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Transfer impact assessment (TIA)
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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.

W

Wearables and digital health technologies (DHT)

Wearables and digital health technologies (DHTs) are sensor-based devices and software (smartwatches, patches, continuous glucose monitors, actigraphs, smartphone apps, connected inhalers and ingestible sensors) that collect physiological, behavioural or environmental data from individuals in daily life. In clinical trials they enable novel digital endpoints such as step count, gait, sleep, heart rate variability, cough frequency or medication adherence, support decentralised designs and provide real-world data between visits. In care, they underpin remote patient monitoring, digital therapeutics and consumer wellness.

Regulators have built frameworks for their use as evidence: the FDA guidance on digital health technologies for remote data acquisition in clinical investigations (final, December 2023) covers verification, validation and usability of DHTs and their fitness for purpose; the EMA has a qualification procedure for novel methodologies including digital measures, and its 2020 questions-and-answers on digital technology-based methodologies set expectations. Whether a wearable is a medical device depends on its intended purpose: a consumer smartwatch used to collect exploratory data is generally not, while a device or algorithm with a medical claim is a medical device or SaMD, and AI-driven analysis may be a high-risk AI system.

Wearables generate continuous, granular health data, and often biometric and location data, which makes them one of the most demanding processing scenarios under the GDPR. Key issues are: the difficulty of applying data minimisation to raw sensor streams (favour on-device processing and derived measures); the device manufacturer's own role, since consumer platforms frequently act as independent controllers with their own accounts, cloud storage and analytics, often outside the EEA; bring-your-own-device policies and data left on participants' devices; the risk of revealing trial participation or health status through notifications; the Data Act rights of users over connected-product data; and transparency towards participants about what is collected passively. A DHT-specific section in the DPIA, a DPA or joint-controller arrangement with the technology provider and a clear description in the informed consent form are the minimum; see iliomad's health apps domain page.