Predict toxicity. Save lives. Faster.
Screen any molecule across 12 biological targets in milliseconds. Built on Tox21 — the gold standard toxicity dataset.
Average cost of a failed drug due to unexpected toxicity
Traditional toxicity testing takes 3-5 years per compound through animal studies and lab work
90% of drug candidates fail — toxicity is the #1 reason for late-stage failures
Each failed compound wastes millions before toxicity is discovered
ToxPredict changes this.
Type any drug name and get instant toxicity predictions
9 of 12 toxicity targets exceed the 0.75 industry benchmark threshold
We extract three complementary types of molecular features:
Total: 2,224 features per molecule
Soft voting combines probability outputs from all three models — this approach almost always outperforms any single model and is more robust to individual model weaknesses.
We use 5-fold Stratified Cross Validation to ensure our metrics are reliable and not overfitted to a single train/test split. This is the standard validation approach in published pharmaceutical ML research.
Scientific honesty is part of good science
"Heroin scores low on our model — not because it's safe, but because its danger comes from opioid receptor binding, which Tox21 doesn't measure. A complete drug safety system requires multiple complementary assay panels. This is a known limitation of all Tox21-based models."— ToxPredict Team
Prescribed to pregnant women for morning sickness — caused 10,000+ birth defects worldwide. Teratogenicity was not tested.
Weight loss drug withdrawn after causing fatal heart valve damage in thousands of patients.
Painkiller withdrawn — linked to 60,000+ cardiac deaths. Cardiovascular risk missed in trials.
AI toxicity screening like ToxPredict catches cellular danger signals before compounds reach human trials.