使用贝叶斯方法预测生物制品和疫苗的Ppk计算 - 一个教程
1Center for Mathematical Sciences, MSD, Oss, The Netherlands.
Pharmaceutical statistics
|April 11, 2024
概括
本研究介绍了一种贝叶斯方法,用于预测开发早期的制造工艺能力. 这种方法提高了工艺的稳定性,并在商业化之前降低了风险,提高了制药产品的质量.
科学领域:
- 制药制造业 制药制造业 制药制造业
- 生物制药工艺开发 生物制药过程开发
- 统计过程控制 统计过程控制
背景情况:
- 生物制剂和疫苗的快速过程开发可能会损害稳定性,导致推出后的问题.
- 目前的方法评估的过程能力 (Ppk) 晚在商业化,阻碍及时调整.
- 生物制药开发往往侧重于关键质量属性,而没有充分评估过程的稳定性.
研究的目的:
- 提出一个基于贝叶斯的方法论,用于在开发过程中预测制造工艺在规模上的性能.
- 能够及早识别流程漏洞和需要改进的领域.
- 在产品发布之前增强流程稳定性和知识.
主要方法:
- 利用贝叶斯统计学来结合有限的开发数据,类似的产品数据和主题专家 (SME) 的知识.
- 在贝叶斯框架内制定信息先验,以预测过程能力.
- 在关键的开发阶段 - - 门口 - - 应用预测性Ppk方法.
主要成果:
- 通过使用有限的数据和先前知识,展示了一种预测长期过程能力的方法.
- 在商业化之前,提供了对潜在流程漏洞的早期见解.
- 实现了以数据为导向的发展工作优先级,以提高稳健性.
结论:
- 贝叶斯式方法可以在商业数据可用之前预测制造过程的性能.
- 在阶段门中整合预测性Ppk评估有助于持续改进过程.
- 这种方法导致更强大的制造工艺和在推出时增加的工艺知识.
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