Resistance profile of the new nucleoside reverse transcriptase inhibitor apricitabine
Bibliographic record
Abstract
Apricitabine is a novel deoxycytidine nucleoside reverse transcriptase inhibitor (NRTI) currently in clinical development for the treatment of HIV infection. Apricitabine shows antiviral activity in vitro against HIV-1 strains and clinical isolates with mutations in the reverse transcriptase that confer resistance to other NRTIs, including M184V, thymidine analogue mutations (TAMs), nucleoside-associated mutations such as L74V and certain mutations at codon 69. Apricitabine has shown activity in treatment-experienced HIV-1-infected patients with NRTI resistance (with M184V and up to five TAMs) as well as in treatment-naive patients. Resistance to apricitabine is slow to develop in vitro and there has been little evidence of development of resistance to apricitabine in clinical use thus far, including patients receiving apricitabine for up to 48 weeks. The resistance profile of apricitabine suggests there is a low potential for cross-resistance with the currently available NRTIs and, thus, apricitabine may provide a treatment option for treatment-experienced HIV-1-infected patients with resistance to other NRTIs. In particular, the activity of apricitabine in the presence of the M184V mutation, which confers high-level resistance to lamivudine and emtricitabine, lends it to being used as a replacement for deoxycytidine analogues in patients who have failed treatment with lamivudine or emtricitabine.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".