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Historical Benchmarks for Quality Tolerance Limits Parameters in Clinical Trials.
Makowski, Marcin; Bhagat, Ruma; Chevalier, Soazig; Gilbert, Steven A; Görtz, Dagmar R; Kozinska, Marta; Nadolny, Patrick; Suprin, Melissa; Turri, Sabine.
Afiliação
  • Makowski M; Global Clinical & Data Operations, GlaxoSmithKline GmbH & Co. KG, Prinzregentenpl. 9, 81675, Munich, Germany. Marcin.x.Makowski@gsk.com.
  • Bhagat R; Product Development Quality, Roche, 1 DNA way, South San Francisco, CA, 94404, USA.
  • Chevalier S; Clinical Sciences and Operations, Sanofi, 1 Avenye Pierre Brossolette, 91380, Chilly-Mazarin, France.
  • Gilbert SA; Statistical Research & Innovation, Pfizer Inc., 300 Technology Square, Third Floor, Cambridge, MA, 02139, USA.
  • Görtz DR; BioResearch Quality & Compliance, Janssen-Cilag GmbH, Johnson & Johnson Platz 1, 41470, Neuss, Germany.
  • Kozinska M; Centralized Monitoring, AstraZeneca, Postepu 14, 02-390, Warsaw, Poland.
  • Nadolny P; Clinical Data Management, Sanofi, 1 Avenue Pierre Brossolette, 91380, Chilly-Mazarin, France.
  • Suprin M; Clinical Data Management and Programming, Allergan, 2525 Dupont Drive, Irvine, CA, 92612, USA.
  • Turri S; Clinical Development Quality Center of Excellence, Pfizer, Inc, Eastern Point Road, Groton, CT, 06340, USA.
Ther Innov Regul Sci ; 55(6): 1265-1273, 2021 11.
Article em En | MEDLINE | ID: mdl-34453269
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 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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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Benchmarking Tipo de estudo: Guideline Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Benchmarking Tipo de estudo: Guideline Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article