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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.

P

Profiling

Profiling means any form of automated processing of personal data consisting of the use of personal data to evaluate certain personal aspects relating to a natural person, in particular to analyse or predict aspects concerning that natural person's performance at work, economic situation, health, personal preferences, interests, reliability, behaviour, location or movements (Art. 4(4) GDPR).

Three elements are required: automated processing, personal data, and the purpose of evaluating personal aspects. Profiling is not prohibited as such, but it triggers specific rules: the right to object under Art. 21, including an absolute right to object to profiling for direct marketing; the protections of Art. 22 against solely automated decisions with legal or similarly significant effects; a mandatory DPIA where profiling is systematic and extensive (Art. 35(3)(a)); and heightened transparency, since data subjects must be informed of the existence of profiling and of the logic involved (Art. 13(2)(f)).

In health, profiling includes risk stratification algorithms, patient-similarity matching for trial recruitment, predictive models of disease progression, adherence scoring in digital therapeutics, and audience segmentation for disease-awareness campaigns. Most of these use health data and therefore also require an Art. 9 exception. Where the profiling is performed by an AI system in a healthcare or medical device context, it is likely to be a high-risk AI system under the EU AI Act, adding requirements on data governance, human oversight and transparency to the GDPR analysis.