Evidence map›Paper›PMID 28391404›Full record

ArticleClinical pharmacokinetics2017

Physiologically Based Pharmacokinetic Modeling of Renally Cleared Drugs in Pregnant Women.

André Dallmann, Ibrahim Ince, Juri Solodenko, Michaela Meyer, Stefan Willmann, Thomas Eissing, Georg Hempel

Abstract read
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Article in Clinical pharmacokinetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed
8.2field-weighted citation impact, top 2% 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

43 citing papers in PubMed, 82 citations in OpenAlex.

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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

7 authors at 2 institutions in 1 country.

André DallmannDepartment of Pharmaceutical and Medical Chemistry-Clinical Pharmacy, Westfälische Wilhelm-University Münster, 48149, Münster, Germany.
Ibrahim InceBayer AG, Drug Discovery, Pharmaceuticals, Systems Pharmacology & Medicine I, Kaiser-Wilhelm-Allee, 51373, Leverkusen, Germany. ibrahim.ince@bayer.com.ORCID 0000-0001-9036-7305
Juri SolodenkoBayer AG, ET-TD-ET Systems Pharmacology ONC, 51368, Leverkusen, Germany.
Michaela MeyerBayer AG, DD-CS Clinical Pharmacometrics, 42113, Wuppertal, Germany.
Stefan WillmannBayer AG, DD-CS Clinical Pharmacometrics, 42113, Wuppertal, Germany.
Thomas EissingBayer AG, Drug Discovery, Pharmaceuticals, Systems Pharmacology & Medicine I, Kaiser-Wilhelm-Allee, 51373, Leverkusen, Germany.
Georg HempelDepartment of Pharmaceutical and Medical Chemistry-Clinical Pharmacy, Westfälische Wilhelm-University Münster, 48149, Münster, Germany.
Bayer (Germany) · DEUniversity of Münster · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSince pregnant women are considerably underrepresented in clinical trials, information on optimal dosing in pregnancy is widely lacking. Physiologically based pharmacokinetic (PBPK) modeling may provide a method for predicting pharmacokinetic changes in pregnancy to guide subsequent in vivo pharmacokinetic trials in pregnant women, minimizing associated risks.

objectivesThe goal of this study was to build and verify a population PBPK model that predicts the maternal pharmacokinetics of three predominantly renally cleared drugs (namely cefazolin, cefuroxime, and cefradine) at different stages of pregnancy. It was further evaluated whether the fraction unbound (f

methodsBased on a recent literature review on anatomical and physiological changes during pregnancy, a pregnancy population PBPK model was built using the software PK-Sim

resultsThe pregnancy population PBPK model successfully predicted the pharmacokinetics of cefazolin, cefuroxime, and cefradine at all tested stages of pregnancy. All predicted plasma concentrations fell within a 2-fold error range and 85% of the predicted concentrations within a 1.25-fold error range. The f

conclusionPregnancy population PBPK models can provide a valuable tool to predict a priori the pharmacokinetics of predominantly renally cleared drugs in pregnant women. These models can ultimately support informed decision making regarding optimal dosing regimens in this vulnerable special population.

Indexed as

Models, BiologicalCefazolinCefuroximeCephradineComputer SimulationDose-Response Relationship, DrugFemaleHumansPharmaceutical PreparationsPharmacokineticsPregnancyRenal EliminationCefazolinCefuroximeCephradinePharmaceutical Preparations

Identifiers

PMID28391404
OpenAlexW2604693974

What OpenQuestion holds

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Read underepoch 390

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.