The Use of a Sum of Inverse Gaussian Functions to Describe the Absorption Profile of Drugs Exhibiting Complex Absorption

Csajka, Chantal; Drover, David R.; Verotta, Davide

doi:10.1007/s11095-005-5266-8

Cited by 27 publications

(14 citation statements)

References 18 publications

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“…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. Weibull distribution, inverse Gaussian distribution) [11][12][13][14] are employed (the partial derivatives in the FUNCA will have to be specified accordingly). T1=0 T2=0 T3=0 T4=0 T5=0 T6=0 T7=0 DOSE1=0 DOSE2=0 DOSE3=0 DOSE4=0 DOSE5=0 DOSE6=0 DOSE7=0 ENDIF IF (DOSENO == 1) THEN T1=TIME DOSE1=AMT ENDIF IF (DOSENO == 2) THEN T2=TIME DOSE2=AMT ENDIF IF (DOSENO == 3) THEN T3=TIME DOSE3=AMT ENDIF IF (DOSENO == 4) THEN T4=TIME DOSE4=AMT ENDIF IF (DOSENO == 5) THEN T5=TIME DOSE5=AMT ENDIF IF (DOSENO == 6) THEN T6=TIME DOSE6=AMT ENDIF IF (DOSENO == 7 (1) The 0.1-hourly sampling after first dose is only designed to obtain a nicer initial absorption curve for visual presentation.…”

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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“…As such, they commonly fail when used for predictions outside the range of data used to establish them. Examples of these kinds of pharmacokinetic models include those with sum-of-inverse-Gaussian functions to describe drug absorption profiles (Csajka et al 2005) or Bayesian p-splines to estimate pharmacokinetic parameters ( Jullion et al 2009). By contrast, a purely mechanistic model incorporates physiologically based assumptions about the mechanisms controlling the system.…”

Section: 2mentioning

confidence: 99%

Physiologically Based Modeling of Food Digestion and Intestinal Microbiota: State of the Art and Future Challenges. An INFOGEST Review

Feunteun

Al-Razaz

Dekker

et al. 2021

Annu. Rev. Food Sci. Technol.

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This review focuses on modeling methodologies of the gastrointestinal tract during digestion that have adopted a systems-view approach and, more particularly, on physiologically based compartmental models of food digestion and host–diet–microbiota interactions. This type of modeling appears very promising for integrating the complex stream of mechanisms that must be considered and retrieving a full picture of the digestion process from mouth to colon. We may expect these approaches to become more and more accurate in the future and to serve as a useful means of understanding the physicochemical processes occurring in the gastrointestinal tract, interpreting postprandial in vivo data, making relevant predictions, and designing healthier foods. This review intends to provide a scientific and historical background of this field of research, before discussing the future challenges and potential benefits of the establishment of such a model to study and predict food digestion and absorption in humans. Expected final online publication date for the Annual Review of Food Science and Technology, Volume 12 is March 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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“…Semi-mechanistic approaches for drug absorption such as transit compartment absorption and deconvolution method using the sum of inverse Gaussian functions were then tested. (21)(22)(23) Allometric scaling was used to adjust for the effect of body weight on disposition parameters with allometric exponents fixed to 0.75 for clearance (CL) parameters and 1 for volumes of distribution (V). ( 24) Besides total body weight, fat-free mass (FFM) and normal fat mass (NFM) were tested as alternative descriptors to characterize the size of drug-clearing organs and blood flows through them and to explore the possibility that MPA may distribute differentially between muscle or fat.…”

Section: Accepted Articlementioning

confidence: 99%

A Semimechanistic Pharmacokinetic Model for Depot Medroxyprogesterone Acetate and Drug–Drug Interactions With Antiretroviral and Antituberculosis Treatment

Francis

Mngqibisa

McIlleron

et al. 2021

Clin Pharma and Therapeutics

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Depot medroxyprogesterone acetate (DMPA) is an injectable hormonal contraceptive, widely used by women of childbearing potential living with HIV and/or tuberculosis. As medroxyprogesterone acetate (MPA) is a CYP3A4 substrate, drug-drug interactions (DDIs) with antiretroviral or antituberculosis treatment may lead to subtherapeutic MPA concentrations (<0.1 ng/mL), resulting in contraception failure, when DMPA is dosed at 12week intervals. A pooled population pharmacokinetic analysis with 744 plasma MPA concentrations from 138 women treated with DMPA and antiretroviral/antituberculosis treatment across three clinical trials was performed. Monte Carlo simulations were performed to predict the percentage of participants with subtherapeutic MPA concentrations and to derive alternative dosing strategies. MPA clearance increased by 24.7% with efavirenz co-administration. Efavirenz plus antituberculosis treatment (rifampicin+isoniazid) increased clearance by 52.4%. Conversely, lopinavir/ritonavir and nelfinavir decreased clearance (28.7% Accepted ArticleThis article is protected by copyright. All rights reserved and 15.8%, respectively), but lopinavir/ritonavir also accelerated MPA's appearance into the systemic circulation, thus shortening the terminal half-life. A higher risk of subtherapeutic MPA concentrations at week 12 was predicted on a typical 60-kg woman on efavirenz (4.99%) and efavirenz with antituberculosis treatment (6.08%) when compared to MPA alone (2.91%).This risk increased in women with higher body weight. Simulations show that re-dosing every 8-10 weeks circumvents the risk of subtherapeutic MPA exposure associated with these DDIs. Dosing DMPA every 8-10 weeks should eliminate the risk of subtherapeutic MPA exposure caused by co-administered efavirenz and/or antituberculosis treatment, thus reducing the risk of contraceptive failure. Main text

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The Use of a Sum of Inverse Gaussian Functions to Describe the Absorption Profile of Drugs Exhibiting Complex Absorption

Cited by 27 publications

References 18 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)

Physiologically Based Modeling of Food Digestion and Intestinal Microbiota: State of the Art and Future Challenges. An INFOGEST Review

A Semimechanistic Pharmacokinetic Model for Depot Medroxyprogesterone Acetate and Drug–Drug Interactions With Antiretroviral and Antituberculosis Treatment

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