed poorly. The models and the designed molecules are research and licensing assets rather than regulated products, and the company maintains no disclosed clinical pipeline of its own. Regulatory standing for any therapeutic built on OpenCRISPR or another licensed asset sits with the licensee that develops it, which is a structural consequence of the open licensing model.

The disclosure gap here is specific and consequential, and it should be stated with the mitigating facts attached. Profluent designed a functional human genome editor with a generative model and released it openly for free licensing, and no accompanying dual use risk assessment, release governance framework or access policy was located in this review. That is the same question EvolutionaryScale answered in this category by commissioning an external review of the risks and benefits before releasing an open model, which makes the contrast a direct one rather than a general complaint. Two facts cut the other way and belong in any fair reading: OpenCRISPR-1 reduced off target editing by roughly 95 percent against SpCas9, so on the axis most relevant to gene editing safety the designed molecule is an improvement on the incumbent, and free licensing has a genuine access argument since it bypasses the licence payments attached to existing CRISPR patent families. The separate domain bias question, whether generation quality falls away in protein families with sparse training coverage, is partially addressed by the company's scaling law work but no per family breakdown was located.

Not applicable. This is a molecular design platform with no provider workflow surface and no EHR touchpoint.

Three access routes are stated openly, which is more than most in this category: licensing a designed molecule asset outright, collaborating on new proteins, or joining an early access programme for the models themselves via API. OpenCRISPR-1 is distributed as an openly licensed sequence, which is the least restrictive delivery model in the category since the recipient simply holds the molecule. Held at B rather than A because model access is an early access API rather than a generally available product, and no on premise option, tenancy terms or data residency commitments were located.

The commercial structure is unusually legible even though no price is published. Three routes are named plainly, being asset licensing, collaboration and early access to models, and the free licensing of OpenCRISPR-1 is itself a published commercial term with a stated rationale. Commercial counterparties are named across sectors rather than described generically, including Revvity, Corteva Agriscience, the Rett Syndrome Research Trust and Integrated DNA Technologies, which lets a buyer see what kind of organization actually transacts here. Funding is disclosed at 150 million dollars total including a 106 million dollar Series B co led by Altimeter Capital and Bezos Expeditions. No rate card, licence fee schedule or deal economics were located.

Broad by design and demonstrated across genuinely different protein classes rather than asserted. Disclosed target markets span therapeutics, diagnostics, agriculture and biomanufacturing, and the underlying model family has produced or been applied to enzymes, antibodies, gene editors and peptides, with OpenAntibodies covering single shot design against 20 drug targets and OpenCRISPR covering genome editing. The named commercial relationships mirror that spread, from a life sciences tools company to an agricultural science company to a rare disease research trust. Modality is proteins rather than small molecules, which is the real boundary.