ADMETlab

ADMETlab predicts and systematically evaluates absorption, distribution, metabolism, excretion (ADME) and toxicity (T) properties of chemical compounds to inform drug discovery prioritization.

Key Features:

• Comprehensive Database: ADMETlab is built on a database containing 288,967 entries for data-driven analyses.
• Function Modules: Four function modules include drug-likeness analysis and ADMET endpoints prediction, with drug-likeness assessed by six types using five established rules and one predictive model, and prediction of 31 ADMET endpoints categorized as Basic Properties (3), Absorption (6), Distribution (3), Metabolism (10), Elimination (2), and Toxicity (7).
• Systematic Evaluation and Searching: The platform performs systematic compound evaluations, database searches, and similarity analyses to prioritize and filter potential drug candidates.

Scientific Applications:

• Early-stage ADMET assessment: Enables early evaluation of drug-likeness and ADME/T properties to identify potential efficacy and safety issues.
• Virtual screening and prioritization: Supports rapid virtual screening, similarity analysis, and prioritization of chemical structures for downstream development.

Methodology:

Implemented with the Django framework in Python and built upon a database of 288,967 entries.