I run discovery
This is you if
- Too many candidates look equally worth the screen
- The model and the lab are answering different questions
- The program is stuck between interesting and test this
- You need a reason to move one candidate up and another down
What delay costs
Unfocused screening spends the months the program needed for learning. A longer list does not make the next experiment clearer, and the budget does not come back.
Services that fit
Start with one. If two could help, the first conversation is where we say which should come first.
01
AI for Drug DiscoveryUsual first step
When you need compounds and predicted properties narrowed before the lab spends months screening.
02
Bioinformatics
When the program also needs a reading of the biology, not only a ranked list.
03
Biomedical Research
When a disease question has to be written so partners and leaders can follow the evidence.
What the first conversation covers
- 01
The decision the team is struggling to make
- 02
What you already know about the compounds or the biology
- 03
Where a model can prepare the experiment, and where the lab still has to test
Questions people ask first
Will this discover a drug?
No. The output is a priority: what to look at sooner. Laboratory validation still has to happen. We say where a prediction is thin.
We have internal data science.
Use us for the decision the internal queue cannot reach, or for a second pass before a costly screen. The handoff is a shorter list with the reasons attached.