The International Council for Harmonisation’s ICH M14 guideline introduces pivotal changes to how non-interventional studies using Real-World Data (RWD) are conducted for medical safety evaluation. Aiming to harmonize international standards, the European Medicines Agency’s (EMA) Committee for Medicinal Products for Human Use (CHMP) formally adopted the guideline on September 18, 2025. The document lays out structured principles for planning, designing, analyzing, and reporting these studies to improve decision-making and regulatory acceptance. The guideline emphasizes the importance of robust evidence generation, detailing methods to ensure the reliability and relevance of the collected data, including biases, confounding, and methodological considerations.
Pillars of Study Design and Methodology
The guideline underlines the necessity of a methodical approach to study design and feasibility assessment. Researchers are now tasked to clearly formulate research questions and identify appropriate data sources through systematic feasibility assessments. The guideline recommends using diverse structured templates, such as the PICOTS framework, to ensure studies address key aspects, including the target population, exposure, comparator, outcome, timing, and setting. Furthermore, careful attention to the distinctions between various RWD sources like Electronic Health Records (EHRs), administrative claims data, registries, and data from Digital Health Technologies (DHTs) is vital.
Operational Challenges and Data Management
In its comprehensive scope, the guideline discusses operational challenges associated with data management and curation. It mandates a thorough data management plan, highlighting the significance of data relevance, accuracy, and completeness, along with robust quality assurance controls. The guideline advises integrating QA/QC processes with data holders and ensuring transparent, detailed documentation—essential elements for maintaining high data integrity needed for regulatory decision-making. These processes also encompass handling missing data, employing sensitivity analyses, and leveraging quantitative bias analysis to assess and mitigate potential biases.
– Researchers must adopt rigorous methods to validate key study variables.
– Ethical and legal considerations are crucial when managing data linkage across different sources.
– The guideline necessitates clear delineation between pre-specified and post-hoc analyses within the statistical analysis plan.
– Engaging early with regulators can facilitate smoother adoption and implementation of study protocols.
Investing in meticulously designed studies using RWD for safety assessments offers numerous benefits beyond regulatory compliance. It ultimately guides more informed decision-making concerning medicinal use in real-world settings. Researchers must prioritize transparency and carefully document methodological choices including statistical methods, data sources, variable validation processes, and feasibility assessments. This meticulous approach ensures the development of scientifically robust and internationally harmonized safety studies. Enhanced global collaboration will allow leveraging large datasets, providing rich insights into medication safety across diverse populations, facilitating new discoveries, and potentially influencing global safety standards. Thus, staying informed about evolving methodologies and guidelines remains crucial for healthcare professionals engaged in pharmacoepidemiology.
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