Evidence map›Paper›PMID 39435882›Full record

ArticleClinical and translational science2024

Elucidation of DPP-4 involvement in systemic distribution and renal reabsorption of linagliptin by PBPK modeling with a cluster Gauss-Newton method.

Ryo Nakamura, Takashi Yoshikado, Yasunori Aoki, Yuichi Sugiyama, Koji Chiba

Abstract read
In one paragraph

Article in Clinical and translational science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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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

5 authors.

Ryo NakamuraLaboratory of Clinical Pharmacology, Yokohama University of Pharmacy, Yokohama-shi, Kanagawa, Japan.
Takashi YoshikadoLaboratory of Clinical Pharmacology, Yokohama University of Pharmacy, Yokohama-shi, Kanagawa, Japan.ORCID 0009-0003-2773-9761
Yasunori AokiLaboratory of Quantitative System Pharmacokinetics/Pharmacodynamics, Josai International University, Tokyo, Japan.ORCID 0000-0002-5881-2023
Yuichi SugiyamaLaboratory of Quantitative System Pharmacokinetics/Pharmacodynamics, Josai International University, Tokyo, Japan.ORCID 0000-0002-8452-8835
Koji ChibaLaboratory of Clinical Pharmacology, Yokohama University of Pharmacy, Yokohama-shi, Kanagawa, Japan.ORCID 0000-0001-7600-7813

Funding

Ministry of Education, Culture, Sports, Science, and Technology in Japan 22H02789Ministry of Education, Culture, Sports, Science, and Technology in Japan 24K09925
6 · The paper itself

Abstract

The dipeptidyl peptidase-4 (DPP-4) inhibitor linagliptin (LNG) exhibits target-mediated drug disposition (TMDD) in clinical settings, characterized by saturable binding to plasma soluble DPP-4 (sDPP-4) and tissue transmembrane DPP-4 (tDPP-4). Previous studies have indicated that saturable renal reabsorption of LNG contributes to its nonlinear urinary excretion observed in humans and wild-type mice, but not in Dpp-4 knockout mice. To elucidate the mechanisms underlying these complex phenomena, including DPP-4-related renal reabsorption of LNG, we employed physiologically-based pharmacokinetic (PBPK) modeling combined with a cluster Gauss-Newton method (CGNM). The CGNM facilitated the exploration of parameters in rat and human PBPK models for LNG and the determination of parameter identifiability. Through PBPK-CGNM analysis using reported autoradiography data ([

Indexed as

Dipeptidyl Peptidase 4Dipeptidyl-Peptidase IV InhibitorsLinagliptinModels, BiologicalRenal ReabsorptionAnimalsHumansKidneyMaleMiceMice, KnockoutRatsTissue DistributionDipeptidyl Peptidase 4Dipeptidyl-Peptidase IV InhibitorsDPP4 protein, humanDPP4 protein, ratLinagliptin

Identifiers

PMID39435882
PMCPMC11494486

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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.