AI Drug Discovery Simulator
Individual visual simulation: from target to preclinical shortlist
Biomedical AI

Drug discovery from AI

The simulation models the pipeline: target profiling, molecule generation, docking, ADMET filtering, and preclinical shortlist. Changing model parameters immediately affects stage passability and expected program efficacy.

42k/day
Screening speed
63%
Success probability
28%
Toxicity risk
14.6 months
Time to lead
Dataset quality72%
Model depth12 blocks
Compute budget7 TPU-equivalents
Novelty bias56%
Safety threshold74%
System stable: prioritize docking optimization and toxicity control.
RUNNING
Target
0
fail 0
Generator
0
fail 0
Docking
0
fail 0
ADMET
0
fail 0
Preclinical
0
fail 0