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从质量保证角度优化停留时间分布曲线的定量分析。

Optimal quantification of residence time distribution profiles from a quality assurance perspective.

机构信息

Center of Plastics Innovation, University of Delaware, DE, USA.

Department of Chemical and Biochemical Engineering, Rutgers University, NJ, USA.

出版信息

Int J Pharm. 2023 Mar 5;634:122653. doi: 10.1016/j.ijpharm.2023.122653. Epub 2023 Jan 27.

DOI:10.1016/j.ijpharm.2023.122653
PMID:36716830
Abstract

Residence time distribution (RTD) has been widely applied across various fields of chemical engineering, including pharmaceutical manufacturing, for applications such as material traceability, quality assurance, system health monitoring, and fault detection. Determination of a representative RTD, in principle, requires an accurate process analytical technology (PAT) procedure capturing the entire range of tracer concentrations from zero to maximum. Such a wide concentration range creates at least two problems: i) decreased accuracy of the model across the entire range of concentrations, relating to limit of quantification, and ii) ambiguity associated with the detection of the tracer for low concentration levels, relating to limit of detection (LOD). These problems affect not only the RTD profile itself, but also RTD-based applications, which can potentially lead to erroneous conclusions. This article seeks to minimize the impact of these problems by understanding the relative importance of different features of RTD on the detection of out-of-specification (OOS) products. In this work, the RTD obtained experimentally was truncated at different levels, to investigate the impact of the truncation of RTD on funnel plots for OOS detection. The main finding is that the tail of the RTD can be truncated with no loss of accuracy in the determination of exclusion intervals. This enables the manufacturing scientist to focus entirely on the peak region, maximizing the accuracy of chemometric models.

摘要

停留时间分布(RTD)已广泛应用于化学工程的各个领域,包括制药制造,可用于物料追溯、质量保证、系统健康监测和故障检测等应用。原则上,确定有代表性的 RTD 需要一个准确的过程分析技术(PAT)程序,该程序能够捕捉从零到最大的整个示踪剂浓度范围。如此宽的浓度范围至少会产生两个问题:i)整个浓度范围内模型的准确性降低,与定量限有关,ii)与检测低浓度示踪剂相关的检测限(LOD)有关的模糊性。这些问题不仅影响 RTD 曲线本身,还影响基于 RTD 的应用,这可能会导致错误的结论。本文旨在通过了解 RTD 对不合格产品(OOS)检测的不同特征的相对重要性,尽量减少这些问题的影响。在这项工作中,实验获得的 RTD 被截断到不同的水平,以研究 RTD 截断对 OOS 检测的漏斗图的影响。主要发现是,RTD 的尾部可以截断,而不会影响排除区间的确定的准确性。这使制造科学家能够完全专注于峰区,从而最大限度地提高化学计量模型的准确性。

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