Abstract 175: A Novel Orally-Active Small-Molecule Antagonist of the Platelet Protease-Activated Receptor-4, BMS-986120, Inhibits Arterial Thrombosis With Limited Impact on Hemostasis in Cynomolgus Monkeys
Bibliographic record
Abstract
Introduction: BMS-986120 (BMS) is a novel orally-active antagonist of protease-activated receptor-4 (PAR4), a human platelet thrombin receptor, and is in phase I clinical trial. The antithrombotic potential of BMS was studied in models of electrically-mediated carotid artery thrombosis and bleeding time (BT) in cynomolgus monkeys, which have platelet thrombin receptors similar to human. Methods: Individual anesthetized monkeys were given orally of BMS (0.2, 0.5,1 mg/kg) or vehicle (n=8/group) 2 hour before a combination of thrombosis, BT and ex vivo biomarker experiments. Aspirin alone (ASA, 4 mg/kg/h IV) or in combination with BMS (0.5, 1 mg/kg) was also studied (n=8/group). Thrombus weight (TW) reduction, BT increase over vehicle in kidney (KBT) and mesenteric artery (MBT), and platelet aggregation (PA) inhibition were determined. Peak PA responses to activation peptides selective for PAR4 (PAR4-AP, 12.5 μM) and PAR1 (PAR1-AP, 18 μM), ADP (20 μM), and collagen (5 μg/ml) were determined by whole blood aggregometry. Results: BMS comparably inhibited PA induced by PAR4-AP in human and monkey blood in vitro (IC 50 of 9.5±2.7 and 2.1±0.4 nM, respectively). In monkeys, BMS produced parallel rightward shifts in the log PA dose response to PAR4-AP without affecting maximum response, suggesting surmountable antagonism. BMS (1 mg/kg) did not inhibit PA induced by PAR1-AP, ADP and collagen, supporting selectivity. BMS (0.2, 0.5, 1 mg/kg) reduced TW by 35±5, 49±4, and 83±4%, respectively. Maximum KBT and MBT increases were only 2.2-fold and 1.8-fold, respectively. A maximum antiplatelet dose of ASA (4 mg/kg/h, n=8) slightly reduced TW by 12±2% and increased KBT and MBT by 2.2- and 2.7-fold, respectively. Co-administration of ASA and BMS (0.5 or 1 mg/kg) reduced TW by 54±3 and 95±2%, increased KBT by 3.1- and 3.6-fold, and increased MBT by 2.6- and 3.3-fold, respectively (n=8/group). In companion monkey studies, clopidogrel (0.3 mg/kg/day, n=6) alone reduced TW by 49±6%, but increased KBT and MBT by 7.3- and 8.1-fold, respectively. Conclusion: In monkeys, BMS alone or combined with ASA prevents occlusive carotid artery thrombosis with limited impact on BT, demonstrating a wider therapeutic window than the standard of care antiplatelet drugs, aspirin and clopidogrel.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".