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21 CFR Part 11
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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

Principles of data protection

The principles of data protection are the seven foundational rules in Art. 5 GDPR against which every processing operation is measured, and which are echoed in the UK GDPR, the Swiss FADP, the OECD Guidelines and Convention 108+ of the Council of Europe.

  • Lawfulness, fairness and transparency (Art. 5(1)(a)): a valid legal basis, no deception, and clear information to individuals.
  • Purpose limitation (Art. 5(1)(b)): data collected for specified, explicit and legitimate purposes and not further processed incompatibly, with a presumption of compatibility for scientific research under Art. 89 safeguards.
  • Data minimisation (Art. 5(1)(c)): adequate, relevant and limited to what is necessary.
  • Accuracy (Art. 5(1)(d)): accurate and kept up to date, with inaccurate data corrected or erased.
  • Storage limitation (Art. 5(1)(e)): identifiable form kept no longer than necessary.
  • Integrity and confidentiality (Art. 5(1)(f)): appropriate security against unauthorised or unlawful processing, loss, destruction or damage.
  • Accountability (Art. 5(2)): the controller is responsible for, and must be able to demonstrate, compliance with all of the above.

Breaches of the principles attract the highest tier of administrative fines under Art. 83(5). In a DPIA, each principle is assessed in turn for the processing at hand; iliomad's methodology scores each principle and each actor's security measures on a three-point scale to produce an actionable remediation plan for sponsors and HealthTech companies.