From phenotypic signal to mechanism.
BioSymetrics’ MOA Miner™ turns phenotype-screening hits into ranked hypotheses about targets, mechanisms of action, and biological pathways.
Find the biology behind the hit.
A phenotype-based screen can show which compounds create a desired effect without revealing the molecular explanation. That gap can make mechanism identification a bottleneck for the next stage of discovery.
MOA Miner™ helps connect the observed phenotype to the targets and mechanisms that may explain it, giving partners a clearer starting point for follow-up.
A ranked path from chemistry to biology.
We learn the chemical features associated with hits, rank a much larger chemical space by predicted activity, and examine which target and mechanism-of-action annotations are concentrated near the top of the ranking. Pathway analysis adds biological context to the strongest target signals.
Prioritize the next experiment.
MOA Miner™ produces a ranked evidence base rather than a definitive target assignment. The results can help partners compare hypotheses, understand relevant pathways, and decide which compounds, annotations, or assays to take forward into experimental validation.
Connect prediction to validation.
MOA Miner™ fits into our broader discovery workflow alongside phenotype modelling, computer-vision analysis of high-throughput experimental readouts, pathway analysis, and in vivo validation. We use these connected capabilities to move from a computational signal toward evidence that can be tested in living systems.
Search beyond the annotated library.
We recently expanded our in silico chemical search space to approximately 557 million compounds. Our phenotype model learns from the screen’s hit and no-hit labels, then ranks compounds across that larger search space against the observed signal.
Make every hypothesis easier to assess.
We interpret ranked hypotheses alongside the annotation data that support them and the experiments that test them. Tracking annotation provenance helps partners understand where target and mechanism signals come from, while laboratory validation tests whether those signals hold up in a biological system.
Could MOA Miner™ help you interpret hits from a phenotype screen?
If you have phenotype-screening data and want to prioritize targets, mechanisms, pathways, or follow-up assays, we would welcome a conversation about your screen, annotation needs, and validation plan.
Partner with us