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Inspection
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Institutional Review Board (IRB)
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Investigational medicinal product (IMP)
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Joint controllers
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k-anonymity
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Large language model (LLM)
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Term of the Day

Natural history study

A natural history study is a preplanned observational study intended to track the course of a disease over time, identifying demographic, genetic, environmental and other variables that correlate with its development and outcomes in the absence of intervention, or under standard of care. Designs may be retrospective (chart review of existing records) or prospective (longitudinal follow-up of a cohort or registry).

Natural history data is particularly important in rare and paediatric diseases, where randomised placebo-controlled trials may be infeasible or unethical. The FDA (guidance on rare disease natural history studies, 2019) and the EMA accept well-designed natural history studies to define endpoints and biomarkers, identify patient subgroups, estimate sample sizes and, in some cases, serve as external or historical control arms for single-arm trials supporting orphan products.

Because they are non-interventional, natural history studies fall outside the CTR and are governed by national law (for example France's MR-003 or MR-004 reference methodologies) and by the GDPR. They typically involve secondary use of medical records, long-term follow-up, genetic data and small populations in which anonymisation is rarely achievable, so pseudonymisation, a DPIA and a robust research legal basis under Art. 9(2)(j) are essential. Registries maintained by patient organisations or academic consortia raise additional questions of joint controllership and data access governance.

E

EU Artificial Intelligence Act (AI Act)

The EU Artificial Intelligence Act (AI Act), Regulation (EU) 2024/1689, is the European Union's horizontal framework for the development, placing on the market and use of artificial intelligence systems. Published on 12 July 2024 and in force since 1 August 2024, it applies in stages: prohibited practices and AI literacy obligations from 2 February 2025; rules for general-purpose AI models and governance from 2 August 2025; most obligations for high-risk AI systems from 2 August 2026; and obligations for high-risk AI embedded in products covered by sectoral legislation such as medical devices from 2 August 2027, subject to the timing adjustments proposed in the Commission's 2025 digital omnibus.

The Act follows a risk-based approach. It prohibits certain practices (manipulative techniques, social scoring, most real-time remote biometric identification); imposes a full compliance regime on high-risk systems listed in Annex III (including systems used for access to essential services, employment, education and law enforcement) and on AI that is a safety component of, or is itself, a product subject to third-party conformity assessment under Annex I legislation, which includes the MDR and IVDR; requires transparency for chatbots, deepfakes and emotion recognition; and sets specific duties for general-purpose models. Obligations are allocated between providers and deployers, with importers, distributors and authorised representatives for non-EU providers.

For life sciences, AI-enabled software as a medical device, diagnostic algorithms and clinical decision support are typically high-risk, while AI used purely for research and development is largely exempt under Art. 2(6) until placed on the market. The Act operates alongside the GDPR: Art. 10 data governance, Art. 14 human oversight and Art. 27 fundamental rights impact assessments complement DPIAs and the rules on automated decisions. Fines reach EUR 35 million or 7% of worldwide turnover. iliomad acts as AI Officer and EU AI Act authorised representative; see also the AI Act summary in the regulations centre.