[SS09] Enhancing Drug Development and Patient Care through Model Informed Drug Development

[SS09-04] Bayesian exposure-response analyses to justify the clinical dose of valemetostat for adult T-cell leukemia/lymphoma

*Masato Fukae¹ (1. Daiichi Sankyo Co., Ltd. (Japan))

Keywords:

Pharmacometrics,Model-Informed Drug Development,Bayesian Analysis

The presenter will showcase how a novel application of a Bayesian approach enhances a model-informed drug development with a case of valemetostat. Valemetostat is an oral inhibitor of enhancer of zeste homolog (EZH) 2 and EZH1 approved in Japan for the treatment of adult T-cell leukemia/lymphoma (ATLL), which is known as rare cancer, in 2022. To support the approved daily dose of 200 mg and inform dose adjustments in certain subpopulations, Bayesian exposure-response analyses were conducted using data from two clinical trials. The Bayesian approach employed spike and slab priors, allowing covariate analyses even with limited data. The analyses included two efficacy endpoints, overall response by central and investigator assessments in patients with ATLL (n = 38, 150-200 mg), and six safety endpoints in patients with non-Hodgkin lymphoma (n = 102, 150-300 mg), which included grade 3+ laboratory values for anemia, absolute neutrophil count decreased, and platelet count decreased; any grade 3+ treatment-emergent adverse event (TEAE); and dose reductions and dose interruptions due to TEAEs. A slightly positive relationship was observed between unbound exposure and efficacy endpoints. A steeper relationship was observed in safety endpoints, compared with efficacy. Candidate covariate effects, except intercepts of the baseline laboratory values, were regularized via the spike and slab priors; only the laboratory values for corresponding hematologic TEAEs were shown to be of substantial impact. The definition of target exposure range was predefined as exposure range providing satisfactory efficacy and acceptable safety. The target exposure range was established as 184-887 ng·h/mL using the developed exposure-response models, within the range of available exposure data. The simulated exposure range considering inter-individual variability from separately developed population pharmacokinetic model showed that 200 mg could reach target exposure in the overall population and across subpopulations of interest, supporting the use of valemetostat 200 mg in patients with ATLL. In conclusion, the utility of logistic regressions in a Bayesian framework with spike and slab priors, in which all the covariate effects were included and simultaneously estimated, was demonstrated.