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Record W2027642737 · doi:10.1517/14656560903176446

New antiretroviral drugs: a review of the efficacy, safety, pharmacokinetics, and resistance profile of tipranavir, darunavir, etravirine, rilpivirine, maraviroc, and raltegravir

2009· review· en· W2027642737 on OpenAlexaffabout
Christine Hughes, Linda Robinson, Alice Tseng, Rodger D. MacArthur

Bibliographic record

VenueExpert Opinion on Pharmacotherapy · 2009
Typereview
Languageen
FieldMedicine
TopicHIV/AIDS drug development and treatment
Canadian institutionsUniversity of TorontoWindsor Regional HospitalToronto General HospitalUniversity of Alberta
Fundersnot available
KeywordsDarunavirEtravirineRaltegravirMaravirocRilpivirineMedicinePharmacologyDrugIntensive care medicineVirologyHuman immunodeficiency virus (HIV)Viral loadAntiretroviral therapy

Abstract

fetched live from OpenAlex

BACKGROUND: The introduction and approval of new antiretroviral agents in the US and Canada bring new opportunities and new challenges. Arguably, for the first time ever, clinicians have the drugs necessary to achieve the goal of suppressing HIV RNA to levels less than 50 copies/mL in even the most treatment-experienced patients and in those with extensive drug-limiting resistance mutations. However, the use of these new agents is complicated by many drug-drug interactions and--to some extent--pre-existing mutations. To derive maximum durability from the use of these newer drugs, a thorough understanding of their indications and limitations is critical. OBJECTIVE: To thoroughly review the six most recently approved or soon-to-be-approved antiretroviral drugs in the US and Canada: tipranavir, darunavir, etravirine, rilpivirine, maraviroc, and raltegravir. METHODS: Discussion of the indications for, and pharmacokinetics, resistance profile, activity, toxicity, and clinical trials results of, the six new agents. RESULTS/CONCLUSIONS: These six new agents have resulted in marked progress towards the goal of being able to provide HIV-infected individuals with the drugs necessary to achieve decades of durable suppression of HIV without substantial 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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.915
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.028
GPT teacher head0.378
Teacher spread0.349 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations84
Published2009
Admission routes2
Has abstractyes

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