Abstract 3914: ZW49, a HER2-targeted biparatopic antibody-drug conjugate for the treatment of HER2-expressing cancers
Bibliographic record
Abstract
Abstract Therapies targeting HER2 have transformed the treatment of patients with HER2-expressing breast and gastric cancers. Unfortunately, many patients recur following HER2-targeted treatments and new therapies are needed. Multiple antibody-drug conjugate (ADC) technologies are being explored in this setting, some of which utilize the anti-HER2 antibody trastuzumab. Here we present the preclinical characterization of a new anti-HER2 biparatopic ADC, ZW49, which is generated from the conjugation of a novel N-acyl sulfonamide auristatin payload to the inter-chain disulfide bond cysteines of the bispecific anti-HER2 IgG1 antibody ZW25, via a protease cleavable linker. A series of in vitro and in vivo experiments were performed to characterize ZW49 as a potential therapeutic candidate. In cellular binding assays, it was confirmed that the payload conjugation to ZW25 did not affect the antibody's binding to HER2-expressing cells. ZW49 displayed potent in vitro cytotoxicity in multiple cancer cell lines expressing HER2 and was efficacious in multiple patient-derived xenograft (PDX) models. In mice bearing the HBCx-13b HER2 3+ PDX, two doses of ZW49 administered two weeks apart generated tumor regressions. Furthermore, preliminary results from PDX models with lower levels of HER2 expression treated with ZW49 also generated regressions. In nonhuman primates ZW49 administered intravenously every two weeks for three doses was well tolerated. Based on these findings, we are proceeding with further development of ZW49 as a therapeutic candidate in HER2-expressing cancers. Citation Format: Kevin J. Hamblett, Phil W. Hammond, Stuart D. Barnscher, Vincent K. Fung, Rupert H. Davies, Grant R. Wickman, Andrea Hernandez, Tong Ding, Adam S. Galey, Geoffrey C. Winters, Jamie R. Rich, John S. Babcook. ZW49, a HER2-targeted biparatopic antibody-drug conjugate for the treatment of HER2-expressing cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3914.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".