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Improving early drug discovery through ADME modelling: an overview
1Department of Biological Science and Computing Science, University of Alberta, Edmonton, AB, Canada. david.wishart@ualberta.ca
Drugs in R&D
|October 30, 2007
Summary
Drug development faces high failure rates. Early prediction of ADME (absorption, distribution, metabolism, excretion) properties using computational modeling can significantly reduce costly late-stage drug discovery failures.
Area of Science:
- Drug Discovery and Development
- Computational Chemistry
- Pharmacokinetics
Background:
- Drug development is a high-risk, high-cost process with low success rates.
- Late-stage termination of drug candidates is often due to unforeseen pharmacokinetic issues.
- Early identification of problematic drug leads is crucial for efficiency.
Purpose of the Study:
- To review the application of ADME (absorption, distribution, metabolism, excretion) modeling in reducing late-stage attrition in drug discovery.
- To highlight existing tools for predicting and visualizing ADME data.
- To discuss the need for further tool development and integration of ADME data in early compound selection.
Main Methods:
- Review of current literature and available computational tools for ADME prediction.
- Focus on ADME parameter predictors, metabolic fate and stability predictors, cytochrome P450 substrate predictors, and PBPK modeling.
- Discussion on the integration of ADME data into early drug discovery workflows.
Main Results:
- ADME modeling offers a promising route to identify problematic drug leads early.
- Various tools exist for predicting ADME parameters, metabolic fate, stability, and drug-drug interactions (e.g., CYP450 substrates).
- Physiology-based pharmacokinetic (PBPK) modeling software is available for in-depth analysis.
Conclusions:
- Integrating ADME modeling and data visualization early in drug discovery can significantly reduce late-stage failures.
- Further development of predictive tools and their seamless integration is essential.
- Proactive assessment of ADME properties is key to successful and cost-effective drug development.
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