---
title: "Predictors overview"
description: "Validate computational predictions against experimental results, and fit Bayesian PK/PD, dose-response and hierarchical models with PyMC."
tags:
  - section
  - predictors
generated: true
---

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](/docs/plans-and-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](/docs/capabilities).

## Tools in this section

| Tool | What it does |
|---|---|
| [BioBERT](/docs/biobert) | Deprecated. BioBERT literature search is no longer available in chat; use PubMed search instead. |
| [ProTox-3](/docs/protox3) | Deprecated. ProTox-3 is no longer available; ADMET-AI toxicity endpoints replace it. |
| [Validation monitor](/docs/validation-monitor) | Validate computational predictions against experimental results and track hit validation with a test-suite report. |
| [Bayesian statistics](/docs/bayesian) | Bayesian statistical modeling and PK/PD analysis with PyMC — regression, hierarchical models, dose-response curves, and compartmental PK models. |

## Read next