Strategies for successful dose optimization in oncology drug development: a practical guide.

IF 1.2 4区 医学 Q4 PHARMACOLOGY & PHARMACY
Qiqi Deng, Lili Zhu, Brendan Weiss, Praveen Aanur, Lei Gao
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Abstract

Dose optimization is a critical challenge in drug development. Historically, dose determination in oncology has followed a divergent path from other non-oncology therapeutic areas due to the unique characteristics and requirements in Oncology. However, with the emergence of new drug modalities and mechanisms of drugs in oncology, such as immune therapies, radiopharmaceuticals, targeted therapies, cytostatic agents, and others, the dose-response relationship for efficacy and toxicity could be vastly varied compared to the cytotoxic chemotherapies. The doses below the MTD may demonstrate similar efficacy to the MTD with an improved tolerability profile, resembling what is commonly observed in non-oncology treatments. Hence, alternate strategies for dose optimization are required for new modalities in oncology drug development. This paper delves into the historical evolution of dose finding methods from non-oncology to oncology, highlighting examples and summarizing the underlying drivers of change. Subsequently, a practical framework and guidance are provided to illustrate how dose optimization can be incorporated into various stages of the development program. We provide the following general recommendations: 1) The objective for phase I is to identify a dose range rather than a single MTD dose for subsequent development to better characterize the safety and tolerability profile within the dose range. 2) At least two doses separable by PK are recommended for dose optimization in phase II. 3) Ideally, dose optimization should be performed before launching the confirmatory study. Nevertheless, innovative designs such as seamless II/III design can be implemented for dose selection and may accelerate the drug development program.

肿瘤药物研发中成功优化剂量的策略:实用指南。
剂量优化是药物开发中的一项重要挑战。从历史上看,由于肿瘤学的独特性和要求,肿瘤学的剂量确定一直与其他非肿瘤学治疗领域不同。然而,随着免疫疗法、放射性药物、靶向疗法、细胞抑制剂等新的药物模式和药物机制在肿瘤学中的出现,与细胞毒性化疗相比,疗效和毒性的剂量反应关系可能会有很大的不同。低于MTD的剂量可能具有与MTD相似的疗效,但耐受性有所改善,这与非肿瘤治疗中常见的情况类似。因此,在肿瘤药物开发的新模式中,需要有剂量优化的替代策略。本文深入探讨了从非肿瘤学到肿瘤学的剂量寻找方法的历史演变,重点举例说明并总结了变化的根本原因。随后,本文提供了一个实用框架和指南,说明如何将剂量优化纳入开发计划的各个阶段。我们提出以下一般性建议:1) I 期的目标是为后续开发确定一个剂量范围,而不是单一的 MTD 剂量,以便更好地描述剂量范围内的安全性和耐受性特征。2)建议在 II 期进行剂量优化时至少使用两个可通过 PK 分离的剂量。3) 理想情况下,剂量优化应在启动确证研究之前进行。然而,创新设计(如无缝 II/III 设计)可用于剂量选择,并可加快药物开发计划。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Biopharmaceutical Statistics
Journal of Biopharmaceutical Statistics 医学-统计学与概率论
CiteScore
2.50
自引率
18.20%
发文量
71
审稿时长
6-12 weeks
期刊介绍: The Journal of Biopharmaceutical Statistics, a rapid publication journal, discusses quality applications of statistics in biopharmaceutical research and development. Now publishing six times per year, it includes expositions of statistical methodology with immediate applicability to biopharmaceutical research in the form of full-length and short manuscripts, review articles, selected/invited conference papers, short articles, and letters to the editor. Addressing timely and provocative topics important to the biostatistical profession, the journal covers: Drug, device, and biological research and development; Drug screening and drug design; Assessment of pharmacological activity; Pharmaceutical formulation and scale-up; Preclinical safety assessment; Bioavailability, bioequivalence, and pharmacokinetics; Phase, I, II, and III clinical development including complex innovative designs; Premarket approval assessment of clinical safety; Postmarketing surveillance; Big data and artificial intelligence and applications.
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