Pharmaceutical, clinical, and resistance information on doravirine, a novel non-nucleoside reverse transcriptase inhibitor for the treatment of HIV-1 infection
Bibliographic record
Abstract
As part of a combined antiretroviral regimen, doravirine is safe and effective at suppressing viral replication in both treatment-naive and treatment-experienced adults living with human immunodeficiency virus (HIV)-1 who have no history of drug resistance against doravirine.In virologically suppressed individuals switching to a combination of doravirine, lamivudine, and tenofovir disoproxil fumarate, no resistance was found after 48 weeks.In treatment-naive individuals, rare cases (<2%) of emergent drug resistance have been reported, often involving the development of substitutions at position V106.From these few clinical cases, it is inferred that crossresistance with other non-nucleoside reverse transcriptase inhibitors (NNRTIs) should be limited.In contrast, the use of doravirine as a second NNRTI should be evaluated on a case-by-case basis in the presence of pre-existing resistance.Importantly, doravirine remains active against K103N viruses in vitro, and limited clinical evidence suggests this to be the case in patients as well.Since K103N is by far the most prevalent (<70%) NNRTI substitution found in clinical practice, resistance against doravirine-based antiretroviral therapies is expected to be rare, even for treatment-experienced individuals.This review summarizes chemical, pharmacological, and clinical information about doravirine with an emphasis on drug resistance.The efficacy results from an early phase clinical trial evaluating doravirine in combination with islatravir are also provided.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".