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Historical Benchmarks for Quality Tolerance Limits Parameters in Clinical Trials

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 quality tolerance limits (QTLs) as a quality control in clinical trials. Previously, TransCelerate pro...

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Autores principales: Makowski, Marcin, Bhagat, Ruma, Chevalier, Soazig, Gilbert, Steven A., Görtz, Dagmar R., Kozińska, Marta, Nadolny, Patrick, Suprin, Melissa, Turri, Sabine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8492573/
https://www.ncbi.nlm.nih.gov/pubmed/34453269
http://dx.doi.org/10.1007/s43441-021-00335-3
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author Makowski, Marcin
Bhagat, Ruma
Chevalier, Soazig
Gilbert, Steven A.
Görtz, Dagmar R.
Kozińska, Marta
Nadolny, Patrick
Suprin, Melissa
Turri, Sabine
author_facet Makowski, Marcin
Bhagat, Ruma
Chevalier, Soazig
Gilbert, Steven A.
Görtz, Dagmar R.
Kozińska, Marta
Nadolny, Patrick
Suprin, Melissa
Turri, Sabine
author_sort Makowski, Marcin
collection PubMed
description 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 quality tolerance limits (QTLs) as a quality control in clinical trials. Previously, TransCelerate proposed a framework for QTL implementation and parameters. Historical data can be important in helping to determine QTL thresholds in new clinical trials. METHODS: This article presents results of historical data analyses for the previously proposed parameters based on data from 294 clinical trials from seven TransCelerate member companies. The differences across therapeutic areas were assessed by comparing Alzheimer’s disease (AD) and oncology trials using a separate dataset provided by Medidata. RESULTS: TransCelerate member companies provided historical data on 11 QTL parameters with data sufficient for analysis for parameters. The distribution of values was similar for most parameters with a relatively small number of outlying trials with high parameter values. Medidata provided values for three parameters in a total of 45 AD and oncology trials with no obvious differences between the therapeutic areas. CONCLUSION: Historical parameter values can provide helpful benchmark information for quality control activities in future trials.
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spelling pubmed-84925732021-10-15 Historical Benchmarks for Quality Tolerance Limits Parameters in Clinical Trials Makowski, Marcin Bhagat, Ruma Chevalier, Soazig Gilbert, Steven A. Görtz, Dagmar R. Kozińska, Marta Nadolny, Patrick Suprin, Melissa Turri, Sabine Ther Innov Regul Sci Original Research 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 quality tolerance limits (QTLs) as a quality control in clinical trials. Previously, TransCelerate proposed a framework for QTL implementation and parameters. Historical data can be important in helping to determine QTL thresholds in new clinical trials. METHODS: This article presents results of historical data analyses for the previously proposed parameters based on data from 294 clinical trials from seven TransCelerate member companies. The differences across therapeutic areas were assessed by comparing Alzheimer’s disease (AD) and oncology trials using a separate dataset provided by Medidata. RESULTS: TransCelerate member companies provided historical data on 11 QTL parameters with data sufficient for analysis for parameters. The distribution of values was similar for most parameters with a relatively small number of outlying trials with high parameter values. Medidata provided values for three parameters in a total of 45 AD and oncology trials with no obvious differences between the therapeutic areas. CONCLUSION: Historical parameter values can provide helpful benchmark information for quality control activities in future trials. Springer International Publishing 2021-08-27 2021 /pmc/articles/PMC8492573/ /pubmed/34453269 http://dx.doi.org/10.1007/s43441-021-00335-3 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Research
Makowski, Marcin
Bhagat, Ruma
Chevalier, Soazig
Gilbert, Steven A.
Görtz, Dagmar R.
Kozińska, Marta
Nadolny, Patrick
Suprin, Melissa
Turri, Sabine
Historical Benchmarks for Quality Tolerance Limits Parameters in Clinical Trials
title Historical Benchmarks for Quality Tolerance Limits Parameters in Clinical Trials
title_full Historical Benchmarks for Quality Tolerance Limits Parameters in Clinical Trials
title_fullStr Historical Benchmarks for Quality Tolerance Limits Parameters in Clinical Trials
title_full_unstemmed Historical Benchmarks for Quality Tolerance Limits Parameters in Clinical Trials
title_short Historical Benchmarks for Quality Tolerance Limits Parameters in Clinical Trials
title_sort historical benchmarks for quality tolerance limits parameters in clinical trials
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8492573/
https://www.ncbi.nlm.nih.gov/pubmed/34453269
http://dx.doi.org/10.1007/s43441-021-00335-3
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