Informed consent aims to provide clinical trial participants with transparent education about the trial’s objectives, potential risks and benefits, and procedural requirements. As clinical trial designs evolve to include decentralized and adaptive elements, the informed consent process becomes increasingly complex. In response, this article explores the potential application of AI-powered...
The new ISPE GAMP® Guide: Artificial Intelligence provides a comprehensive, state-of-the-art best practice framework to efficiently and effectively achieve high-quality AI-enabled computerized systems in regulated life science areas. It bridges established GAMP concepts with...
This special anniversary article addresses the history and milestones that define the GAMP Community of Practice (CoP). In celebration of the 25th anniversary of the creation of GAMP Americas, we reflect on the vital role GAMP Americas has played in that journey. We commemorate key accomplishments of its members, share recent activities, and look ahead to the future of GAMP Americas.
The landscape of clinical trials has been transformed in a post-pandemic world. In July, ISPE released the second edition of ISPE GAMP® Good Practice Guide: Validation and Compliance of Computerized GCP Systems and Data – Good eClinical Practice. It addresses managing complexities associated with decentralized clinical trials, the benefits and challenges of using open-source software, and...
It is an exciting time in life sciences. Many companies have focused initial artificial intelligence/machine learning (AI/ML) adoption efforts on developing and implementing ML trained algorithms, which necessitate following a controlled approach such as the GAMP® 5 ML Sub-System methodology shown below. This blog highlights key artifacts and considerations when implementing AI/ML for GxP use...
Stakeholders across industries are becoming accustomed to using information technology (IT) systems, applications, and business solutions that feature artificial intelligence (AI) and machine learning (ML). Even though some of these uses show phenomenal performance, thorough risk management is required to ensure quality and regulatory compliance are met within the life sciences industry. By...
