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Updated: Jun 21, 2026

An Intestine/Liver Microphysiological System for Drug Pharmacokinetic and Toxicological Assessment
Published on: December 3, 2020
Mechanistic prediction of food-induced variability in drug release and pharmacokinetics using a dynamic
Weiwei Qu1, Peng Wu2, Shilei Yang3
1Institute of Blood and Marrow Transplantation, National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, Collaborative Innovation Center of Hematology, The First Affiliated Hospital of Soochow University, Medical College of Soochow University, Soochow University, Suzhou, Jiangsu 215123, China.
Abstract:
Oral sustained-release (SR) formulations are widely used in clinical practice, yet reliable prediction of their in vivo performance remains challenging due to the dynamic and heterogeneous gastrointestinal (GI) environment. Here, a bioinspired dynamic human stomach-intestine system (DHSI-IV) was used to simulate physiologically relevant GI environments under different prandial states. Ibuprofen SR capsules were evaluated under fasted (water), milk, carbonated beverage, and high-fat meal conditions. The DHSI-IV reproduced pronounced prandial-dependent GI dynamics, with gastric half-emptying times ranging from 16.7 min (water) to 90.2 min (high-fat meal). These differences led to distinct dissolution behaviors, with cumulative release of 42.1 ± 1.5% (water), 33.15 ± 2.05% (carbonated beverage), 41.95 ± 3.35% (milk), and 44.35 ± 1.45% (high-fat meal). Coupling in vitro dissolution data with a simplified convolution-based pharmacokinetic (PK) back-calculation approach enabled prediction of systemic exposure. Predicted fasted-state PK parameters agreed with clinical data (Tmax 4.0 ± 0.5 h vs. ∼ 4.5 h; Cmax 12.5 ± 2.7 μg/mL vs. 13.88 ± 2.6 μg/mL). Under fed (high-fat meal) conditions, the model captured delayed absorption (Tmax 5.5 ± 0.5 h vs. ∼ 6.0 h) and increased exposure (Cmax 20.2 ± 2.3 μg/mL; AUC0-24h 153.7 ± 22.6 μg·h/mL). Overall, DHSI-IV provides a predictive platform for evaluating SR formulations under physiologically relevant GI conditions, supporting food-effect assessment and formulation optimization.
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