Archive for January 2025
Good Machine Learning Practices (GMLP): Extending GxP Principles in AI-Enabled Healthcare
The integration of artificial intelligence (AI) and machine learning (ML) in healthcare has transformed how medical technology is developed, evaluated, and deployed. This innovation calls for adherence to rigorous quality standards to ensure safety, efficacy, and compliance. While traditional Good Practice (GxP) guidelines—such as Good Manufacturing Practice (GMP), Good Clinical Practice (GCP), and Good Laboratory…
Read MoreDesigning an Audit Trail for AI in Clinical Trials: Aligning with the EU AI Act
As artificial intelligence (AI) continues to transform clinical trials, ensuring transparency, accountability, and compliance has become critical. Central to achieving these goals is the implementation of a robust audit trail system. While the EU Artificial Intelligence Act (EU AI Act) does not explicitly define audit trail requirements for high-risk AI systems, it emphasizes the need…
Read MoreEngaging with the FDA on AI in Clinical Trials: Beyond Traditional Meetings
The U.S. Food and Drug Administration’s (FDA) draft guidance, Considerations for the Use of Artificial Intelligence to Support Regulatory Decision-Making for Drug and Biological Products, offers a comprehensive framework for the integration of artificial intelligence (AI) in drug development. For regulatory professionals, understanding the various engagement options beyond traditional FDA meetings is crucial for effectively…
Read MoreWho’s Afraid of the Big, Bad EU AI Act?
The European Union’s Artificial Intelligence Act (EU AI Act) has become a significant milestone in the global regulation of artificial intelligence. As the world’s first comprehensive AI regulation, it introduces a risk-based framework designed to ensure the safe and ethical deployment of AI technologies. For industries relying heavily on innovation, like biopharma clinical trials, understanding…
Read MoreData Governance Under the EU AI Act: From Clinical Trial Analytics to Compliance
In clinical trials and healthcare, data comprise the foundation of every decision, from designing study protocols to analyzing patient outcomes. As artificial intelligence (AI) increasingly shapes clinical operations, data governance has become a critical factor in ensuring data quality, compliance, and ethical AI deployment. Data governance involves the management of data availability, usability, integrity, and…
Read MoreBuilding a Compliant Quality Management System for AI in Healthcare
In healthcare and biopharma, ensuring patient safety, product quality, and regulatory compliance has always been paramount. A Quality Management System (QMS) serves as the backbone for these priorities, providing a structured framework for risk management, process standardization, and continuous improvement. As artificial intelligence (AI) becomes more embedded in clinical operations and drug development, traditional QMS…
Read MoreBridging Innovation and Compliance: Aligning Digital Transformation with the EU AI Act
Digital transformation in the biopharma industry isn’t just about adopting the latest technologies—it’s about fundamentally reimagining how clinical trials are designed, conducted, and analyzed. This shift involves integrating artificial intelligence (AI), cloud computing, and data analytics to streamline operations, accelerate drug development, and improve patient experiences. However, with the introduction of the European Union’s Artificial…
Read MoreThe Unfolding Cancer Crisis: Breaking the Rules of Mitosis and Rising Incidence
Cancer unfolds when mitosis, or the process of cell reproduction, decides to break all the rules and go rogue. Despite significant strides in scientific understanding and cancer treatment, including use of artificial intelligence (AI) to accelerate cancer immunotherapy research, recent updates from the American Cancer Society cast a shadow on our optimistic journey. While scientific…
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