Evidence map›Paper›PMID 36678526›Full record

ArticlePharmaceuticals (Basel, Switzerland)2022

Prospective Prediction of Dapaconazole Clinical Drug-Drug Interactions Using an In Vitro to In Vivo Extrapolation Equation and PBPK Modeling.

Natalícia de Jesus Antunes, Fernanda de Lima Moreira, Karin Kipper, Lewis Couchman, Daniel Temponi Lebre, Atholl Johnston, Gilberto De Nucci

Open access · goldAbstract read
In one paragraph

Article in Pharmaceuticals (Basel, Switzerland), 2022. 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
0.7field-weighted citation impact, top 30% 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, 4 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

7 authors at 5 institutions in 3 countries.

Natalícia de Jesus AntunesDepartment of Pharmacology, Faculty of Medical Sciences, State University of Campinas (UNICAMP), Campinas 13083-881, SP, Brazil.ORCID 0000-0002-7820-552X
Fernanda de Lima MoreiraFaculty of Pharmacy, Federal University of Rio de Janeiro, Rio de Janeiro 21941-902, RJ, Brazil.
Karin KipperInstitute of Chemistry, University of Tartu, 14a Ravila Street, 50411 Tartu, Estonia.ORCID 0000-0002-7295-8993
Lewis CouchmanAnalytical Services International (ASI) Ltd., St George's-University of London, Cranmer Terrace, London SW17 0RE, UK.
Daniel Temponi LebreCenter for Applied Mass Spectrometry (CEMSA), São Paulo 05508-000, SP, Brazil.
Atholl JohnstonAnalytical Services International (ASI) Ltd., St George's-University of London, Cranmer Terrace, London SW17 0RE, UK.
Gilberto De NucciDepartment of Pharmacology, Faculty of Medical Sciences, State University of Campinas (UNICAMP), Campinas 13083-881, SP, Brazil.
St George's, University of London · GBUniversidade de São Paulo · BRUniversidade Estadual de Campinas (UNICAMP) · BRUniversidade Federal do Rio de Janeiro · BRUniversity of Tartu · EE

Funding

São Paulo Research Foundation 2016/22506-1
6 · The paper itself

Abstract

This study predicted dapaconazole clinical drug−drug interactions (DDIs) over the main Cytochrome P450 (CYP) isoenzymes using static (in vitro to in vivo extrapolation equation, IVIVE) and dynamic (PBPK model) approaches. The in vitro inhibition of main CYP450 isoenzymes by dapaconazole in a human liver microsome incubation medium was evaluated. A dapaconazole PBPK model (Simcyp version 20) in dogs was developed and qualified using observed data and was scaled up for humans. Static and dynamic models to predict DDIs following current FDA guidelines were applied. The in vitro dapaconazole inhibition was observed for all isoforms investigated, including CYP1A2 (IC50 of 3.68 µM), CYP2A6 (20.7 µM), 2C8 (104.1 µM), 2C9 (0.22 µM), 2C19 (0.05 µM), 2D6 (0.87 µM), and 3A4 (0.008−0.03 µM). The dynamic (PBPK) and static DDI mechanistic model-based analyses suggest that dapaconazole is a weak inhibitor (AUCR > 1.25 and <2) of CYP1A2 and CYP2C9, a moderate inhibitor (AUCR > 2 and <5) of CYP2C8 and CYP2D6, and a strong inhibitor (AUCR ≥ 5) of CYP2C19 and CYP3A, considering a clinical scenario. The results presented may be a useful guide for future in vivo and clinical dapaconazole studies.

Indexed as

cytochrome P450dapaconazolehuman liver microsomesinhibitionin vitro evaluationIVIVEPBPK model

Identifiers

PMID36678526
PMCPMC9861162
OpenAlexW4313260012

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.