根据 GDUFA 监管科学研究计划,美国 FDA 公开鼓励使用定量方法和建模(quantitative methods and modeling,QMM)方法以及模型集成证据(model-integrated evidence,MIE)来支持仿制药产品的开发和审批(2,3,4,5,6)。MIE方法利用虚拟生物等效性(virtual bioequivalence,VBE)试验结果指导关键体内研究的设计,并通过支持考虑体外测试并减少其它推荐的常规体内研究(包括但不限于 PK、PD 或可比性临床终点研究(3))的替代 BE 方法来获得药品批准。对于复杂仿制药和口服剂型,QMM 方法的应用可以并且正在用于支持替代 BE 方法和监管审评(2,3,7,8,9,10,11,12,13,14)。这些定量方法包括机械建模,例如基于生理的药代动力学(PBPK)建模和计算流体动力学 (CFD) 建模,定量临床药理学工具集,例如群体药代动力学(PPK)方法,以及先进的数据分析方法。
除资助 QMM 方法的内部和外部研究及其在支持药品开发和批准的 MIE 中的整合外,FDA 还努力改善制药行业和 FDA 之间的互动框架。在这些互动的范围内,FDA 引入了模型主文件(MMF)的概念,以促进模型共享和模型接受,并最终推进仿制药开发以及简化监管提交和评估(15,16)。
MIE 对于非复杂和复杂仿制药的促进作用是通过考虑药品质量属性来表征和预测体内性能,为减少人体测试的研究设计提供信息,以及支持解决与某些药品相关的挑战的替代 BE 方法。
此次研讨会极大地加强了行业、学术界和 FDA 之间的沟通和协调。尽管研讨会与会者指出了在监管决策中实施 QMM 所面临的挑战,但为开发最佳实践奠定了基础,以验证其是否达到预期目的,并将其应用于支持非复杂和复杂仿制药的替代 BE 评估。研讨会的成果将用于促进 QMM 方法的应用,并制定将此类方法纳入仿制药开发计划和监管申报的最佳实践。
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