Qualified Access Program
We’re extending the Engine to a limited number of partners through the Qualified Access Program for pharma and biotech teams bringing real translational and clinical questions that sit at the intersection of modalities, scales, and the decisions they inform. If your team is working on a question of this kind, we’d like to hear about it.
What we do together
Each engagement is a working partnership. You bring the question and the scientific context that shapes it. Our team operates the engine on your data, working through the question with your scientific lead—exploring hypotheses, surfacing mechanisms, and refining the outputs as the picture comes into focus. Partners don’t need to integrate the engine, train scientists on it, or build internal AI infrastructure. The engine stays with us. The project we run together.
What you receive are outputs sized to your decision, each one carrying a reasoning trace, which your scientists can interrogate the way they would a colleague’s paper.
Every engagement is structured around these four commitments from us.
A named project team. Project lead, lead scientist, and executive sponsor—assigned for the duration of the engagement.
A defined scope. A scientific question, milestones, and the end date clear at kickoff—and refined together as the work progresses.
A defined scope. A scientific question, milestones, and the end date clear at kickoff—and refined together as the work progresses.
A clear end-state. Continuation under standard terms, a defined extension, or a clean off-board. The three outcomes are agreed up front so the end of the engagement is never a surprise.
Where the engine is being put to work
The engine is built for translational and clinical decisions. Here are some examples of where partners have been finding it useful, and where the engine is being applied across a growing range of questions.
A preclinical evidence package for IND. Which indication is most likely to respond, and why. Which patient subpopulations the mechanism actually serves. Whether a candidate biomarker is strong enough to enrich a Phase Ib/2—or if the available evidence says no.
A preclinical evidence package for IND. Which indication is most likely to respond, and why. Which patient subpopulations the mechanism actually serves. Whether a candidate biomarker is strong enough to enrich a Phase Ib/2—or if the available evidence says no.
Exploratory clinical positioning work. Comparative asset dossiers, lifecycle planning, BD diligence support. These are areas where the engine is being applied to a growing range of questions. Partners with engagements in these areas are particularly welcome.
Translational and computational biology in immunology, inflammation, or haematology. Target context, pathway analysis, omics interpretation, biomarker rationale, model-system selection. Co-scientist support in therapeutic areas adjacent to our oncology foundation, where the engine’s application is currently being extended.
Questions that don’t map onto these examples are welcome—the engine is most useful wherever a question hasn’t been asked in quite that way before.
Who fits
The strongest engagements share a few characteristics:
A defined scientific question. One where the partner has done the prior work, knows what has been tried, and where a better answer would inform a decision the partner is actively making.
A scientific lead engaged with the work. Working sessions are scientific conversations between the partner’s lead and our team. The depth of the engagement on both sides shapes the outcome.
Decision-making authority within reach. The engagement is most productive when the partner can act on the findings—either directly or with internal stakeholders who are part of the conversation early.
Requesting an invite
Tell us about the question. The form takes about ten minutes; we respond within two weeks.
If the fit is right, we’ll schedule a discovery conversation to scope the project together. If it isn’t, we’ll tell you why.