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Record W2981827356 · doi:10.1371/journal.pone.0223969

A drug interaction study investigating the effect of Rifabutin on the pharmacokinetics of Maraviroc in healthy subjects

2019· article· en· W2981827356 on OpenAlexafffund
Mona Ghannad, Michelle K. Dennehy, Charles la Porte, Isabelle Seguin, Danielle C. Tardiff, Ranjeeta Mallick, Elham Sabri, G. Zhang, Salmaan Kanji, D. William Cameron

Bibliographic record

VenuePLoS ONE · 2019
Typearticle
Languageen
FieldMedicine
TopicMalaria Research and Control
Canadian institutionsUniversity of OttawaOttawa Hospital
FundersViiV HealthcareUniversity of OttawaOttawa Hospital Research InstitutePfizer
KeywordsMaravirocRifabutinPharmacokineticsPharmacologyCmaxOral administrationMedicineDrug interactionChemistryInternal medicineHuman immunodeficiency virus (HIV)Immunology

Abstract

fetched live from OpenAlex

Effects of steady-state rifabutin on the pharmacokinetics of steady-state maraviroc were investigated in fourteen healthy adult female and male volunteers. Maraviroc 300 mg twice daily (BID) was given orally with food for fifteen days. On day six, rifabutin 300 mg once daily (QD, P.O.) was added to the regimen. Formal pharmacokinetic (PK) sampling was performed on days five and fifteen. Individual plasma drug concentration-time data for maraviroc, and rifabutin on day fifteen, were obtained using validated High Performance Liquid Chromatography (HPLC) tandem Mass Spectrometry (MS/MS). Rifabutin steady state exposure was comparable to data in the literature. Maraviroc area under the curve (AUC) and minimum plasma concentration (Clast or Cmin) were reduced by 17% and 30% respectively when co-administered with rifabutin. No unexpected or serious adverse eventsoccurred. Based on the reduced exposure of maraviroc observed in this study, increasing the dose of maraviroc may be studied to normalize its moderately reduced exposure following rifabutin co-administration, a moderate inducer of CYP3A4.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.204
Threshold uncertainty score0.192

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.038
GPT teacher head0.315
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2019
Admission routes2
Has abstractyes

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