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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.

Z

Zero-knowledge proof

A zero-knowledge proof (ZKP) is a cryptographic protocol in which one party, the prover, convinces another party, the verifier, that a statement is true without revealing any information beyond the truth of the statement itself. Introduced by Goldwasser, Micali and Rackoff in 1985, ZKPs have moved from theory to deployment through constructions such as zk-SNARKs and zk-STARKs, which produce compact, quickly verifiable proofs. A ZKP must be complete (a true statement can always be proven), sound (a false statement cannot be proven except with negligible probability) and zero-knowledge (the verifier learns nothing else).

Practical applications include proving that a person is over a certain age without disclosing their date of birth, proving that a credential (a medical licence, a vaccination status, membership of a cohort) is valid without revealing the underlying document, authenticating to a system without transmitting a password, and demonstrating that a computation was performed correctly on private data. The EU Digital Identity Wallet under the eIDAS 2.0 Regulation is expected to use zero-knowledge techniques for selective disclosure of attributes, and the EDPB has recommended ZKPs for age verification in its 2025 statement on age assurance as a way to satisfy data minimisation.

ZKPs belong to the family of privacy-enhancing technologies alongside encryption, secure multi-party computation, federated learning and differential privacy. In health and clinical research, candidate use cases are verifying trial eligibility criteria or a participant's identity in eConsent and decentralised trials without exposing full medical records, proving that a dataset meets k-anonymity or other release criteria without revealing it, authenticating investigators and patients to platforms, and audit-friendly proofs that a processor has applied agreed transformations. Under the GDPR, ZKPs are a means of implementing data protection by design and Art. 32 security: they reduce the personal data disclosed in a transaction, but the data held by the prover remains personal data and the overall processing still requires a legal basis and, where health data is involved, a DPIA.