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Record W2902172836 · doi:10.1021/acs.jmedchem.8b00843

The Journey of HIV-1 Non-Nucleoside Reverse Transcriptase Inhibitors (NNRTIs) from Lab to Clinic

2018· article· en· W2902172836 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Medicinal Chemistry · 2018
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS drug development and treatment
Canadian institutionsMerck Canada Inc. (Canada)
FundersNational Institute of Allergy and Infectious DiseasesGovernment of Shandong ProvinceScience and Engineering Research BoardNational Institutes of HealthUppsala UniversitetNational Natural Science Foundation of ChinaDepartment of Science and Technology, Ministry of Science and Technology, IndiaNational Institute of Mental HealthEuropean Molecular Biology LaboratoryShandong UniversityVillum Fonden
KeywordsEfavirenzEtravirineNevirapineRilpivirineReverse transcriptaseReverse-transcriptase inhibitorNucleoside Reverse Transcriptase InhibitorVirologyHuman immunodeficiency virus (HIV)ChemistryPharmacologyMedicineAntiretroviral therapyViral loadRNA

Abstract

fetched live from OpenAlex

Human immunodeficiency virus (HIV) infection is now pandemic. Targeting HIV-1 reverse transcriptase (HIV-1 RT) has been considered as one of the most successful targets for the development of anti-HIV treatment. Among the HIV-1 RT inhibitors, non-nucleoside reverse transcriptase inhibitors (NNRTIs) have gained a definitive place due to their unique antiviral potency, high specificity, and low toxicity in antiretroviral combination therapies used to treat HIV. Until now, >50 structurally diverse classes of compounds have been reported as NNRTIs. Among them, six NNRTIs were approved for HIV-1 treatment, namely, nevirapine (NVP), delavirdine (DLV), efavirenz (EFV), etravirine (ETR), rilpivirine (RPV), and doravirine (DOR). In this perspective, we focus on the six NNRTIs and lessons learned from their journey through development to clinical studies. It demonstrates the obligatory need of understanding the physicochemical and biological principles (lead optimization), resistance mutations, synthesis, and clinical requirements for drugs.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.390
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.015
GPT teacher head0.286
Teacher spread0.272 · 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