---
title: "ADMET overview"
description: "Screen absorption, metabolism, clearance and toxicity before committing to synthesis — hERG, DILI and mutagenicity, plus protein solubility from a sequence."
tags:
  - section
  - admet
generated: true
---

A molecule can bind perfectly and still fail as a drug — because it isn't absorbed, is cleared too fast, or is toxic. ADMET prediction screens for those liabilities before you commit to synthesis, so you filter bad actors early and optimize the survivors. Reach for it at hit triage, then again during lead optimization.

> **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

- Predict absorption, distribution, metabolism, excretion, and toxicity
- Flag safety liabilities (hERG, DILI, mutagenicity) early
- Predict aqueous solubility
- Profile off-target / kinome selectivity

For which tool fits each, see [What you can achieve](/docs/capabilities).

## Tools in this section

| Tool | What it does |
|---|---|
| [ADMET-AI](/docs/admet-ai) | Predict 41 TDC ADMET endpoints and 8 RDKit descriptors from SMILES with Chemprop-RDKit graph neural networks — hERG, AMES, DILI, CYP450 and clearance. |
| [ADMETlab 3.0](/docs/admetlab3) | Deprecated. The external ADMETlab 3.0 service is unavailable; use ADMET-AI instead. |
| [DeepChem](/docs/deepchem) | Retired. Use ADMET-AI for property and ADMET prediction. |
| [DeepPurpose](/docs/deeppurpose) | Train and run DeepPurpose models for drug-target prediction on the platform. |
| [DeepSol on the platform](/docs/deepsol) | Predict protein solubility for E. coli expression from an amino acid sequence. |
| [GraphSol](/docs/graphsol) | Predict protein solubility from sequence with an attentive graph convolutional network over predicted contact maps — a probability plus a binary call. |

## Recipes using these tools

## Read next