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Implementation of In Vitro Drug Resistance Assays: Maximizing the Potential for Uncovering Clinically Relevant Resistance Mechanisms
Published on: December 9, 2015
Methods for predicting in vivo pharmacokinetics using data from in vitro assays.
J Brian Houston1, Aleksandra Galetin
1School of Pharmacy and Pharmaceutical Sciences, University of Manchester, Manchester M13 9PT, UK. Brian.Houston@manchester.ac.uk
Current Drug Metabolism
|November 11, 2008
Summary
Optimizing in vivo predictions from in vitro metabolic stability and CYP inhibition data requires careful integration of pharmacokinetic parameters. Addressing potential pitfalls ensures accurate drug development and minimizes false positives or negatives.
Area of Science:
- Pharmacokinetics and Drug Metabolism
- In Vitro to In Vivo Extrapolation (IVIVE)
Background:
- In vitro assays are crucial for predicting drug behavior in vivo.
- Accurate prediction requires understanding metabolic stability and CYP inhibition.
- Challenges exist in translating in vitro findings to clinical outcomes.
Purpose of the Study:
- To discuss strategies for optimizing in vivo predictions from in vitro metabolic stability and CYP inhibition data.
- To highlight potential pitfalls and inaccuracies in current methods.
- To provide recommendations for best practices in drug development.
Main Methods:
- Discussing the use of hepatic microsomes and isolated hepatocytes for metabolic stability assessment.
- Integrating metabolic stability data with pharmacokinetic characteristics (protein binding, RBC uptake) and blood flow.
- Utilizing in vitro data (Ki, KI, kinact) for CYP inhibition potential assessment.
Main Results:
- Quantitative in vivo prediction requires integrating in vitro parameters with pharmacokinetic information.
- Key parameters include fmCYP (fraction of metabolic clearance), victim drug properties, and enzyme properties (kdeg).
- Summarizing mechanisms leading to false negatives and false positives in in vitro strategies.
Conclusions:
- Accurate in vivo prediction relies on the comprehensive integration of various in vitro and pharmacokinetic parameters.
- Careful consideration of potential pitfalls is essential for reliable drug-drug interaction predictions.
- Future improvements in prediction strategies are needed for enhanced drug development.
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