Late Breaking Abstract - ZW1528: A dual-targeting bispecific antibody to broadly suppress airway inflammation by inhibiting IL-4Ra and IL-33 pathways
Bibliographic record
Abstract
IL-33 is a key proinflammatory cytokine associated with airway inflammation and tissue remodelling in chronic obstructive pulmonary disease (COPD). In addition, IL-4Ra signalling plays the major role in promoting Type 2 (T2) inflammation in some patients. ZW1528 is a bispecific antibody targeting IL-4Ra and IL-33 designed for dual blockade of key mediators of airway inflammation. ZW1528 was constructed using Azymetric™ technology with IgG-like geometry and Fc optimization. Cell cultures and primary immune cells (PBMCs) from healthy donors and COPD patients were used to characterize IL-4Ra or IL-33 blockade in vitro. Pharmacokinetics (PK) and biomarkers of dual blockade were investigated in non-human primates (NHP) and transgenic mice. ZW1528 has high affinity for IL-4Ra and IL-33 with potent blockade of IL-4/13, and IL-33 signalling comparable to clinical benchmark monoclonal antibody controls. ZW1528 shows in vitro inhibition of T2 and non-T2 responses in PBMCs of COPD patients, illustrated by downregulation of IgE receptors and reduced IFNg release. ZW1528 elicits biomarkers of IL-33 and IL-4Ra engagement in vivo and reduces lung inflammation in murine models. The bispecific has antibody-like PK in rodents and NHPs and extended serum half-life via Fc optimization. Notably, in primary human cell models, ZW1528 shows dual IL-4Ra/IL-33 blockade beyond that seen with clinical benchmark antibody combinations. The results highlight the ability of ZW1528 to inhibit key cytokines involved in pathology of COPD. This concomitant inhibition may translate into broader suppression of airway inflammation, opening avenues for efficient treatment of patients with COPD.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.008 |
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".