Click here to open the filter panel
U
UK GDPR
U
Unexpected serious adverse reaction (SUSAR)
V
Validation (computerised system validation, CSV)
V
Vendor assessment (third-party risk management)
V
Vital interests (Art. 6(1)(d) GDPR)
V
Vulnerable participants (vulnerable subjects)
W
Wearables and digital health technologies (DHT)
W
Withdrawal (of consent and from a clinical trial)
W
World Health Organization (WHO)
X
XAI (explainable artificial intelligence)
Y
Yellow Card scheme (UK)
Z
Zero-knowledge proof
Z
Zero trust architecture
Click a letter to view all its definitions
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.

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

Purpose limitation

Purpose limitation is the principle in Art. 5(1)(b) GDPR that personal data must be collected for specified, explicit and legitimate purposes and not further processed in a manner that is incompatible with those purposes. It has two components: purpose specification at the time of collection, communicated to the data subject under Art. 13 and 14, and a compatibility requirement for any subsequent use. The principle derives from the OECD Guidelines and Convention 108 and was analysed in detail in the Article 29 Working Party Opinion 03/2013.

Further processing for a new purpose is permitted if it is compatible, assessed under Art. 6(4) by reference to the link between purposes, the context of collection and reasonable expectations, the nature of the data, the consequences for individuals and the existence of safeguards such as pseudonymisation. Art. 5(1)(b) adds a presumption: further processing for archiving in the public interest, scientific or historical research or statistical purposes is not considered incompatible, provided the Art. 89(1) safeguards are in place. Incompatible new purposes require a fresh legal basis and information.

In life sciences the principle governs whether trial data collected for a specific protocol can be reused for exploratory analyses, pooled databases, model training or secondary research. The EDPB (Opinion 3/2019) cautions that the research presumption is not a blanket licence and that transparency towards participants remains necessary. Describing planned future uses in the informed consent form, adopting tiered or broad consent for samples, and documenting compatibility assessments in the DPIA are the operational answers.