Abstract LB094: KisoBody: Development and pre-clinical assessment of a novel multispecific antibody platform
Bibliographic record
Abstract
Abstract Monoclonal antibody therapy has revolutionized cancer treatment by addressing a variety of mechanisms from interfering with signaling to checkpoint inhibition. Bispecific antibodies double the number of therapeutic mechanisms addressed by each antibody to improve clinical outcomes. A substantial advance in therapeutic antibodies is increasing the number of mechanisms addressable per molecule to three or beyond to improve efficacy and safety. The KisoBody platform was developed to address the need for multispecific antibodies that are highly customizable and easy to manufacture. The KisoBody platform is based on heavy chain only antibodies (VHH) in conjunction with human Fc. The compact stable nature of VHH antibodies make them ideal building blocks for multidomain antibodies. The overall size of the KisoBody starts at approximately 140 kDa. The KisoBody can be assembled with wild type Fc domain to facilitate large scale manufacturing processes and maintain clinically relevant pharmacokinetics. Expression of several KisoBodies in CHO cells produced titers ranging from 2.3 to 4.4 g/L cell culture. Conventional two-step purification with protein A affinity chromatography following by size-exclusion chromatography resulted in proteins with purities of between 95.5 % and 99.5%. The pharmacokinetics of the KisoBody are consistent with that of canonical monoclonal antibodies of around 200 hours half-life in mice. The modular design of the KisoBody platform leads to very straightforward customization of the tumor targeting domains and the domains used for recruitment of other cell types, or to interfere with other cancer functions of therapeutic significance. The trispecific KisoBody presented here, KBI-436 has the ability to target tumor cells through binding to dopamine receptor 2 while simultaneously engaging the immune system through checkpoint inhibitors. The three VHH binding domains engage multiple mechanisms of action. The binding activity of the individual domains was tested in vitro. KBI-436 is easily manufactured using CHO cells, yielding a titer of greater than 3.5 g/L cell culture. Following a purification, a purity of greater than 98 % was achieved. The anti-tumor effects of KBI-436 were demonstrated in vivo in a number of human PBMC co-engraftment murine models of human SCLC. This molecule is being advanced to clinical trials in dopamine receptor positive solid tumors. Citation Format: Richard Wargachuk, Dominic Hou, Claire Bonfils, Nicolas Morin, Shugang Yao, Milica Krstic, Yun Cui, Jacynthe L. Toulouse, Donald Gagné, Elijus Undzys, Alex Zhou, Emily Chen, Ashwani Gupta, Luis DaCruz, David Young. KisoBody: Development and pre-clinical assessment of a novel multispecific antibody platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB094.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".