Zigakibart demonstrates clinical safety and efficacy in a Phase 1/2 trial of healthy volunteers and patients with IgA nephropathy
Bibliographic record
Abstract
INTRODUCTION: Zigakibart is a humanized IgG4 monoclonal antibody that binds the cytokine A Proliferation-Inducing Ligand (APRIL, also known as TNFSF13). APRIL is a critical factor in immunoglobulin (Ig) A nephropathy (IgAN) pathogenesis. METHODS: Here, we report healthy volunteers (63 overall) and 100-week data from an ongoing Phase 1/2 clinical trial in 40 patients with IgAN (NCT03945318) treated with zigakibart. RESULTS: In healthy volunteers, zigakibart was well tolerated following intravenous administration of single doses ranging from 10-1350 mg or multiple doses ranging from 50-450 mg every two weeks. Zigakibart exposure increased in a dose-proportional manner, with corresponding durable reductions in levels of free APRIL, IgA and IgM, and to a lesser extent, IgG. In patients with IgAN, zigakibart 600 mg, administered subcutaneously every two weeks, was well tolerated with no treatment-emergent adverse events leading to study drug discontinuation or death. A 60% reduction in proteinuria and sustained estimated glomerular filtration rate stabilization were observed at week 100. There was a notable decrease in hematuria, as well as rapid and durable reductions in IgA, galactose-deficient IgA (Gd-IgA1), and IgM levels, with a modest reduction in IgG. CONCLUSIONS: Overall, zigakibart demonstrated robust pharmacological activity, and clinical evidence shows an acceptable safety profile with clinically meaningful proteinuria reduction and sustained estimated glomerular filtration rate stabilization in patients with IgAN, providing a potentially disease-modifying approach for the treatment of IgAN. The effects of zigakibart on proteinuria and long-term kidney function in adults with IgAN are being evaluated in the ongoing phase 3 BEYOND study (NCT05852938).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".