A phase 2, open‐label, randomized, multiple‐dose study evaluating Inarigivir in treatment‐naïve patients with chronic hepatitis B
Bibliographic record
Abstract
BACKGROUND/AIMS: Novel agents acting against hepatitis B virus (HBV) are needed to improve HBsAg seroclearance or termed as 'functional cure'. Inarigivir (retinoic acid-inducible gene I agonist) has immunomodulatory and direct antiviral actions against HBV. We aimed to determine the safety and efficacy of Inarigivir for the treatment of HBV infection. PATIENTS/METHODS: 80 treatment-naïve patients were randomized in 4 ascending dose cohorts to receive 12 weeks of Inarigivir 25, 50, 100, 200 mg or placebo in a ratio of 4:1. All patients were then given tenofovir for another 12 weeks. RESULTS: Least squares (LS) mean reductions in HBV DNA from baseline increased with higher doses of Inarigivir (0.6116 in 25 mg and 1.5774 in 200 mg groups vs. 0.0352 in placebo group) (95% CI 0.9518-0.2011 and 1.921-1.1634 respectively). LS mean changes in HBV RNA and HBsAg from baseline ranged from -0.3856 to -0.5794 versus -0.1474 and -0.0956 to -0.1818 versus +0.0026 in Inarigivir-treated versus placebo groups respectively. During the tenofovir-treated period, LS mean reductions in HBsAg in the Inarigivir-treated groups ranged from 0.1709 to 0.3529 versus 0.1984 in the placebo group. Inarigivir-treated groups showed mean reductions in ALT from baseline between 23.3 and 33.8 versus 0.7 U/L in the placebo group. Treatment-emergent adverse events related to Inarigivir and placebo occurred in 4.7% and 6.3% patients respectively. CONCLUSIONS: Twelve-week Inarigivir up to 200 mg dose was associated with a reduction of HBV DNA, HBV RNA and antigen levels. A trend for greater HBsAg reduction was observed in Inarigivir pre-treated patients after switching to tenofovir.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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 teacher head, 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".