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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.

D

Data Protection Impact Assessment (DPIA)

A Data Protection Impact Assessment (DPIA) is a process designed to describe a processing operation, assess its necessity and proportionality, and manage the risks to the rights and freedoms of natural persons by assessing them and determining the measures to address them (Art. 35 GDPR; EDPB/WP29 Guidelines WP248). It is mandatory where processing is likely to result in a high risk, in particular for systematic and extensive profiling, large-scale processing of special category data, and systematic monitoring of public areas.

National supervisory authorities publish lists of operations requiring a DPIA under Art. 35(4); almost all include the processing of health data for research, health platforms and genetic data. In practice, every clinical trial, health data warehouse, medical device with connectivity and AI system trained on patient data requires one. Where residual risk remains high, the controller must consult the authority before starting (Art. 36).

A DPIA must contain at least a systematic description of the processing and its purposes, an assessment of necessity and proportionality, an assessment of the risks to individuals, and the measures envisaged to address them, with the DPO's advice. iliomad's methodology scores each GDPR principle and each actor's security measures on a three-point scale and produces a risk-acceptance recommendation for the sponsor; see iliomad DPIA services. A DPIA is a living document to be updated at each protocol amendment or vendor change, and it is one of the first documents requested during inspections and due diligence.