Your generative pipeline already produces candidates faster than chemistry can evaluate them. Quantum-hybrid training raises the share that earns bench time — roughly 10× more structures well suited to human drugs in a completed pharmaceutical proof-of-concept. bartech.one provides the access, the modelling and the integration.
A one-page technical brief, sent by email. No form to fill in.
A generative model will hand you a million candidate structures overnight — that part now works beautifully. The harder question is which ones carry the molecular weight, the lipophilicity and the drug-likeness together, because optimizing those jointly rather than one at a time is exactly the shape of problem classical hardware finds expensive. Which is why searches are usually run one property at a time.
The good molecules were always in there. Until now, the search simply couldn't afford to look for all of them at once.
Outcomes recorded in completed proof-of-concept and production deployments of the underlying platform.
No rip-and-replace, and nothing sensitive leaving your network.
Quantum optimization, combinatorial variables, mixed-integer linear programming and tensor programming in one engine — so you describe the science, not the mathematics. No other commercial solver has all four.
Connects to SAP S/4HANA and Oracle over encrypted APIs. All that ever leaves is a matrix and a vector — numbers that cannot be read back into anything. Your compounds, targets and costings never go with them.
Up to two million variables and constraints — the whole problem, every rule, solved at once. Nothing sampled, nothing relaxed to make it fit the software.
One page, the full evidence set, and what a first engagement looks like. Reply comes from a person, not a marketing sequence.