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T
Transfer impact assessment (TIA)
T
Trial master file (TMF)
U
UK GDPR
U
Unexpected serious adverse reaction (SUSAR)
V
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V
Vendor assessment (third-party risk management)
V
Vital interests (Art. 6(1)(d) GDPR)
V
Vulnerable participants (vulnerable subjects)
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Wearables and digital health technologies (DHT)
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World Health Organization (WHO)
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Zero-knowledge proof
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Zero trust architecture
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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.

H

Health data warehouse (HDW)

A health data warehouse (HDW; in French, entrepôt de données de santé, EDS) is a platform that collects, harmonises and stores health data from multiple source systems, such as electronic health records, laboratory and imaging systems, biobanks and administrative databases, to make it available for secondary use: research, innovation, quality improvement, health system management and, increasingly, training of AI models. University hospitals (for example the AP-HP warehouse in Paris), regional networks, national infrastructures and, in a growing number of cases, pharmaceutical and MedTech companies operate such platforms.

France has the most developed regulatory framework. Since 2021 the CNIL has published a reference framework (référentiel) for health data warehouses: a warehouse that conforms to it may be created on a declaration of conformity, otherwise a CNIL authorisation is required. The framework sets conditions on purposes (excluding, for example, commercial prospecting), data sources, patient information and objection rights, pseudonymisation, access governance through a scientific and ethics committee, security (including HDS certified hosting), retention (generally 20 years) and the requirement that each downstream study comply with MR-004 or obtain its own authorisation. Comparable frameworks exist in other countries (German university medicine data integration centres, Finnish Findata, Danish national registries), and the European Health Data Space will turn such warehouses into data holders supplying health data access bodies from 2029.

Building or using a warehouse raises the full range of GDPR questions: identifying the controller (hospital, consortium, industrial partner) and any joint controllers; the legal basis (public interest or legitimate interest with Art. 9(2)(j)); transparency towards patients who are not individually contacted; a mandatory DPIA; security and access measures; the status of data made available to users as pseudonymised or anonymised; and transfer rules where users or cloud providers are outside the EEA. iliomad supports hospitals and companies in creating warehouses and in accessing them; see health data warehouse services, the French HDW guideline and the HDW guide in the resource centre.