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An Overview of Current Statistical Methods for Implementing Quality Tolerance Limits

Kilaru, Rakhi; Amodio, Sonia; Li, Yasha; Wells, Christine; Love, Sharon; Zeng, Yuling; Ye, Jingjing; ... Talbot, Susan; + view all (2023) An Overview of Current Statistical Methods for Implementing Quality Tolerance Limits. Therapeutic Innovation & Regulatory Science 10.1007/s43441-023-00598-y. (In press). Green open access

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Abstract

BACKGROUND: In 2016, the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use updated its efficacy guideline for good clinical practice and introduced predefined quality tolerance limits (QTLs) as a quality control in clinical trials. QTLs are complementary to Quality by Design (QbD) principles (ICH-E8) and are one of the components of the risk-based clinical trial quality management system. METHODS: Currently the framework for QTLs process is well established, extensively describing the operational aspects of Defining, Monitoring and Reporting, but a single source of commonly used methods to establish QTLs and secondary limits is lacking. This paper will primarily focus on closing this gap and include applications of statistical process control and Bayesian methods on commonly used study level quality parameters such as premature treatment discontinuation, study discontinuation and significant protocol deviations as examples. CONCLUSIONS: Application of quality tolerance limits to parameters that correspond to critical to quality factors help identify systematic errors. Some situations pose special challenges to implementing QTLs and not all methods are optimal in every scenario. Early warning signals, in addition to QTL, are necessary to trigger actions to further minimize the possibility of an end-of-study excursion.

Type: Article
Title: An Overview of Current Statistical Methods for Implementing Quality Tolerance Limits
Location: Switzerland
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/s43441-023-00598-y
Publisher version: https://doi.org/10.1007/s43441-023-00598-y
Language: English
Additional information: This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Keywords: Centralized statistical monitoring, Data quality, Quality by design, Quality tolerance limits, Risk identification, Risk-based monitoring
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology > MRC Clinical Trials Unit at UCL
URI: https://discovery.ucl.ac.uk/id/eprint/10184613
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