Critical Issues in Therapeutic Drug Monitoring of Antiretroviral Drugs
Bibliographic record
Abstract
The interest in therapeutic drug monitoring (TDM) of antiretroviral drugs is growing rapidly. For the protease inhibitors, and to a lesser extent for the non-nucleoside reverse transcriptase inhibitors, relationships between plasma drug concentrations and their efficacy and toxicity have been identified. Furthermore, the pharmacokinetics of especially the protease inhibitors vary widely between patients, suggesting a role for TDM to individualize antiretroviral therapy. Recently, randomized, prospective clinical trials evaluating the role of TDM in the management of HIV-1-infected patients showed promising results. However, there are still many questions to be answered before large-scale introduction of TDM can be justified (e.g., which pharmacokinetic parameter should be optimized, and what is the minimal effective concentration). This review summarizes the basis for TDM of antiretroviral drugs and discusses the problems and prospects of this potential tool in the care for HIV-1-infected individuals.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".