BioMate AI
Scientists designing new medicines

How we design · 中文

How we design
medicines

Designed in silico · tested in the lab · guided by patient data

Three loops not one

Computer lab and clinic
three loops that compound

Real drug design runs more than one loop — and its most valuable input is patient and clinical data. ① An in-silico loop generates and scores candidates against everything we know — patient and clinical data, known biology and structure, patents and freedom-to-operate, medicinal-chemist expertise, and our predictors — over many fast, low-cost rounds that converge on a small set, before anything is synthesized. ② A wet-lab loop takes over from there — synthesis, in-vitro assays, ADMET and in-vivo are all experimental — and the results recalibrate the computational models, so each in-silico round sharpens while each wet-lab round shrinks. ③ A clinical loop closes around both: patient and clinical data guides which targets to pursue and validates the mechanism, feeding back so the whole system gets better at choosing what to make.

Patient & clinical data — what we label and use Cohorts & labels Disease vs. healthyResponder vs. non-responderSeverity & stage Multi-omics TranscriptomicsProteomicsHuman genetics / GWAS Target evidence Expression in disease tissueGenetic associationMechanism validation Outcomes Treatment responseBiomarkersDisease progression guides target selection ① In-silico loop — fast & low-cost, before any synthesis Target &epitope Generate Score &select iterate · many fast rounds … also bounded by Known biology & structure Patents · FTO Med-chem expertise Predictors converged set ② Wet-lab loop — every candidate must clear these Synthesis & identityHPLC · mass-spec · purity Affinity & selectivityKd (SPR/BLI) · counter-targets Functional potencycell EC50 · mechanism readout Developabilitysolubility · permeability · stability Safety / ADMEThERG · CYP · cytotoxicity In-vivo PK & efficacyexposure · half-life · disease model a candidate must clear all of these to advance Candidates advance to the clinic ② wet-lab results recalibrate the in-silico models ③ clinical outcomesfeed back

Picking the right target is its own discipline — see how we identify targets →

Before anything is made

We check what matters
not just whether it works

Most candidate medicines fail late, for reasons that could have been caught early. We weigh all of them together, from the start.

The right target

Designed to act where it should — and leave the rest alone.

Able to become a medicine

Stable, deliverable and manufacturable — not just active in a dish.

New and ownable

Distinct from what already exists, with clear freedom to develop.

True to the biology

Grounded in how each target actually behaves in the body.

Balanced not one-sided

Activity, safety and makeability weighed together — the real trade-off.

Proven at the bench

The lab, not the model, has the final say.

Experimental validation at the bench

The lab decides

The wet lab has
the final say

Every design is made and tested for real. Those results feed back into the next round — so the work compounds, and the ideas that advance are the ones that hold up at the bench.

See where we focus →

Work with us

Building medicines for
immune-mediated disease