Clinical Utility of Current NNRTIs and Perspectives of New Agents in This Class under Development
Bibliographic record
Abstract
Highly active antiretroviral therapy (HAART) has significantly reduced the number of deaths caused by AIDS. However, the antiviral efficacy of HAART comprising protease inhibitors (PIs) and nucleoside reverse transcriptase inhibitors (NRTIs) is frequently accompanied by a decrease in patients' quality of life. PI-based therapies often fail due to poor adherence caused by heavy pill burden, complex dosing schedules and undesirable side effects. The current trend is to switch from PI-based to PI-sparing regimens consisting of non-nucleoside reverse transcriptase inhibitors (NNRTIs) and NRTIs. Despite some encouraging results from NNRTI-containing therapies, two major concerns in using the currently available NNRTIs remain: 1) low genetic barrier to the emergence of resistance and 2) cross-resistance due to single mutations that often render the whole class of NNRTIs ineffective. Clearly, new and improved NNRTIs are needed to address these concerns.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".