HCV796
Bibliographic record
Abstract
UNLABELLED: Anti-hepatitis C virus (HCV) drug development has been challenged by a lack of experience with inhibitors inclusive of in vitro, animal model, and clinical study. This manuscript outlines activity and correlation across such a spectrum of models and into clinical trials with a novel selective nonstructural protein 5B (NS5B) polymerase inhibitor, HCV796. Enzyme assays yielded median inhibitory concentration (IC(50)) values of 0.01 to 0.14 microM for genotype 1, with half maximal effective concentration (EC(50)s) of 5 nM and 9 nM against genotype 1a and 1b replicons. In the chimeric mouse model, a 2.02 +/- 0.55 log reduction in HCV titer was seen with monotherapy, whereas a suboptimal dose of 30 mg/kg three times per day in combination with interferon demonstrated a 2.44 log reduction (P = 0.001 versus interferon alone) Clinical outcomes in combination with pegylated interferon and ribavirin have revealed additive efficacy in treatment naïve patients. Abnormal liver function test results were observed in 8% of HCV-796 patients treated for over 8 weeks, resulting in suspension of further trial activity. CONCLUSION: The RNA-dependent RNA polymerase inhibitor HCV796 demonstrated potent anti-HCV activity consistently through enzyme inhibition assays, subgenomic replicon, and chimeric mouse studies. Strong correlations of outcomes in the mouse model were seen with subsequent clinical trials, including a plateau in dose-related antiviral activity and additive impact from combination therapy with interferon. These outcomes demonstrate the utility of the range of in vitro and in vivo models now available for anti-HCV drug development and support the potential utility of polymerase inhibitors in future combination therapies for HCV treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.147 | 0.109 |
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".