ArticleThe AAPS journal2012
A mechanism-based approach for absorption modeling: the Gastro-Intestinal Transit Time (GITT) model.
Article in The AAPS journal, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Meta-analysis of Magnetic Marker Monitoring Data to Characterize the Movement of Single Unit Dosage Forms Though the Gastrointestinal Tract Under Fed and Fasting Conditions.Pharmaceutical research · 2016Pooled it
- Individualized, discrete event, simulations provide insight into inter- and intra-subject variability of extended-release, drug products.Theoretical biology & medical modelling · 2012Trial
- A Population-based Gastrointestinal Transit Model Using Individual-Level Imaging Data.Pharmaceutical research · 2026Article
- The Finite Absorption Time Concept Guiding Model Informed Drug & Generics Development in Clinical Pharmacology.Pharmaceutical research · 2025Review
- A multicompartment population PK model to predict tenofovir and emtricitabine mucosal tissue concentrations for HIV prevention.CPT: pharmacometrics & systems pharmacology · 2023Article
- Rituximab pharmacokinetic and pharmacokinetic-pharmacodynamic evaluation based on a study in diffuse large B-cell lymphoma: Influence of tumor size on pharmacokinetic and assessment of pharmacokinetic similarity.CPT: pharmacometrics & systems pharmacology · 2023Article
- Application of Deep Neural Networks as a Prescreening Tool to Assign Individualized Absorption Models in Pharmacokinetic Analysis.Pharmaceutics · 2021Article
- Individualized Absorption Models in Population Pharmacokinetic Analyses.CPT: pharmacometrics & systems pharmacology · 2020Article
- A Minimal Continuous-Time Markov Pharmacometric Model.The AAPS journal · 2017Article
- Empirical models for fitting of oral concentration time curves with and without an intravenous reference.Journal of pharmacokinetics and pharmacodynamics · 2017Article
- Mechanism-Based Modeling of Gastric Emptying Rate and Gallbladder Emptying in Response to Caloric Intake.CPT: pharmacometrics & systems pharmacology · 2016Article
- Development of a Novel Simplified PBPK Absorption Model to Explain the Higher Relative Bioavailability of the OROS® Formulation of Oxybutynin.The AAPS journal · 2016Article
- Population pharmacogenetic pharmacokinetic modeling for flip-flop phenomenon of enteric-coated mycophenolate sodium in kidney transplant recipients.European journal of clinical pharmacology · 2014Article
- Article
- Use of partial AUC (PAUC) to evaluate bioequivalence--a case study with complex absorption: methylphenidate.Pharmaceutical research · 2013Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Absorption models used in the estimation of pharmacokinetic drug characteristics from plasma concentration data are generally empirical and simple, utilizing no prior information on gastro-intestinal (GI) transit patterns. Our aim was to develop and evaluate an estimation strategy based on a mechanism-based model for drug absorption, which takes into account the tablet movement through the GI transit. This work is an extension of a previous model utilizing tablet movement characteristics derived from magnetic marker monitoring (MMM) and pharmacokinetic data. The new approach, which replaces MMM data with a GI transit model, was evaluated in data sets where MMM data were available (felodipine) or not available (diclofenac). Pharmacokinetic profiles in both datasets were well described by the model according to goodness-of-fit plots. Visual predictive checks showed the model to give superior simulation properties compared with a standard empirical approach (first-order absorption rate + lag-time). This model represents a step towards an integrated mechanism-based NLME model, where the use of physiological knowledge and in vitro–in vivo correlation helps fully characterize PK and generate hypotheses for new formulations or specific populations.
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