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PK/DB: database for pharmacokinetic properties and predictive in silico ADME models
Tiago L Moda1, Leonardo G Torres, Alexandre E Carrara
1Laboratory of Computational and Medicinal Chemistry, Center for Structural Molecular Biotechnology, Institute of Physics of São Carlos, University of São Paulo, São Carlos-SP 13566-970, Brazil.
Bioinformatics (Oxford, England)
|August 8, 2008
Summary
A new database, PK/DB, offers robust pharmacokinetic (PK) data and in silico ADME predictions. This freely available resource aids drug discovery and development by managing extensive PK measurements and predictive models.
Area of Science:
- Pharmacokinetics and Drug Discovery
- Computational Chemistry and Cheminformatics
Background:
- Pharmacokinetic (PK) properties are crucial for effective drug discovery and development.
- In silico prediction of absorption, distribution, metabolism, and excretion (ADME) is vital for early-stage drug assessment.
Purpose of the Study:
- To design and develop PK/DB, a novel, freely available database for pharmacokinetic studies.
- To create robust databases supporting in silico ADME prediction.
- To provide a comprehensive, web-based, and accessible platform for PK data management.
Main Methods:
- Development of a comprehensive, web-based database named PK/DB.
- Management of 1203 compounds and 2973 pharmacokinetic measurements.
- Integration of five distinct in silico ADME prediction models.
Main Results:
- PK/DB successfully manages a substantial collection of pharmacokinetic data.
- The database includes models for predicting human intestinal absorption, oral bioavailability, plasma protein binding, blood-brain barrier penetration, and water solubility.
- The resource is designed for ease of access and comprehensive utility.
Conclusions:
- PK/DB serves as a valuable, freely accessible resource for pharmacokinetic research.
- The database enhances in silico ADME prediction capabilities, supporting efficient drug discovery.
- The integrated PK measurements and predictive models facilitate robust drug development pipelines.
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