Bristol Myers Squibb Co.

Organic cation transporter 1 (OCT1, SLC22A1) is a key determinant in the hepatic disposition of cationic drugs, primarily supported by pharmacogenomic studies. However, evidence for OCT1-mediated drug-drug interactions (DDIs) remains limited. This study aimed to elucidate the role of OCT1 in DDIs using cynomolgus monkeys through comprehensive in vitro and in vivo experiments. Cynomolgus monkey OCT1 (cOCT1) shares 94.2% amino acid identity with human OCT1 (hOCT1). Transport assays in transfected human embryonic kidney 293 cells showed that sumatriptan, fenoterol, metformin, quinidine, and 1-methyl-4-phenylpyridinium were transported by cOCT1 at rates comparable to hOCT1 (less than 2-fold difference). The K_m and V_max values for cOCT1-mediated transport of sumatriptan and fenoterol were similar or within 2-fold to those of hOCT1 (K_m: 188 ± 56 vs 178 ± 25 and 1.6 ± 0.48 vs 0.73 ± 0.47 μM, respectively, V_max: 49.4 ± 8.3 vs 83.9 ± 5.2 and 124 ± 8.9 vs 158 ± 22 pmol/min per mg, respectively). Inhibition studies demonstrated that quinidine, rifamycin SV, and ketoprofen inhibited sumatriptan uptake in monkey hepatocytes to a similar extent as in human hepatocytes, with IC₅₀ values within a 2- to 3-fold range. In addition, axitinib, nintedanib, and erlotinib were identified as inhibitors of both cOCT1 and hOCT1. In vivo, coadministration of axitinib (15 mg/kg), nintedanib (40 mg/kg), and erlotinib (15 mg/kg) increased sumatriptan area under the plasma concentration-time curve from zero to 24 hours by 1.3, 2.0, and 1.9-fold, respectively, compared with sumatriptan alone (2 mg/kg). These findings underscore the crucial role of OCT1 in the hepatic disposition and DDIs of cationic drugs, and indicate that cynomolgus monkeys may serve as a valuable model for studying OCT1-mediated drug disposition and interactions. SIGNIFICANCE STATEMENT: This study provides the first evidence that cynomolgus monkey organic cation transporter 1 (OCT1) transport and inhibition characteristics closely align with its human ortholog. Consistent with our in vitro findings, coadministration of OCT1 inhibitors (axitinib, nintedanib, and erlotinib) significantly increased the systemic exposure of sumatriptan in monkeys. These findings offer valuable insights into the role of OCT1 in drug-drug interactions and highlight the potential of cynomolgus monkeys as a useful and potentially translational model for OCT1-mediated disposition and interactions.

Real‐world research has identified differences in effectiveness and safety between direct oral anticoagulants (DOACs) when used to reduce risks of stroke and systemic embolism in patients with atrial fibrillation. However, treatment decisions and subsequent outcomes are poorly understood in patients with atrial fibrillation who experience bleeding when receiving a DOAC.

A retrospective observational study was conducted using US claims data from Optum’s Clinformatics Data Mart Database (January 2012 through March 2024). The study population comprised adults with nonvalvular atrial fibrillation who initiated a DOAC and had a subsequent claim for bleeding. After propensity score matching, patients who persisted with the same DOAC after bleeding were compared with those who switched to another DOAC. The main outcomes were major bleeding and stroke/systemic embolism.

Among 59 620 apixaban initiators and 21 004 rivaroxaban initiators with bleeding while on therapy, 408 apixaban‐to‐rivaroxaban switchers were matched with 2040 persistent apixaban users, and 901 rivaroxaban‐to‐apixaban switchers were matched with 4505 persistent rivaroxaban users. Compared with persisting with apixaban following a bleeding event, apixaban‐to‐rivaroxaban switching was associated with a higher risk of major bleeding (hazard ratio [HR], 1.690 [95% CI, 1.130–2.527]) and a similar risk of stroke/systemic embolism (HR, 1.793 [95% CI, 0.765–4.202]). Compared with persisting with rivaroxaban, rivaroxaban‐to‐apixaban switching was associated with a lower risk of major bleeding (HR, 0.651 [95% CI, 0.460–0.920]) and a similar risk of stroke/systemic embolism (HR, 0.783 [95% CI, 0.371–1.652]).

These findings suggest that the choice of DOAC after a bleeding event can affect treatment outcomes in patients with atrial fibrillation.

Dose selection is a key decision to make in the early phase of drug development. Classical phase I/II dose-finding trials randomly assign a few doses and select the best among them. Response-adaptive assignment designs are more efficient but are still far from optimal. Recently, some researchers used machine learning (ML) methods such as contextual bandits (CB) to find the "optimal" dose and to investigate the asymptotic properties of the methods. We present a case study for oncology phase I/II dose-finding trial designs using Thompson sampling and Bayesian bootstrap for CB with either modeling clinical utility directly or jointly modeling efficacy and safety. We focus on practical questions such as the number of interim analyses to conduct and whether we should model the utility directly, jointly model efficacy and safety which compose the utility, or use a model independent approach such as multi-armed bandits, but not for a specific compound or tumor type. We also consider how to use weak informative prior information. We conducted an extensive simulation study and compared different combinations of design settings and modeling methods, under several feasible scenarios of the dose-response relationship. Based on simulation results, we make practical recommendations for the use of the proposed ML approach for phase I/II dose-finding trial designs.