Application of the quality by design approach to the drug substance manufacturing process of an Fc fusion protein: Towards a global multi‐step design space

设计质量 关键质量属性 质量(理念) 过程分析技术 过程(计算) 工艺设计 计算机科学 工艺验证 风险分析(工程) 制造工艺 可靠性工程 稳健性(进化) 医药制造业 实验设计 生化工程 工艺工程 在制品 工程类 数学 运营管理 医学 统计 过程集成 药理学 材料科学 化学 验证和确认 复合材料 哲学 生物化学 操作系统 下游(制造业) 认识论 基因
作者
Alex Eon‐Duval,Pascal Valax,Thomas Solacroup,Hervé Broly,Ralf Gleixner,Claire Le Strat,James K. Sutter
出处
期刊:Journal of Pharmaceutical Sciences [Elsevier]
卷期号:101 (10): 3604-3618 被引量:39
标识
DOI:10.1002/jps.23273
摘要

The article describes how Quality by Design principles can be applied to the drug substance manufacturing process of an Fc fusion protein. First, the quality attributes of the product were evaluated for their potential impact on safety and efficacy using risk management tools. Similarly, process parameters that have a potential impact on critical quality attributes (CQAs) were also identified through a risk assessment. Critical process parameters were then evaluated for their impact on CQAs, individually and in interaction with each other, using multivariate design of experiment techniques during the process characterisation phase. The global multi‐step Design Space, defining operational limits for the entire drug substance manufacturing process so as to ensure that the drug substance quality targets are met, was devised using predictive statistical models developed during the characterisation study. The validity of the global multi‐step Design Space was then confirmed by performing the entire process, from cell bank thawing to final drug substance, at its limits during the robustness study: the quality of the final drug substance produced under different conditions was verified against predefined targets. An adaptive strategy was devised whereby the Design Space can be adjusted to the quality of the input material to ensure reliable drug substance quality. Finally, all the data obtained during the process described above, together with data generated during additional validation studies as well as manufacturing data, were used to define the control strategy for the drug substance manufacturing process using a risk assessment methodology.

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