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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.

R

Randomised clinical trial (RCT)

A randomised clinical trial (RCT) is a clinical trial in which participants are allocated to two or more treatment groups by a chance process rather than by choice of the investigator or patient. Randomisation balances known and unknown prognostic factors across groups, so that differences in outcome can be attributed to the intervention. Combined with blinding (masking of treatment allocation from participants, investigators and assessors) and a concurrent control group (placebo or active comparator), it is the design that regulators regard as providing the highest level of evidence, in line with ICH E9 and E10.

Randomisation schedules are generated by an independent statistician using methods such as simple, block, stratified or adaptive randomisation, and implemented through an IRT or RTSM system that also manages drug supply and controlled unblinding. Reporting follows the CONSORT statement, and the analysis population and handling of intercurrent events are pre-specified under the ICH E9(R1) estimand framework.

From a data protection perspective, randomisation and blinding create specific processing operations: stratification factors (age band, sex, disease stage, biomarker or genetic status) are recorded in the randomisation system; treatment assignment is highly confidential information whose disclosure would compromise the trial; and emergency unblinding must be possible for patient safety while being fully logged. These flows, the processor role of the IRT vendor and access controls should be described in the DPIA, and the independent statistician's access to unblinded data addressed in the DMC charter.

Does randomisation mean a clinical trial is blinded?

No. Randomisation assigns participants to groups by chance; blinding limits knowledge of those assignments. A trial can be randomised but open-label. The protocol should explain both arrangements, including who can see treatment allocation and how emergency access works, because these choices address different sources of bias.