Stochastic Differential Equation-based Mixed Effects Model of the Fluid Volume in the Fasted Stomach in Healthy Adult Human

Wang, Kai; Marciani, Luca; Amidon, Gordon L.; Smith, David E.; Sun, Duxin

Abstract

The rate and extent of drug dissolution and absorption from a solid oral dosage form depend largely on the fluid volume along the gastrointestinal tract. Hence, a model built upon the gastric fluid volume profiles can help to predict drug dissolution and subsequent absorption. To capture the great inter- and intra-individual variability (IAV) of the gastric fluid volume in fasted human, a stochastic differential equation (SDE)-based mixed effects model was developed and compared with the ordinary differential equation (ODE)-based model. Twelve fasted healthy adult subjects were enrolled and had their gastric fluid volume measured before and after consumption of 240 mL of water at pre-determined intervals for up to 2 hours
post ingestion. The SDE- and ODE-based mixed effects models were implemented and compared using extended Kalman filter algorithm via NONMEM. The SDE approach greatly improved the goodness of fit compared with the ODE counterpart.
The proportional and additive measurement error of the final SDE model decreased from 14.4 to 4.10% and from 17.6 to 4.74 mL, respectively. The SDE-based mixed effects model successfully characterized the gastric volume profiles in the fasted healthy subjects, and provided a robust approximation of the physiological parameters in the very dynamic system.
The remarkable IAV could be further separated into system dynamics terms and measurement error terms in the SDE model instead of only empirically attributing IAV to measurement errors in the traditional ODE method. The system dynamics were best captured by the random fluctuations of gastric emptying coefficient Kge.

Citation

Wang, K., Marciani, L., Amidon, G. L., Smith, D. E., & Sun, D. (2023). Stochastic Differential Equation-based Mixed Effects Model of the Fluid Volume in the Fasted Stomach in Healthy Adult Human. AAPS Journal, 25(5), https://doi.org/10.1208/s12248-023-00840-3

• Journal Article Type: Article
• Acceptance Date: Jul 1, 2023
• Online Publication Date: Jul 27, 2023
• Publication Date: Jul 27, 2023
• Deposit Date: Jul 30, 2023
• Publicly Available Date: Jul 28, 2024
• Journal: The AAPS Journal
• Electronic ISSN: 1550-7416
• Publisher: American Association of Pharmaceutical Scientists
• Peer Reviewed: Peer Reviewed
• Volume: 25
• Issue: 5
• DOI: https://doi.org/10.1208/s12248-023-00840-3
• Keywords: Pharmaceutical Science
• Public URL: https://nottingham-repository.worktribe.com/output/23609538
• Publisher URL: https://link.springer.com/article/10.1208/s12248-023-00840-3
• Additional Information: Received: 18 April 2023; Accepted: 1 July 2023; First Online: 27 July 2023; : ; : The authors declare no competing interests.