Evidence map›Paper›PMID 30091221›Full record

ArticleCPT: pharmacometrics & systems pharmacology2018

PBPK Models for CYP3A4 and P-gp DDI Prediction: A Modeling Network of Rifampicin, Itraconazole, Clarithromycin, Midazolam, Alfentanil, and Digoxin.

Nina Hanke, Sebastian Frechen, Daniel Moj, Hannah Britz, Thomas Eissing, Thomas Wendl, Thorsten Lehr

Abstract read
In one paragraph

Article in CPT: pharmacometrics & systems pharmacology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 99 papers.

0numbers the graph read from it
0cells of the map it votes in
99citing 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

99 citing papers in PubMed.

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39 more citing papers are in PubMed but not listed here.

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.

Nina HankeClinical Pharmacy, Saarland University, Saarbrücken, Germany.
Sebastian FrechenClinical Pharmacometrics, Bayer AG, Leverkusen, Germany.
Daniel MojClinical Pharmacy, Saarland University, Saarbrücken, Germany.
Hannah BritzClinical Pharmacy, Saarland University, Saarbrücken, Germany.
Thomas EissingClinical Pharmacometrics, Bayer AG, Leverkusen, Germany.
Thomas WendlClinical Pharmacometrics, Bayer AG, Leverkusen, Germany.
Thorsten LehrClinical Pharmacy, Saarland University, Saarbrücken, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

According to current US Food and Drug Administration (FDA) and European Medicines Agency (EMA) guidance documents, physiologically based pharmacokinetic (PBPK) modeling is a powerful tool to explore and quantitatively predict drug-drug interactions (DDIs) and may offer an alternative to dedicated clinical trials. This study provides whole-body PBPK models of rifampicin, itraconazole, clarithromycin, midazolam, alfentanil, and digoxin within the Open Systems Pharmacology (OSP) Suite. All models were built independently, coupled using reported interaction parameters, and mutually evaluated to verify their predictive performance by simulating published clinical DDI studies. In total, 112 studies were used for model development and 57 studies for DDI prediction. 93% of the predicted area under the plasma concentration-time curve (AUC) ratios and 94% of the peak plasma concentration (C

Indexed as

Models, BiologicalAlfentanilATP Binding Cassette Transporter, Subfamily B, Member 1ClarithromycinCytochrome P-450 CYP3ADigoxinDrug InteractionsHumansItraconazoleMidazolamRifampinAlfentanilATP Binding Cassette Transporter, Subfamily B, Member 1ClarithromycinCYP3A4 protein, humanCytochrome P-450 CYP3ADigoxinItraconazoleMidazolamRifampin

Identifiers

PMID30091221
PMCPMC6202474

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.