Application of a Gamma Model of Absorption to Oral Cyclosporin

Debord, Jean; Risco, Eléonore; Harel, Michel; Meur, Yann Le; Büchler, Mathias; Lachâtre, Gérard; Guellec, Chantal Le; Marquet, Pierre

doi:10.2165/00003088-200140050-00004

Cited by 52 publications

(19 citation statements)

References 20 publications

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“…In fact, the transit compartment absorption model is equivalent to a model with absorption lag time distributed in a gamma distribution [9,10]. In this regard, the strategy of dose superimposition presented in this article can easily be extended to absorption models with multiple dose administration where other probability distributions (e.g.…”

Section: Discussionmentioning

confidence: 99%

Implementation of dose superimposition to introduce multiple doses for a mathematical absorption model (transit compartment model)

Shen

Boeckmann²,

Vick

2012

J Pharmacokinet Pharmacodyn

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A mathematical absorption model (e.g. transit compartment model) is useful to describe complex absorption process. However, in such a model, an assumption has to be made to introduce multiple doses that a prior dose has been absorbed nearly completely when the next dose is administered. This is because the drug input cannot be determined from drug depot compartment through integration of the differential equation system and has to be analytically calculated. We propose a method of dose superimposition to introduce multiple doses; thereby eliminating the assumption. The code for implementing the dose superimposition in WinNonlin and NONMEM was provided. For implementation in NONMEM, we discussed a special case (SC) and a general case (GC). In a SC, dose superimposition was implemented solely using NM-TRAN abbreviated code and the maximum number of the doses that can be administered for any subject must be pre-defined. In a GC, a user-supplied function (FUNCA) in FORTRAN code was defined to perform dose superimposition to remove the restriction that the maximum number of doses must be pre-defined.

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Section: Discussionmentioning

confidence: 99%

Implementation of dose superimposition to introduce multiple doses for a mathematical absorption model (transit compartment model)

Shen

Boeckmann²,

Vick

2012

J Pharmacokinet Pharmacodyn

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“…4). Previously, transit model ("tanks-in-series") approaches have been used to describe signal transduction (62,71), and similar approaches have been used to model absorption (12,66). Weiss used the gamma distribution to model drug residence times (67), and since then, similar approaches have been applied to other areas (26,55).…”

Section: Discussionmentioning

confidence: 99%

Population Pharmacokinetics of Rifampin in Pulmonary Tuberculosis Patients, Including a Semimechanistic Model To Describe Variable Absorption

Wilkins

Savic

Karlsson

et al. 2008

Antimicrob Agents Chemother

139

132

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This article describes the population pharmacokinetics of rifampin in South African pulmonary tuberculosis patients. Three datasets containing 2,913 rifampin plasma concentration-time data points, collected from 261 South African pulmonary tuberculosis patients aged 18 to 72 years and weighing 28.5 to 85.5 kg and receiving regular daily treatment that included administration of rifampin (450 to 600 mg) for at least 10 days, were pooled. A compartmental pharmacokinetic model was developed using nonlinear mixed-effects modeling. Variability in the shape of the absorption curve was described using a flexible transit compartment model, in which a delay in the onset of absorption and a gradually changing absorption rate were modeled as the passage of drug through a chain of hypothetical compartments, ultimately reaching the absorption compartment. A previously described implementation was extended to allow its application to multiple-dosing data. The typical population estimate of oral clearance was 19.2 liters ⅐ h ؊1 , while the volume of distribution was estimated to be 53.2 liters. Interindividual variability was estimated to be 52.8% for clearance and 43.4% for volume of distribution. Interoccasional variability was estimated for CL/F (22.5%) and mean transit time during absorption (67.9%). The use of single-drug formulations was found to increase both the mean transit time (by 104%) and clearance (by 23.6%) relative to fixed-dose-combination use. A strong correlation between clearance and volume of distribution suggested substantial variability in bioavailability, which could have clinical implications, given the dependence of treatment effectiveness on exposure. The final model successfully described rifampin pharmacokinetics in the population studied and is suitable for simulation in this context.

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“…al. [2]. The 3 parameters are determined by the use of global (simulated annealing) and local (Powell) non-linear optimization.…”

Section: Introductionmentioning

confidence: 99%

The use of a physiologically based pharmacokinetic model to evaluate deconvolution measurements of systemic absorption

Levitt¹

2003

BMC Clin Pharmacol

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Background: An unknown input function can be determined by deconvolution using the systemic bolus input function (r) determined using an experimental input of duration ranging from a few seconds to many minutes. The quantitative relation between the duration of the input and the accuracy of r is unknown. Although a large number of deconvolution procedures have been described, these routines are not available in a convenient software package.

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Application of a Gamma Model of Absorption to Oral Cyclosporin

Abstract: This model could simplify the Bayesian monitoring of cyclosporin therapy.

Cited by 52 publications

References 20 publications

Implementation of dose superimposition to introduce multiple doses for a mathematical absorption model (transit compartment model)

Implementation of dose superimposition to introduce multiple doses for a mathematical absorption model (transit compartment model)

Population Pharmacokinetics of Rifampin in Pulmonary Tuberculosis Patients, Including a Semimechanistic Model To Describe Variable Absorption

The use of a physiologically based pharmacokinetic model to evaluate deconvolution measurements of systemic absorption

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