A Population-based Gastrointestinal Transit Model Using Individual-Level Imaging Data.

IF 4.1 3区医学 Q2 CHEMISTRY, MULTIDISCIPLINARY

Pharmaceutical Research Pub Date : 2026-09-24 DOI:10.1007/s11095-026-04210-4

Feifan Xie, Yuxin Xie, Yehua Xie, Zeneng Cheng, Feiyan Liu

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引用次数: 0

Abstract

Purpose: Gastrointestinal (GI) transit is a key determinant of oral drug absorption. Existing GI transit models derived from summary transit-time distributions provide limited characterization of inter-individual variability. This study aimed to develop a population-based GI transit model using individual-level imaging data.

Methods: Individual gastric emptying (GE), small intestinal (SI) transit, and colon arrival (CA) data from imaging studies of non-absorbed markers in healthy adults were extracted from the literature. A population-based GI transit model was developed using sequential Weibull GE and transit compartment models. Formulation type and prandial state were evaluated as covariates, and inter-individual variability was estimated on key transit parameters.

Results: Individual data comprising 90 GE, 26 SI, and 39 CA profiles were included. The final model consisted of a Weibull GE component and a six-compartment SI transit model. Formulation type and prandial state significantly influenced GE. Mean GE time was 0.16 h for liquid formulations under fasted conditions, while mean SI transit time was 2.97 h with substantial inter-individual variability (CV = 50.0%).

Conclusion: This population-based GI transit model, informed by individual imaging data, quantitatively captures both mean transit behavior and inter-individual variability and may facilitate mechanistic absorption frameworks for oral drug exposure prediction.

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基于个体水平成像数据的人群胃肠运输模型。

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来源期刊

Pharmaceutical Research 医学-化学综合

CiteScore

6.60

自引率

5.40%

发文量

276

审稿时长

3.4 months

期刊介绍： Pharmaceutical Research, an official journal of the American Association of Pharmaceutical Scientists, is committed to publishing novel research that is mechanism-based, hypothesis-driven and addresses significant issues in drug discovery, development and regulation. Current areas of interest include, but are not limited to: -(pre)formulation engineering and processing- computational biopharmaceutics- drug delivery and targeting- molecular biopharmaceutics and drug disposition (including cellular and molecular pharmacology)- pharmacokinetics, pharmacodynamics and pharmacogenetics. Research may involve nonclinical and clinical studies, and utilize both in vitro and in vivo approaches. Studies on small drug molecules, pharmaceutical solid materials (including biomaterials, polymers and nanoparticles) biotechnology products (including genes, peptides, proteins and vaccines), and genetically engineered cells are welcome.