Abstract A012: Discovery and characterization of Casdatifan (AB521), a clinical-stage, potent, and selective Hypoxia-Inducible Factor (HIF)-2α inhibitor
Bibliographic record
Abstract
Abstract Introduction. The microenvironment of solid tumors is known to be hypoxic and requires induction of genes associated with metabolism, growth, proliferation, angiogenesis, and erythropoiesis for tumor cells to survive and metastasize. Hypoxia-inducible factors (HIFs) are the central driving force for the cellular response to hypoxia and regulate a vast array of these genes. HIF-2α protein levels are tightly regulated post-translationally in an oxygen-dependent manner. Hypoxic conditions or aberrations in the Von-Hippel Lindau (VHL) ubiquitin ligase complex lead to HIF-2α stabilization and transcription of various pro-tumorigenic gene sets. The inhibition of HIF-2α has been demonstrated to be an effective strategy to mitigate tumor growth in the clinic with the recent approval of belzutifan for the treatment of advanced metastatic clear cell renal cell carcinoma (ccRCC). However, belzutifan suffers from saturated drug exposure and peripheral PD effects at its approved dose regimen, casting uncertainty whether optimal intra-tumoral inhibition of HIF-2α was achieved in these studies. Herein, we present the discovery and characterization of casdatifan, a potent and selective small molecule HIF-2α inhibitor, with pharmacokinetic properties optimized to enable deeper PD effects and robust intra-tumoral HIF-2α inhibition. Methods. Applying a pharmacophore mapping and structure-based design approach, we identified multiple novel series of small molecule HIF-2α inhibitors. Interrogation of structure activity relationships and pharmacokinetic trends culminated in the discovery of casdatifan. The potency of casdatifan was evaluated using a suite of biochemical and cell-based assays. Efficacy and pharmacodynamic markers were also evaluated in mice bearing established A498 and 786-O ccRCC xenograft tumors treated with casdatifan. Results. Casdatifan was found to avidly bind the HIF-2α PAS-B domain and potently block HIF-2α-mediated gene transcription under physiologically relevant conditions. Additionally, robust antitumor activity was observed in mouse ccRCC xenograft models following oral administration of casdatifan. Casdatifan exhibits a favorable preclinical pharmacokinetic (PK) profile. In healthy volunteers (ARC-14, NCT05117554), casdatifan showed a favorable PK profile featuring a terminal half-life of 18-24 hours. No evidence of saturable drug absorption has been observed, with dose-proportional increase in exposure across the evaluated dose range. Potent HIF-2α inhibition is demonstrated by dose-dependent reductions in serum EPO, an established peripheral PD marker for HIF-2α inhibition. Conclusions. Extensive optimization of a novel series of HIF-2α inhibitors culminated in the discovery of casdatifan. The PK/PD profile for casdatifan is consistent with a potential best-in-class HIF-2α inhibitor, with deeper reductions of peripheral biomarkers than has been reported by clinical competition. Continued evaluation of casdatifan in patients with ccRCC and other advanced solid tumors is underway (ARC-20, NCT05536141). Citation Format: Kenneth V. Lawson, Artur Mailyan, Guillaume Mata, Joel W. Beatty, Samuel L. Drew, Jeremy T. A. Fournier, Jaroslaw Kalisiak, Ahn T. Tran, Kai Yu, Brandon R. Rosen, Clayton Hardman, Matthew Epplin, Kelsey E. Sivick, Dana Piovesan, Suan Liu, Elain Ginn, Cesar A. Meleza, Lisa Seitz, Tzuling Cheng, Amber Pham, Mohammad Ghasemi, Paul G. Foster, Matthew J. Walters, Manmohan Leleti, Jay P. Powers. Discovery and characterization of Casdatifan (AB521), a clinical-stage, potent, and selective Hypoxia-Inducible Factor (HIF)-2α inhibitor [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Optimizing Therapeutic Efficacy and Tolerability through Cancer Chemistry; 2024 Dec 9-11; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(12_Suppl):Abstract nr A012.
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 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 | 0.000 | 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) | 0.000 | 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".