pharmtox-admetai-prediction

Validate ADMET toxicity predictions for multiple compounds by running the built-in verification workflow to check AI model predictions against predefined reference sets. It enforces numeric thresholds, text-length requirements, and RDKit SMILES validation.

An ISC template for pharmacology toxicity assessment is a structured workflow that codifies ADMET validation rules. It standardizes toxicology evaluations across chemicals using predefined YAML frontmatter, multilingual prompt files, and built-in verification tooling.

Yes, you can use RDKit for SMILES validation in ADMET prediction workflows. This template integrates RDKit-based SMILES validation alongside AI model predictions using a configurable Python script to ensure chemical structures meet required formats.

The ADMET validation template requires a Python environment to run the configurable AI model prediction script and the RDKit toolkit for SMILES validation. Execute the provided verify_template.sh script to enforce ISC guidelines and toxicity checks.

Enforce numeric thresholds and text-length requirements for toxicity descriptions by running the built-in verification workflow. This automated process checks AI model predictions and textual assessments against predefined toxic reference sets to guarantee consistency.