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采用定制设计实验和新型多维稳健性图谱评估生物制剂。

Evaluation of a Biologic Formulation Using Customized Design of Experiment and Novel Multidimensional Robustness Diagrams.

机构信息

Drug Product Development and Operations, Biologics CMC, Teva Biopharmaceuticals USA, West Chester, Pennsylvania 19380.

Global Statistics, Teva Branded Pharmaceutical Products R&D, Inc., West Chester, Pennsylvania 19380.

出版信息

J Pharm Sci. 2018 Mar;107(3):797-806. doi: 10.1016/j.xphs.2017.10.024. Epub 2017 Oct 26.

Abstract

Formulation development includes selection of appropriate excipients to stabilize the active pharmaceutical ingredient throughout its recommended shelf life, against potential excursions in its life cycle and sometimes to aid in the delivery of therapeutics into the patient. Identity and quantity of every ingredient in a therapeutic formulation are critical to achieve their intended purpose. Deviations from a target composition can result in manufacturing, safety, and efficacy challenges. It is mandatory to establish robustness of a formulation for the expected changes in its composition arising from the qualified "process variability" of the impacting process steps during manufacture. The approach for carrying out a robustness study evolved through improved understanding of a therapeutic stability and exploration of new tools, including the quality by design elements strongly recommended by regulatory agencies. An approach is presented here to study formulation robustness in multidimensional space using a customized experimental design and novel multidimensional diagrams, which present a unique way of identifying robustness limits. The concept is universally applicable to any multivariate analysis and such diagrams would be useful to comprehend the outcome on all variables at a glance. Interpretation of these diagrams is discussed, some of which are applicable in general to any statistical design of experiment.

摘要

制剂开发包括选择适当的辅料,以在推荐的保质期内稳定活性药物成分,防止其生命周期中出现潜在偏差,有时还可帮助将治疗药物递送至患者体内。治疗制剂中每种成分的身份和数量对于实现其预期目的至关重要。偏离目标组成可能导致制造、安全性和疗效方面的挑战。为了应对制造过程中受影响工艺步骤的合格“过程变异性”导致的组成预期变化,有必要建立制剂的稳健性。通过对治疗稳定性的深入了解和对新工具(包括监管机构强烈推荐的质量源于设计要素)的探索,进行稳健性研究的方法得到了发展。本文提出了一种在多维空间中使用定制实验设计和新颖的多维图研究制剂稳健性的方法,这些多维图提供了一种独特的方法来确定稳健性限制。该概念普遍适用于任何多元分析,此类图表可帮助您一目了然地了解所有变量的结果。本文讨论了对这些图表的解释,其中一些解释通常适用于任何实验设计的统计设计。

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