A pharmacokinetic model for multiple sites discontinuous gastrointestinal absorption

Plusquellec, Y.; Efthymiopoulos, Constantin; Duthil, P.; Houin, Georges

doi:10.1016/s1350-4533(99)00060-0

Cited by 28 publications

(17 citation statements)

References 10 publications

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“…As noted in the introduction, the double peak phenomena is reported for piroxicam [4][5][6][7][8][9], ranitidine [10][11][12][13][14][15][16], talinolol [18,19], alprazolam [20], phenazopyridine [21] and many other drugs in humans. Ranitidine double peaks are reportedly caused by multiple site absorption [10,17].…”

Section: Resultsmentioning

confidence: 99%

“…Double peak absorption has been described with several orally administered drugs such as cimetidine [1,2], furosemide [3], piroxicam [4][5][6][7][8][9], ranitidine [10][11][12][13][14][15][16][17], talinolol [18,19], alprazolam [20] and phenazopyridine [21]. Several possible explanations are stated for double peak phenomena; some of the double or multiple peak phenomena can be explained sufficiently by a parallel first order absorption model or a multisegment absorption model.…”

Section: Introductionmentioning

confidence: 99%

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A simple pharmacokinetics subroutine for modeling double peak phenomenon

Mirfazaelian¹,

Mahmoudian²

2006

Biopharm. Drug Dispos.

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Double peak absorption has been described with several orally administered drugs. Numerous reasons have been implicated in causing the double peak. DRUG-KNT--a pharmacokinetic software developed previously for fitting one and two compartment kinetics using the iterative curve stripping method--was modified and a revised subroutine was incorporated to solve double-peak models. This subroutine considers the double peak as two hypothetical doses administered with a time gap. The fitting capability of the presented model was verified using four sets of data showing double peak profiles extracted from the literature (piroxicam, ranitidine, phenazopyridine and talinolol). Visual inspection and statistical diagnostics showed that the present algorithm provided adequate curve fit disregarding the mechanism involved in the emergence of the secondary peaks. Statistical diagnostic parameters (RSS, AIC and R2) generally showed good fitness in the plasma profile prediction by this model. It was concluded that the algorithm presented herein provides adequate predicted curves in cases of the double peak phenomenon.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A simple pharmacokinetics subroutine for modeling double peak phenomenon

Mirfazaelian¹,

Mahmoudian²

2006

Biopharm. Drug Dispos.

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“…Hepatic elimination is governed by allometrically scaled liver blood flow (Q H ) and the estimated hepatic extraction ratio (E H ). The systemic distribution of felodipine is described by a central observation compartment (8) and two peripheral compartments (9,10) separately to the intravenous data. An allometric relationship to bodyweight was assumed for disposition and elimination parameters.…”

Section: Technique Studies and Modelsmentioning

confidence: 99%

“…To model erratic absorption profiles such as multiple peak behavior, several empirical models have been proposed. Plusquellec et al proposed a discontinuous oral absorption model, following the absorption window concept to describe pharmacokinetic (PK) profiles with double peaks (9), then extended this to multiple peaks (10). Recently, Godfrey et al applied a parallel input model and a stepwise input rate function to describe multiple peak PK data (11).…”

Section: Introductionmentioning

confidence: 99%

A mechanism-Based Approach for Absorption Modeling: The Gastro-Intestinal Transit Time (GITT) Model

Hénin

Bergstrand

Standing

et al. 2012

AAPS J

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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 mechanismbased 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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“…Following oral drug intake, the dynamic changes in the luminal concentrations are described with the help of an intestinal transit function that assumes a Gaussian distribution of the drug mass within the tube [18,19] . In contrast to compartmental models, this approach avoids the strict compartmentalization of the various segments of the GI tract and, moreover, can easily consider bi‐directional transport of the drug that occurs during the peristaltic movements of the bowel [20–24] . On the other hand, the integration of the continuous tube model into a whole‐body PBPK model approach is mathematically challenging, because the mass flow through the GI tract is not described by means of ordinary differential equations.…”

Section: Introductionmentioning

confidence: 99%