Abstract P196: Novel hydrophilic drug linkers enable exatecan-based antibody-drug conjugates with promising physiochemical properties and in vivo activity
Bibliographic record
Abstract
Abstract The physiochemical properties of an antibody-drug conjugate (ADC) can impact its stability and pharmacokinetics/pharmacodynamics and are one of the key design attributes. Typically, ADCs with better hydrophilicity are less prone to aggregation and have lower systemic clearance and greater anti-tumor activities. However, the need of incorporating lipophilic payloads with enhanced bystander activity has posed significant challenges to ADC and linker design, especially at higher drug-antibody ratios (DAR). Here we present novel hydrophilic linkers that can greatly improve the hydrophilicity of ADCs conjugated to lipophilic payloads such as exatecan. Exatecan is camptothecin analogue that has failed as a small molecule drug in clinical trials due to lack of therapeutic window but retains considerable promise as an ADC payload because of its high potency and resistance to Pgp efflux. By introducing highly polar PEG, polyhydroxyl and/or polycarboxyl groups, we generated hydrophilic linkers that enable site specific, highly homogeneous conjugation of exatecan to multiple prototypical monoclonal antibodies at DAR8. The linkers may also allow for other DARs such as DAR4 and DAR16. These exatecan-based ADCs with novel hydrophilic linkers were evaluated for their binding affinity and stability and compared with corresponding naked antibodies and deruxtecan-based and conventional vedotin-based ADCs for hydrophilicity, pharmacokinetics, in vitro and in vivo anti-tumor activities. Safety assessments in cynomolgus monkeys have also been planned. ADCs conjugated with the novel hydrophilic linkers were stable at 37oC for 15 days, after 5 cycles of freeze-thaw, and at concentrations as high as 100 mg/mL, as assessed by visual inspection, hydrophobic interaction chromatography, and size-exclusion chromatography. Binding affinity to target-positive cell lines was similar to corresponding naked antibodies. At DAR8, these ADCs were more hydrophilic than deruxtecan-based ADCs and DAR2 species of conventional vedotin-based ADCs. These ADCs also demonstrated potent in vitro cell growth inhibition and induced comparable or stronger tumor regression with single or multiple dosing in multiple mouse xenograft models. The pharmacokinetics profiles of these ADCs are similar to those of the naked antibodies. In summary, our novel hydrophilic linkers can enable conjugation of exatecan-based ADCs at high DARs with favorable physiochemical properties, which result in robust stability, pharmacokinetics, potency, and the potential for a meaningful therapeutic window. Citation Format: Haidong Liu, Lei Wang, Julia Gavrilyuk, Tae Han, Baiteng Zhao, Xiao Shang. Novel hydrophilic drug linkers enable exatecan-based antibody-drug conjugates with promising physiochemical properties and in vivo activity [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2021 Oct 7-10. Philadelphia (PA): AACR; Mol Cancer Ther 2021;20(12 Suppl):Abstract nr P196.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".