Evidence map›Paper›PMID 36050545›Full record

ArticlePharmaceutical research2023

Physiologically based Pharmacokinetic Models under the Prism of the Finite Absorption Time Concept.

Di Wu, Athanasios A Tsekouras, Panos Macheras, Filippos Kesisoglou

Abstract read
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In one paragraph

Article in Pharmaceutical research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Review
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  5. IVIVC Revised.Pharmaceutical research · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Di WuPharmaceutical Sciences and Clinical Supply, Merck & Co., Inc., Rahway, NJ, 07065, USA.
Athanasios A TsekourasDepartment of Chemistry, Laboratory of Physical Chemistry, National and Kapodistrian University of Athens, Athens, Greece.
Panos MacherasPharmaInformatics Unit, ATHENA Research Center, Athens, Greece.
Filippos KesisoglouPharmaceutical Sciences and Clinical Supply, Merck & Co., Inc., Rahway, NJ, 07065, USA. filippos_kesisoglou@merck.com.ORCID http://orcid.org/0000-0002-2805-0662

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To date, mechanistic modeling of oral drug absorption has been achieved via the use of physiologically based pharmacokinetic (PBPK) modeling, and more specifically, physiologically based biopharmaceutics model (PBBM). The concept of finite absorption time (FAT) has been developed recently and the application of the relevant physiologically based finite time pharmacokinetic (PBFTPK) models to experimental data provides explicit evidence that drug absorption terminates at a specific time point. In this manuscript, we explored how PBBM and PBFTPK models compare when applied to the same dataset. A set of six compounds with clinical data from immediate-release formulation were selected. Both models resulted in absorption time estimates within the small intestinal transit time, with PBFTPK models generally providing shorter time estimates. A clear relationship between the absorption rate and the product of permeability and luminal concentration was observed, in concurrence with the fundamental assumptions of PBFTPK models. We propose that future research on the synergy between the two modeling approaches can lead to both improvements in the initial parameterization of PBPK/PBBM models but to also expand mechanistic oral absorption concepts to more traditional pharmacometrics applications.

Indexed as

Intestinal AbsorptionModels, BiologicalAdministration, OralBiopharmaceuticsComputer SimulationPermeabilitySolubilitycorrelationfinite absorption timeoral absorptionPBFTPKPBPK modeling

Identifiers

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.