A Quality Risk Management Model Approach for Cell Therapy Manufacturing
A Quality Risk Management Model Approach for Cell Therapy Manufacturing
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DOI：
10.1111/j.1539-6924.2010.01465.x
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发表时间：
2010-12-01
期刊：
影响因子：
3.8
通讯作者：
Triolo, Fabio
中科院分区：
文献类型：
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作者：
Lopez, Fabio;Di Bartolo, Chiara;Triolo, Fabio
国际监管机构将风险管理视为开发再生医学中基于体细胞的创新疗法的基本生产需求。然而，现有的风险管理指南对临床细胞治疗制造中适用的具体风险分析方法和程序提供的指导很少。这引发了一系列问题。细胞制造是一个自动化程度较低的过程，容易发生操作员引入的变化，并受到加工器官/组织的异质性和试剂（如胶原酶）效率的大量依赖变异性的影响。在本研究中，确定并解决了基于细胞的产品制造环境中面临的主要挑战（即高度依赖人为干预和缺乏可接受风险水平的参考标准），并首次描述了适用于临床使用细胞制造的风险管理模型方法。在这种特定情况下，使用启发式和伪定量失效模式和影响分析/失效模式和关键影响分析风险分析技术与直接估计严重性、发生和检测相关联，与层次分析法一样有效，但比层次分析法更有效。此外，严重性/发生矩阵和帕累托分析可以成功地用于识别优先故障模式，以采取行动来降低风险。本文还讨论了该方法在再生医学中临床细胞治疗制造中的应用。
International regulatory authorities view risk management as an essential production need for the development of innovative, somatic cell-based therapies in regenerative medicine. The available risk management guidelines, however, provide little guidance on specific risk analysis approaches and procedures applicable in clinical cell therapy manufacturing. This raises a number of problems. Cell manufacturing is a poorly automated process, prone to operator-introduced variations, and affected by heterogeneity of the processed organs/tissues and lot-dependent variability of reagent (e.g., collagenase) efficiency. In this study, the principal challenges faced in a cell-based product manufacturing context (i.e., high dependence on human intervention and absence of reference standards for acceptable risk levels) are identified and addressed, and a risk management model approach applicable to manufacturing of cells for clinical use is described for the first time. The use of the heuristic and pseudo-quantitative failure mode and effect analysis/failure mode and critical effect analysis risk analysis technique associated with direct estimation of severity, occurrence, and detection is, in this specific context, as effective as, but more efficient than, the analytic hierarchy process. Moreover, a severity/occurrence matrix and Pareto analysis can be successfully adopted to identify priority failure modes on which to act to mitigate risks. The application of this approach to clinical cell therapy manufacturing in regenerative medicine is also discussed.