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Models and Methods to Evaluate Transport of Drug Delivery Systems Across Cellular Barriers
Published on: October 17, 2013
Applications of physiologically based absorption models in drug discovery and development
1F. Hoffmann-La Roche Ltd. Pharmaceuticals Division, Pharma Research Non-Clinical Development, Non-Clinical Drug Safety, Basel, Switzerland. neil_john.parrott@roche.com
Molecular Pharmaceutics
|June 13, 2008
Summary
Physiologically based models predict intestinal drug absorption, aiding drug discovery and development from early stages to formulation. These models integrate data for in vivo absorption predictions and assess compound developability for humans.
Area of Science:
- Pharmacokinetics and Drug Metabolism
- Computational Biology
- Pharmaceutical Sciences
Background:
- Physiologically based modeling is crucial for predicting intestinal drug absorption.
- Accurate prediction of drug absorption impacts research and development timelines and costs.
Purpose of the Study:
- To describe the application of physiologically based models of intestinal drug absorption in guiding drug research and development.
- To highlight the utility of these models from early drug discovery through clinical development and formulation.
Main Methods:
- Integrating multiple screening data into early simulations for preclinical species.
- Comparing simulation predictions with in vivo plasma concentration data from animal studies.
- Utilizing parameter sensitivity analysis to explore uncertainties and identify absorption-limiting factors.
Main Results:
- Simulations transform individual properties into predictions of in vivo absorption.
- Comparison with animal data reveals unexpected absorption behaviors.
- Parameter sensitivity analysis aids in assessing compound developability and identifying absorption bottlenecks.
Conclusions:
- Physiological models reliably predict human drug absorption.
- Refinement with Phase 1 data guides market formulation development.
- Future improvements depend on in vitro methods for solubility/permeability and modeling transporter effects.
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