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Record W3162292226 · doi:10.1016/j.coviro.2021.04.014

Remdesivir for the treatment of Covid-19: the value of biochemical studies

2021· review· en· W3162292226 on OpenAlexafffund
Matthias Götte

Bibliographic record

VenueCurrent Opinion in Virology · 2021
Typereview
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health ResearchGilead Sciences
KeywordsProofreadingProdrugBiologyRNANucleotideVirologyDrugPopulationCoronavirus disease 2019 (COVID-19)Antiviral drugComputational biologySevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Mechanism (biology)PolymeraseDNAVirusPharmacologyGeneticsMedicineGene

Abstract

fetched live from OpenAlex

The nucleotide analogue prodrug remdesivir remains the only FDA-approved antiviral small molecule for the treatment of infection with SARS-CoV-2. Biochemical studies revealed that the active form of the drug targets the viral RNA-dependent RNA polymerase and causes delayed chain-termination. Delayed chain-termination is incomplete, but the continuation of RNA synthesis enables a partial escape from viral proofreading. Remdesivir becomes embedded in the copy of the RNA genome that later serves as a template. Incorporation of an incoming nucleotide triphosphate is now inhibited by the modified template. Knowledge on the mechanism of action matters. Enzymatic inhibition links to antiviral effects in cell cultures, animal models and viral load reduction in patients, which provides the logical chain that is expected for a direct acting antiviral. Hence, remdesivir also serves as a benchmark in current drug development efforts that will hopefully lead to orally available treatments to the benefit of a broader population.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.002

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 head0.372
GPT teacher head0.554
Teacher spread0.182 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations31
Published2021
Admission routes2
Has abstractyes

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