Pharmacokinetics, Safety, and Efficacy of Tipranavir Boosted With Ritonavir Alone or in Combination With Other Boosted Protease Inhibitors as Part of Optimized Combination Antiretroviral Therapy in Highly Treatment-Experienced Patients (BI Study 1182.51)
Bibliographic record
Abstract
BACKGROUND: Given the limited treatment options for patients with high-level resistance, antiretroviral (ARV) regimens based on concomitant use of 2 ritonavir (RTV)-boosted protease inhibitors (PIs) were considered a therapeutic option. METHODS: Boehringer Ingelheim (BI) study 1182.51 examined the pharmacokinetic profile, safety, and efficacy of RTV-boosted tipranavir (TPV/r), alone and in combination with comparator PIs (CPIs) in 315 triple-class-experienced, HIV-infected patients. RESULTS: Two weeks after single PI therapy, the addition of TPV/r reduced plasma trough levels 52%, 80%, and 56% for lopinavir (LPV), saquinavir (SQV), and amprenavir (APV) recipients, respectively. After 2 weeks, a TPV/r-only regimen reduced HIV viral load (VL) by a median of 1.06 log(10) copies/mL. VL reductions at 2 weeks between single-boosted CPIs were difficult to compare, because the numbers of patients maintaining their previous failing PI after randomization were different. At week 4, patients initiating treatment with TPV-containing regimens sustained VL reduction (median decrease of 1.27 log(10) copies/mL). Patients adding TPV to regimens at week 2 achieved median reductions from a baseline of 1.19 log(10), 0.96 log(10), and 1.12 log(10) copies/mL at week 4 in dual-boosted LPV, SQV, and APV groups, respectively. At 24 weeks, VL reductions (median: -0.24 to -0.47 log(10) copies/mL) were comparable between treatment groups. CONCLUSIONS: The efficacy of a dual PI regimen depended on the presence of TPV, with additional recycled CPIs having limited activity, even in drug-resistant patient populations with plasma trough concentrations regarded as likely to be adequate in this study. No clear guidelines exist about ARV plasma trough concentrations in treatment-experienced patients, however.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".