医学
生物标志物
安慰剂
生物仿制药
药效学
加药
美波利祖马布
临床试验
曲线下面积
随机对照试验
临床终点
内科学
药理学
肿瘤科
药代动力学
嗜酸性粒细胞
病理
生物化学
化学
替代医学
哮喘
作者
Victoria Gershuny,Qin Sun,Sarah J. Schrieber,Murali K. Matta,James L. Weaver,Ping Ji,Morasa Sheikhy,Cheng‐Hui Hsiao,Giri Vegesna,Aanchal Shah,Kristin Prentice,Jennifer Deering,Yow‐Ming Wang,David G. Strauss,Jeffry Florian
摘要
The US Food and Drug Administration (FDA) guidance describes how pharmacodynamic (PD) biomarkers can be used to address residual uncertainty and demonstrate no clinically meaningful differences between a proposed biosimilar and its reference product without relying on clinical efficacy end point(s). Pilot studies and modeling can inform dosing for such PD studies. To that end, we conducted a randomized, double-blinded, placebo-controlled, single-dose, parallel-arm clinical study in healthy participants to evaluate approaches to address information gaps, inform best practices for analysis of biomarker samples and study results, and apply emerging technologies in biomarker characterization. Seventy-two healthy participants (n = 8 per arm) received either placebo or 1 of 4 doses of the interleukin-5 inhibitors mepolizumab (3-24 mg) or reslizumab (0.1-0.8 mg/kg). A clinical study using doses lower than approved therapeutic doses was combined with modeling and simulation to evaluate the dose-response relationship of the biomarker eosinophils. There was no dose-response relationship for eosinophil counts due to variability, although the mepolizumab 24 mg and reslizumab 0.8 mg/kg doses showed clear effects. Published indirect-response models were used to explore eosinophil data across doses from this study and the unstudied therapeutic doses. Simulations were used to calculate typical PD metrics, such as baseline-adjusted area under the effect curve and maximum change from baseline. The simulation results demonstrate sensitivity of eosinophils as a PD biomarker and indicate doses lower than the approved doses would have PD responses overlapping with variability in the placebo arm. The simulation results further highlight the utility of model-based approaches in supporting use of PD biomarkers in biosimilar development.
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