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

doi:10.1208/s12248-023-00840-3

Cited by 3 publications

(2 citation statements)

References 23 publications

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“…13−15 The pressure events are variable in terms of timing and magnitude, starting from below 10 mbar and reaching up to 460 mbar in phase III. 16,17 Furthermore, MMC cycles determine transit times of the dissolved drug, 18,19 volume of the gastric fluid, 20−23 and secretion. 1,12 Since the MMC cycles are characterized by substantial variability, their effect on an in vivo performance of oral drug products can be significant.…”

Section: Introductionmentioning

confidence: 99%

“…Researchers distinguished cyclically repeating phases in the fasted stomach, called the migrating motor complex (MMC): phase I of minimal contractile activity, phase II characterized by irregular contractions of intermittent magnitude, and phase III of the most frequent pressure events of maximal strength, including the “housekeeper wave” . Various lengths of the MMC cycle were determined: from 100 min and up to 230 min, but also, the duration of each of the phases is not constant. − The pressure events are variable in terms of timing and magnitude, starting from below 10 mbar and reaching up to 460 mbar in phase III. , Furthermore, MMC cycles determine transit times of the dissolved drug, , volume of the gastric fluid, − and secretion. , …”

Section: Introductionmentioning

confidence: 99%

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In Vitro Simulation of the Fasted Gastric Conditions and Their Variability to Elucidate Contrasting Properties of the Marketed Dabigatran Etexilate Pellet-Filled Capsules and Loose Pellets

Staniszewska,

Myslitska,

Romański

et al. 2024

Mol. Pharmaceutics

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Variability of the gastrointestinal tract is rarely reflected in in vitro test protocols but often turns out to be crucial for the oral dosage form performance. In this study, we present a generation method of dissolution profiles accounting for the variability of fasted gastric conditions. The workflow featured 20 biopredictive tests within the physiological variability. The experimental array was constructed with the use of the design of experiments, based on three parameters: gastric pH and timings of the intragastric stress event and gastric emptying. Then, the resulting dissolution profiles served as a training data set for the dissolution process modeling with the machine learning algorithms. This allowed us to generate individual dissolution profiles under a customizable gastric pH and motility patterns. For the first time ever, we used the method to successfully elucidate dissolution properties of two dosage forms: pellet-filled capsules and bare pellets of the marketed dabigatran etexilate product Pradaxa. We showed that the dissolution of capsules was triggered by mechanical stresses and thus was characterized by higher variability and a longer dissolution onset than observed for pellets. Hence, we proved the applicability of the method for the in vitro and in silico characterization of immediate-release dosage forms and, potentially, for the improvement of in vitro-in vivo extrapolation.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

In Vitro Simulation of the Fasted Gastric Conditions and Their Variability to Elucidate Contrasting Properties of the Marketed Dabigatran Etexilate Pellet-Filled Capsules and Loose Pellets

Staniszewska,

Myslitska,

Romański

et al. 2024

Mol. Pharmaceutics

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show abstract

Physiological Dynamics in the Upper Gastrointestinal Tract and the Development of Gastrointestinal Absorption Models for the Immediate-Release Oral Dosage Forms in Healthy Adult Human

Wang,

Amidon,

Smith

2023

Pharm Res

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Estimation for stochastic differential equation mixed models using approximation methods

Jamba,

Jacinto,

Filipe

et al. 2024

MATH

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<abstract><p>We used a class of stochastic differential equations (SDE) to model the evolution of cattle weight that, by an appropriate transformation of the weight, resulted in a variant of the Ornstein-Uhlenbeck model. In previous works, we have dealt with estimation, prediction, and optimization issues for this class of models. However, to incorporate individual characteristics of the animals, the average transformed size at maturity parameter $ \alpha $ and/or the growth parameter $ \beta $ may vary randomly from animal to animal, which results in SDE mixed models. Obtaining a closed-form expression for the likelihood function to apply the maximum likelihood estimation method is a difficult, sometimes impossible, task. We compared the known Laplace approximation method with the delta method to approximate the integrals involved in the likelihood function. These approaches were adapted to allow the estimation of the parameters even when the requirement of most existing methods, namely having the same age vector of observations for all trajectories, fails, as it did in our real data example. Simulation studies were also performed to assess the performance of these approximation methods. The results show that the approximation methods under study are a very good alternative for the estimation of SDE mixed models.</p></abstract>

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

Cited by 3 publications

References 23 publications

In Vitro Simulation of the Fasted Gastric Conditions and Their Variability to Elucidate Contrasting Properties of the Marketed Dabigatran Etexilate Pellet-Filled Capsules and Loose Pellets

In Vitro Simulation of the Fasted Gastric Conditions and Their Variability to Elucidate Contrasting Properties of the Marketed Dabigatran Etexilate Pellet-Filled Capsules and Loose Pellets

Physiological Dynamics in the Upper Gastrointestinal Tract and the Development of Gastrointestinal Absorption Models for the Immediate-Release Oral Dosage Forms in Healthy Adult Human

Estimation for stochastic differential equation mixed models using approximation methods

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