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Record W2461594029 · doi:10.3851/imp3059

A Case of a Probable drug Interaction between Lurasidone and Atazanavir-Based Antiretroviral Therapy

2015· article· en· W2461594029 on OpenAlexaff
Mark Naccarato, Elise Hall, Alan Wai, Mario Ostrowski, Adriana Carvalhal

Bibliographic record

VenueAntiviral Therapy · 2015
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS drug development and treatment
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsAtazanavirLurasidoneCYP3A4PharmacologyRitonavirDrugPaliperidoneProtease inhibitor (pharmacology)Drug interactionTherapeutic drug monitoringAntipsychotic drugMedicineAntipsychoticCytochrome P450Antiretroviral therapyInternal medicineMetabolismHuman immunodeficiency virus (HIV)VirologyViral load

Abstract

fetched live from OpenAlex

The cytochrome P450 isoform that is primarily involved in the metabolism of the antipsychotic lurasidone is CYP3A4. Drugs that inhibit or induce this enzyme would then be expected to increase or decrease serum concentrations of lurasidone, respectively. Atazanavir, an HIV-1 protease inhibitor, has demonstrated to be an inhibitor of CYP3A4 and would be expected to increase the exposure of any drug metabolized by this enzyme. We report a case of an atazanavir-precipitated drug-drug interaction that led to elevated serum concentrations of lurasidone and associated clinical symptoms of drug toxicity.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.751
Threshold uncertainty score0.680

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.062
GPT teacher head0.320
Teacher spread0.258 · 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

Citations8
Published2015
Admission routes1
Has abstractyes

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