ArticleJournal of pharmacokinetics and pharmacodynamics2017
Empirical models for fitting of oral concentration time curves with and without an intravenous reference.
Article in Journal of pharmacokinetics and pharmacodynamics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Pharmacokinetic Simulation and Area under the Curve Estimation of Drugs Subject to Enterohepatic Circulation.Pharmaceutics · 2024Article
- Is the One-Compartment Model with First Order Absorption a Useful Approximation?Pharmaceutical research · 2023Article
- Dependence of Bioavailability on Mean Absorption Time: What Does It Tell Us?The AAPS journal · 2023Article
- Relationship Between Dissolution Rate in Vitro and Absorption Rate in Vivo of Ketamine Prolonged-Release Tablets.European journal of drug metabolism and pharmacokinetics · 2023Article
- Analysis of Complex Absorption After Multiple Dosing: Application to the Interaction Between the P-glycoprotein Substrate Talinolol and Rifampicin.Pharmaceutical research · 2022Article
- Usefulness of continuous probability distributions of rates for modelling radionuclide biokinetics in humans and animals.Scientific reports · 2019Article
Corrections and comments
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Authors and funding
1 author.
Funding
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Abstract
Appropriate model selection is important in fitting oral concentration-time data due to the complex character of the absorption process. When IV reference data are available, the problem is the selection of an empirical input function (absorption model). In the present examples a weighted sum of inverse Gaussian density functions (IG) was found most useful. It is shown that alternative models (gamma and Weibull density) are only valid if the input function is log-concave. Furthermore, it is demonstrated for the first time that the sum of IGs model can be also applied to fit oral data directly (without IV data). In the present examples, a weighted sum of two or three IGs was sufficient. From the parameters of this function, the model-independent measures AUC and mean residence time can be calculated. It turned out that a good fit of the data in the terminal phase is essential to avoid parameter biased estimates. The time course of fractional elimination rate and the concept of log-concavity have proved as useful tools in model selection.
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Registered trials
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