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

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

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Article in Pharmaceutical research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 authors.

Feifan XieDivision of Biopharmaceutics and Pharmacokinetics, Xiangya School of Pharmaceutical Sciences, Central South University, Tongzipo Road 172, Changsha, 410013, China.

Yuxin XieDivision of Biopharmaceutics and Pharmacokinetics, Xiangya School of Pharmaceutical Sciences, Central South University, Tongzipo Road 172, Changsha, 410013, China.

Yehua XieEli Lilly and Company, Shanghai, China.

Zeneng ChengDivision of Biopharmaceutics and Pharmacokinetics, Xiangya School of Pharmaceutical Sciences, Central South University, Tongzipo Road 172, Changsha, 410013, China.

Feiyan LiuDivision of Biopharmaceutics and Pharmacokinetics, Xiangya School of Pharmaceutical Sciences, Central South University, Tongzipo Road 172, Changsha, 410013, China. feiyan.liu@csu.edu.cn.ORCID http://orcid.org/0000-0002-3711-2810

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6 · The paper itself

Abstract

purposeGastrointestinal (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.

methodsIndividual 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.

resultsIndividual 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%).

conclusionThis 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.

Indexed as

AbsorptionGastric emptyingInter-individual variabilityPopulation modelingSmall intestinal transit

Identifiers

PMID42786367

DOI10.1208/s12248-012-9324-y

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