Agoram Balaji M
Department of Clinical Pharmacology, Pfizer Inc., Ramsgate Road, Sandwich, UK.
Br J Clin Pharmacol. 2009 Feb;67(2):153-60. doi: 10.1111/j.1365-2125.2008.03297.x. Epub 2008 Dec 11.
Recent regulatory guidance has highlighted the importance of using pharmacokinetic-pharmacodynamic (PK-PD) modelling in the selection of starting doses in first-in-human trials of high-risk biologics. However, limited examples exist in literature illustrating this procedure.
An interpretation of the recommended dose-selection methodology and the minimum anticipated biological effect level (MABEL) principle, contained in the updated European Medicines Agency guidance on risk-mitigation strategies for first-in-human studies, is presented. Some literature and simulation-based examples of the application of PK-PD modelling principles to starting dose selection using in vitro and in vivo data under the MABEL paradigm are highlighted, along with the advantages and limitations of this approach.
To illustrate the use of pharmacokinetic-pharmacodynamic (PK-PD) models to select rational starting doses in clinical trials within the minimum anticipated biological effect level (MABEL) principle using literature data and through simulations.
The new European Medicines Agency guidance on starting dose selection of high-risk biologics was analysed considering the basic pharmacological properties and preclinical testing limitations of many biologics. The MABEL approach to dose selection was illustrated through simulations and through literature-reported examples on the selection of starting doses for biologics such as antibodies based on in vitro biomarker data, in vivo PK and PK-PD data.
Literature reports indicating the use of preclinical pharmacological and toxicological data to select successfully safe starting doses in line with the MABEL principle are summarized. PK-PD model-based simulations of receptor occupancy for an anti-IgE antibody system indicate that the relative abundance of IgE in animal models and patients and the turnover rate of the IgE-antibody complex relative to the off-rate of the antibody from IgE are important determinants of in vivo receptor occupancy.
Mechanistic PK-PD models are capable of integrating preclinical in vitro and in vivo data to select starting doses rationally in first-in-human trials. Biological drug-receptor interaction dynamics is complex and multiple factors affect the dose-receptor occupancy relationship. Thus, these factors should be taken into account when selecting starting doses.
近期的监管指南强调了在高风险生物制品首次人体试验中使用药代动力学-药效学(PK-PD)模型来选择起始剂量的重要性。然而,文献中说明此程序的示例有限。
对欧洲药品管理局(EMA)关于首次人体研究风险缓解策略的最新指南中推荐的剂量选择方法和最低预期生物学效应水平(MABEL)原则进行了解读。重点介绍了一些基于文献和模拟的PK-PD建模原则在MABEL范式下使用体外和体内数据进行起始剂量选择的示例,以及该方法的优缺点。
利用文献数据并通过模拟,说明如何在最低预期生物学效应水平(MABEL)原则下,使用药代动力学-药效学(PK-PD)模型在临床试验中选择合理的起始剂量。
考虑到许多生物制品的基本药理学特性和临床前测试的局限性,对EMA关于高风险生物制品起始剂量选择的新指南进行了分析。通过模拟以及文献报道的基于体外生物标志物数据、体内药代动力学(PK)和PK-PD数据选择生物制品(如抗体)起始剂量的示例,阐述了MABEL剂量选择方法。
总结了表明使用临床前药理学和毒理学数据成功按照MABEL原则选择安全起始剂量的文献报告。基于PK-PD模型对抗IgE抗体系统的受体占有率进行的模拟表明,动物模型和患者体内IgE的相对丰度以及IgE-抗体复合物的周转率相对于抗体从IgE上的解离速率是体内受体占有率的重要决定因素。
机制性PK-PD模型能够整合临床前体外和体内数据,在首次人体试验中合理选择起始剂量。生物药物-受体相互作用动力学复杂,多种因素影响剂量-受体占有率关系。因此,在选择起始剂量时应考虑这些因素。