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In the ever changing world of clinical research, staying up to date with the latest guidelines and best practices is crucial. Our Major Changes in GCP from ICH E6(R2) to (R3): Road Map is designed for busy professionals who want to deepen their knowledge on GCP to help ensure they meet the highest standards of quality, safety, and compliance.
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In January 2025, the US Food and Drug Administration (FDA) published a draft guidance titled “Considerations for the Use of Artificial Intelligence (AI) to Support Regulatory Decision-Making for Drug and Biological Products” for trial sponsors and stakeholders intending to use AI to generate data and clinical evidence.
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In March, 2025, the European Medicines Agency (EMA) released a “Reflection paper on use of real-world data (RWD) in non-interventional studies (NIS) to generate real-world evidence (RWE) for regulatory purposes” as a guidance for stakeholders on quality planning, conduct and analysis of NISs that intend to use RWD to generate RWE.
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In November 2024, the US Food and Drug Administration (FDA) issued a warning letter to the sponsor as a result of a BioResearch Monitoring Program (BIMO) inspection which observed objectionable conditions. The warning letter cited two violations of the Title 21 CFR.
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In December 2024, following the release of the 2024 revision of the Declaration of Helsinki (DoH), US Food and Drug Administration (FDA) staff shared the FDA’s perspective on what their role was in the development of the 2024 DoH and how it may impact FDA procedures. The DoH is intended to guide clinical research involving human participants that is often used as the foundation for other guidelines such as the International Council for Harmonisation (ICH) Good Clinical Practice (GCP).
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In January 2025, the US Food and Drug Administration (FDA) published a draft guidance titled “Considerations for the Use of Artificial Intelligence (AI) to Support Regulatory Decision-Making for Drug and Biological Products” for trial sponsors and stakeholders intending to use AI to generate data and clinical evidence.
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The United States Government Accountability Office (GAO) released a report, “Artificial Intelligence in Health Care: Benefits and Challenges of Machine Learning in Drug Development.” It outlines six options for policymakers in response to challenges in the use of machine learning in drug development. But why would machine learning be useful in clinical research?
