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Can PBPK Modeling Streamline Food Effect Assessments?
1Biopharmaceutics, Pharmaceutical Sciences, Merck & Co., Inc., Kenilworth, New Jersey, USA.
Physiologically based pharmacokinetic (PBPK) modeling can streamline food effect assessments in drug development. This approach uses PBPK models to predict drug absorption influenced by food, optimizing clinical studies.
Area of Science:
- Pharmacokinetics
- Drug Development
- Computational Modeling
Background:
- Physiologically based pharmacokinetic (PBPK) modeling is established for drug-drug interactions and product labeling.
- PBPK models are increasingly used for oral drug absorption and product quality assessments.
- Existing PBPK applications show success in characterizing oral drug product absorption.
Purpose of the Study:
- To explore the utility of PBPK modeling in predicting food-drug interactions.
- To assess the potential of PBPK models for streamlining food effect evaluations in clinical settings.
- To propose a workflow for integrating PBPK into food effect assessments during drug development.
Main Methods:
- Reviewing existing literature on PBPK model applications in oral absorption.
- Analyzing studies that compare PBPK food effect predictions with clinical data.
- Identifying key food effect mechanisms (gastric emptying, luminal solubilization) modeled by PBPK.
- Synthesizing findings to propose a PBPK-driven workflow for food effect assessment.
Main Results:
- PBPK models have successfully characterized oral drug absorption.
- Multiple publications demonstrate PBPK's ability to predict food effects.
- Commonly modeled food effect mechanisms include delayed gastric emptying and altered luminal solubilization.
- PBPK predictions show good agreement with clinical food effect data.
Conclusions:
- PBPK modeling offers a viable approach to streamline food effect assessments.
- The proposed workflow can aid in optimizing clinical development strategies.
- PBPK can reduce the need for certain clinical studies related to food effects.
- This approach is applicable across different Biopharmaceutics Classification System classes.
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