Abstract 3997: Preclinical characterization of ARX517, a next-generation anti-PSMA antibody drug conjugate for the treatment of metastatic castration-resistant prostate cancer
Bibliographic record
Abstract
Abstract Prostate cancer is the most common cancer, and the second leading cause of cancer death, among men in the United States. Metastatic castration-resistant prostate cancer (mCRPC) is an advanced stage of disease in which patients ultimately fail androgen-deprivation therapies and exhibit a poor survival rate. Recently, prostate-specific membrane antigen (PSMA) has been validated as a prostate cancer tumor antigen with its over-expression in prostate tumors and low level of expression in select normal tissues. Using an expanded genetic code to create Engineered Precision Biologics (EPBs), Ambrx has developed ARX517, an anti-PSMA targeted next-generation antibody drug conjugate (ADC), for treatment of mCRPC patients. ARX517 is composed of a humanized anti-PSMA antibody site-specifically conjugated to drug linker AS269 (a potent tubulin inhibitor), yielding a drug-to-antibody ratio of 2. After binding to PSMA expressed on the surface of tumor cells, ARX517 is internalized and delivers a cytotoxic payload which inhibits tubulin polymerization and induces cellular apoptosis. In vitro testing of ARX517 in prostate cancer cell lines with variable PSMA expression demonstrated highly specific and potent sub-nanomolar activity in cells with high PSMA expression. To minimize premature payload release, ARX517 employs a non-cleavable PEG linker and stable oxime conjugation chemistry to enhance stability in circulation. ARX517 exhibited a long terminal half-life and high serum exposure in mice. The serum stability of ARX517 should effectively deliver more payload to target tumor cells, and in multiple CDX and PDX prostate cancer models, ARX517 showed dose-dependent anti-tumor activity in both enzalutamide-sensitive and enzalutamide-resistant models. Repeat dose toxicokinetic studies in non-human primates demonstrated ARX517 was tolerated at exposures well above therapeutic exposures in mouse pharmacology studies, indicating a wide therapeutic index. In summary, ARX517 elicited highly specific, potent cell killing in cell lines with high PSMA expression, inhibited tumor growth in enzalutamide-sensitive and enzalutamide-resistant CDX and PDX models, demonstrated a tolerable safety profile in cynomolgus monkeys, and has a clear therapeutic index based on preclinical serum exposure data. The strong preclinical data and recent clinical validation of PSMA as a mCRPC target provide rationale for evaluation of ARX517 as a potential prostate cancer treatment. ARX517 is currently in a Phase 1 dose escalation trial (ARX517-2011 [NCT04662580]) in the United States. Citation Format: Lillian Skidmore, David Mills, Ji Young Kim, Prathap Shastri, Nick A. Knudsen, Jeff Steen, Jay Nelson, Ying Buechler, Feng Tian, Shawn Zhang. Preclinical characterization of ARX517, a next-generation anti-PSMA antibody drug conjugate for the treatment of metastatic castration-resistant prostate cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3997.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
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".