QSAR, ADMET & Predictive Toxicology

Tools for Designing Therapeutics with Favorable Pharmacokinetic Properties and Safety Profiles

Discover Safe and Effective Therapeutics

Understanding and quantifying structure-activity relationships can significantly impact lead optimization and drug development by minimizing tedious and costly experimentation. Build, validate and apply your own models based on a wide range of approaches, and keep improving them as new data become available. Assess the potential risk posed by unfavorable pharmacokinetic properties and potential toxicity using BIOVIA Discovery Studio’s distributed models, extend them to better cover your proprietary chemical space and use the comprehensible indications to navigate around such liabilities.

QSAR
ADMET
Toxicity

QSAR

Comprehensive and consistent data preparation:
- Ligands: remove duplicates and handle tautomers and ionization
- Prepare response property (scaling and binning)
- Split your data into training and test sets with the appropriate methods
Choose from a large number of physicochemical, topological, electronic, geometric. fingerprint and Quantum Mechanics based descriptors
Create statistical models including Bayesian, MLR (Multiple Linear Regression), PLS (Partial Least Squares), and GFA (Genetic Functional Analysis)
Analyze and validate models using model applicability domains (MAD), automatic test set validation, cross validation and statistical metrics
Identify Matched Molecular Pairs (MMPs) transformations and study activity cliffs