ADMET Prediction Comparison
ADMET-AI vs ADMETlab 3.0 vs SwissADME: ADMET Prediction Compared (2026)
Last updated: 2026-04-16
Every drug candidate needs ADMET profiling — absorption, distribution, metabolism, excretion, and toxicity prediction. SwissADME has been the go-to free tool for years. ADMETlab 3.0 and ADMET-AI represent the new generation: deep learning models trained on larger datasets with broader endpoint coverage. Here's how they compare.
ADMET-AI
Greenstone Biosciences / Stanford
ADMETlab 3.0
SCBDD Group, Central South University
SwissADME
Swiss Institute of Bioinformatics (SIB)
Head-to-Head
Structured comparison across key dimensions.
| Dimension | ADMET-AI | ADMETlab 3.0 | SwissADME |
|---|---|---|---|
| Endpoints | 41 ADMET properties | 119 endpoints (ADME + tox + physicochemical + med chem) | ~15 properties + drug-likeness rules |
| Model architecture | Chemprop D-MPNN + RDKit descriptors (GNN) | Multi-task DMPNN + molecular descriptors | Classical QSAR / descriptor-based (not deep learning) |
| Batch processing | Yes — up to 1,000 compounds (web); unlimited (local) | Yes — via REST API | No — single compound only (web UI) |
| Uncertainty estimates | No | Yes (epistemic + aleatoric) | No |
| API available | Via Platform API | Yes (REST API) | No official API |
| On Platform | Yes | No | No |
| Benchmark performance | Highest average rank on TDC ADMET Leaderboard at publication | Strong across most endpoints; largest coverage | Not benchmarked on TDC (different era of models) |
| Cost | Free (web); credits available on the platform | Free (web + API) | Free |
| Key limitation | Web capped at 1,000 molecules; no uncertainty | Academic server (no SLA); some endpoints on small training data | No batch; classical models lag on novel scaffolds; no toxicity panel |
When to Use Each
ADMET-AI
You need to screen a batch of compounds (up to 1,000). You want the best benchmark performance (TDC leaderboard). You want it available on the platform for pipeline integration.
ADMETlab 3.0
You need the broadest endpoint coverage (119 endpoints). You need uncertainty estimates on predictions. You want REST API access for pipeline integration.
SwissADME
You're checking a single compound's drug-likeness at your desk. You want the BOILED-Egg visualization. You need Lipinski/Veber/PAINS rule checks.
Practitioner Verdict
Use ADMET-AI (available on the platform) for batch screening of up to 1,000 compounds with strong benchmark performance. Use ADMETlab 3.0 when you need the broadest coverage (119 endpoints) or uncertainty estimates. Use SwissADME for quick single-compound checks and drug-likeness rules. For serious lead optimization, use ADMET-AI or ADMETlab in combination, and validate hits with ProTox 3.0 for toxicity.
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