Evidence map›Paper›PMID 37016156›Full record

ArticleThe AAPS journal2023

Dependence of Bioavailability on Mean Absorption Time: What Does It Tell Us?

Michael Weiss, Werner Siegmund

Abstract read
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In one paragraph

Article in The AAPS journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 54% of its field
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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Article
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

2 authors at 2 institutions in 1 country.

Michael WeissDepartment of Pharmacology, Martin Luther University Halle-Wittenberg, 06097, Halle, Germany.
Werner SiegmundDepartment of Clinical Pharmacology, Center of Drug Absorption and Transport (C_DAT), University Medicine Greifswald, Greifswald, Germany.
Martin Luther University Halle-Wittenberg · DEUniversitätsmedizin Greifswald · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The extent and rate of bioavailability are fundamental measures to characterize the pharmacokinetics of drugs after oral administration. Together with bioavailability (F), the mean absorption time (MAT) can be used to define the rate of bioavailability, i.e., the rate of drug absorption. Previous results suggest that F may depend on MAT. Estimates of F and MAT were obtained from the input function (sum of two inverse Gaussian functions) used to model the oral absorption process. The estimation was performed by population analysis (nonlinear mixed-effects modeling) based on data from bioavailability studies in healthy volunteers. For trospium and ketamine, F decreased significantly with increasing MAT, while for propiverine, a significant increase was observed. Thus, the interindividual variability in F could be largely attributed to the interindividual variability in MAT. For trospium and propiverine, the relative dispersion (normalized variance) of the absorption time distribution increased significantly with MAT. For trospium and propiverine, the plot of F versus MAT provides information about the effect of gastrointestinal transit on drug absorption. In contrast, an increase in hepatic extraction with increasing MAT is responsible for the dependence of F on MAT. The F versus MAT plot is suggested as a simple diagnostic tool in evaluating the results of bioavailability studies.

Indexed as

BenzilatesLiverAdministration, OralBiological AvailabilityHumansMuscarinic AntagonistsBenzilatesMuscarinic Antagonistspropiverineabsorption time distributionbioavailabilitygastrointestinal transitmean absorption time

Identifiers

PMID37016156
OpenAlexW4362596921

What OpenQuestion holds

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Registered trials

None linked

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.