The Guide was written by members of ISPE’s GAMP® Community of Practice (CoP). The aim of this and other GAMP guidance insights is to help organizations protect patient safety, ensure product quality, and maintain data integrity while following key Good Practice (GxP) regulatory guidelines of the pharmaceutical and medical device industries with respect to computerized systems. These include, among others, Good Manufacturing Practices (GMPs), Good Laboratory Practices (GLPs), and Good Clinical Practices (GCPs).
This most recent GAMP Good Practice Guide focuses on the latter, utilizing the general principles found in the ISPE GAMP® 5: A Risk-Based Approach to Compliant GxP Computerized Systems (Second Edition) and adapting them to validate computerized systems in the context of clinical trials and applicable GCP regulatory requirements. , It is meant to be used in conjunction with ISPE GAMP® 5 Guide (Second Edition), as well as with other applicable guides, such as the ISPE GAMP® Guide: Records and Data Integrity and the ISPE GAMP® Good Practice Guide: Enabling Innovation. , ,
An international group of experts and industry specialists within the ISPE GAMP CoP collaborated to produce the ISPE GAMP® Good Practice Guide: Validation and Compliance of Computerized GCP Systems and Data – Good eClinical Practice (Second Edition), led by Maximilian Stroebe, PhD, of Janssen Vaccines and Prevention, Oliver Herrmann, of QFINITY Quality Management, and Frank Henrichmann, also of QFINITY.
Henrichmann explained that the second edition of the ISPE GAMP® Good Practice Guide: Validation and Compliance of Computerized GCP Systems and Data was necessary for a variety of reasons. Clinical studies and their regulatory requirements were becoming increasingly complex, new technologies such as wearable devices or other sensors were becoming more available, and researchers had begun to utilize a diverse array of computerized systems to support clinical trials in multiple settings.
Additionally, technology applications in clinical trials have changed even more dramatically, partly in response to the COVID-19 pandemic. Henrichmann pointed out that COVID-19 forced the industry to move towards a more decentralized trial approach, so clinical work could continue during COVID-19 restrictions, e.g., a trial participant measuring their blood pressure at home instead of at a clinical site or using their personal smartphone to report data. This presented challenges in making these interfaces patient-friendly but also reliable and secure in terms of patient privacy.
COVID-19 also accelerated the push towards analysis of real-world data, e.g., analyses based on existing electronic health records (EHR), and applications that could handle huge amounts of data were needed. At the same time, new innovations in artificial intelligence and machine learning have opened whole other approaches to data acquisition and analysis.
In response to the exponentially growing amounts of data now available, regulatory bodies have made significant additions to applicable regulatory requirements since the initial version of the ISPE GAMP® Good Practice Guide: Validation and Compliance of Computerized GCP Systems and Data – Good eClinical Practice2 and the new Guide reflects those changes. ,
The updated GAMP eClinical Good Practice Guide could be beneficial to many different types of organizations, including pharmaceutical and medical device companies, contract research organizations involved in trials, technology service providers, or anyone involved in trial implementation at clinical sites.
Henrichmann pointed out one important element of the updated Guide is its attention to systems at the clinical site. He added, “The sponsor now must make sure that these systems are under appropriate control if the data will be used within the clinical trial. It's a huge problem for the industry, because they don't know how to establish that oversight, but the Guide gives some guidance.”
The updated Guide also contains information on applicable GCP regulations, an overview of applicable processes and challenges in clinical trials, and in-depth analyses of the specific processes and systems typically utilized. It also provides important information and guidance on risk assessment and validation, as well as challenges to data integrity in computerized aspects of clinical trials. Guide appendixes also provide additional information with respect to data privacy challenges, decentralized trials, artificial intelligence, real-world evidence considerations, open-source solutions such as those used for statistics, and other relevant topics.
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