Predictors overview
Validate computational predictions against experimental results, and fit Bayesian PK/PD, dose-response and hierarchical models with PyMC.
Specialized property and safety predictors that supplement the main ADMET and structure tools — literature entity extraction, toxicity, and validation. Reach for these for a specific prediction the broad panels don't cover.
Availability
These tools are metered by credits and gated by your plan — plans set your monthly credits, available model families, and which modal-app tools you can run. See Plans & tiers.
What you can achieve here
- Extract entities and relationships from literature
- Predict specific toxicity endpoints
- Validate and monitor model outputs
For which tool fits each, see What you can achieve.
Tools in this section
| Tool | What it does |
|---|---|
| BioBERT | Deprecated. BioBERT literature search is no longer available in chat; use PubMed search instead. |
| ProTox-3 | Deprecated. ProTox-3 is no longer available; ADMET-AI toxicity endpoints replace it. |
| Validation monitor | Validate computational predictions against experimental results and track hit validation with a test-suite report. |
| Bayesian statistics | Bayesian statistical modeling and PK/PD analysis with PyMC — regression, hierarchical models, dose-response curves, and compartmental PK models. |
Read next
What you can achieve
The outcomes these tools deliver — and which to pick when several do the same thing.
Which tool?
Match a scientific goal to a tool across every domain.
Concept clusters
How tools, jobs, and results fit together.
Workflows
Guided pipelines and copy-and-adapt prompt recipes for common goals.
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