ADME

ADME predicts Absorption, Distribution, Metabolism, and Excretion (ADME) properties of chemical compounds using quantitative structure-activity relationship (QSAR) models to inform pharmacokinetic profiling and reduce ADME-related failure risk in drug discovery.

Key Features:

• Validation Using Marketed Drugs: QSAR models are validated against a dataset of marketed drugs to anchor predictions in real-world data.
• Tier I ADME Assays Integration: Incorporates Tier I experimental endpoints including kinetic aqueous solubility, parallel artificial membrane permeability assay (PAMPA), and rat liver microsomal stability.
• Updated QSAR Models: QSAR models are updated using recent in-house lead optimization study data for the modeled endpoints.
• Performance Metrics: Validated models display balanced accuracies ranging from 71% to 85%.

Scientific Applications:

• Risk Reduction in Drug Development: Predicts potential ADME-related liabilities early to mitigate pharmacokinetic failure risk in drug development projects.
• Lead Optimization: Provides QSAR-based guidance on how structural modifications may affect kinetic aqueous solubility, PAMPA permeability, and microsomal stability during lead refinement.
• Benchmarking and Comparison: Enables comparison of compounds against a validated set of marketed drugs to inform chemical design decisions.

Methodology:

Integrates experimental Tier I assay data with computational modeling techniques to analyze relationships between chemical structure and ADME properties, generate predictive QSAR models, and refine those models through validation against marketed drug data.