Dynamically simulating the effect of food on gastric emptying using a detailed physiological model for gastrointestinal transit and absorption
K. Thelen(1), K. Coboeken(1), Y. Jia(2), J.B. Dressman(3), S. Willmann(1)
(1) Computational Systems Biology, Bayer Technology Services GmbH, Leverkusen, Germany; (2) Abteilung Naturwissenschaftliche Technik, Hochschule Emden/Leer, Emden, Germany; (3) Institute of Pharmaceutical Technology, Johann Wolfgang Goethe University, Frankfurt am Main, Germany
Objectives: It is well-known that food can influence drug absorption through different physicochemical and physiological mechanisms. One important factor represents the rate of gastric emptying (GE), which controls the delivery of drugs to the absorption sites in the intestine. In order to predict the impact of meal ingestion on drug absorption, the relationship between the characteristics of a meal and the GE rate was analyzed, characterized and integrated into a novel model for gastrointestinal transit and absorption.[2,3]
Methods: In a comprehensive literature search, information about the impact of various meals on GE function was collected. The data was analyzed for the influence of the characteristics of the meal including its volume, energy content and composition on the GE rate. Seven mathematical functions were tested for the ability to describe the experimental GE profiles. The most suitable function retrieved was subsequently implemented into the detailed absorption model that is part of the physiologically-based pharmacokinetic (PBPK) software tool PK-Sim®. With the help of this function, the impact of co-administration of a meal on the pharmacokinetics (PK) of an orally administered drug was predicted for a population of 500 male individuals using the example of paracetamol.
Results: More than 100 datasets for GE profiles following ingestion of various meals were obtained. In agreement with literature information, the meal energy content was found to be the principal factor determining the GE rate. A mathematical function of the Weibull type was identified to be the most appropriate empirical function to describe the relevant phases of the experimental GE profiles irrespective of the composition of the meal. Based on the PBPK model for paracetamol administered in the fasted state and using the optimized function, the impact of food ingestion on paracetamol PK could be predicted well.
Conclusions: The influence of meal ingestion on GE rate in humans was analyzed on the basis of extensive literature information. The comprehensive set of data was successfully transferred into an empirical GE function that can be used to physiologically simulate the food-related effect of GE on the PK of orally administered drugs. Further physiological changes associated with the ingestion of meals and that are considered to influence the PK of drugs such as luminal pH, gastrointestinal liquid volumes and splanchnic blood flow will be studied soon.
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