HIV drug resistance against strand transfer integrase inhibitors
Bibliographic record
Abstract
Integrase strand transfer inhibitors (INSTIs) are the newest class of antiretroviral drugs to be approved for treatment and act by inhibiting the essential HIV protein integrase from inserting the viral DNA genome into the host cell's chromatin. Three drugs of this class are currently approved for use in HIV-positive individuals: raltegravir (RAL), elvitegravir (EVG), and dolutegravir (DTG), while cabotegravir (CAB) and bictegravir (BIC) are currently in clinical trials. RAL and EVG have been successful in clinical settings but have relatively low genetic barriers to resistance. Furthermore, they share a high degree of cross-resistance, which necessitated the development of so-called second-generation drugs of this class (DTG, CAB, and BIC) that could retain activity against these resistant variants. In vitro selection experiments have been instrumental to the clinical development of INSTIs, however they cannot completely recapitulate the situation in an HIV-positive individual. This review summarizes and compares all the currently available information as it pertains to both in vitro and in vivo selections with all five INSTIs, and the measured fold-changes in resistance of resistant variants in in vitro assays. While the selection of resistance substitutions in response to RAL and EVG bears high similarity in patients as compared to laboratory studies, there is less concurrence regarding the "second-generation" drugs of this class. This highlights the unpredictability of HIV resistance to these inhibitors, which is of concern as CAB and BIC proceed in their clinical development.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".