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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.

D

Data management plan (DMP)

A data management plan (DMP) in clinical research is the controlled document describing how the data of a clinical trial will be handled from collection to archiving: the design and build of the eCRF and EDC database, data entry conventions, edit checks and validation rules, query management, medical coding (MedDRA for adverse events, WHODrug for medications), reconciliation with external data from laboratories, eCOA and IRT systems and with the safety database, handling of protocol deviations, database lock procedures, SDTM mapping, transfer specifications and archiving. Good Clinical Data Management Practices (GCDMP) of the Society for Clinical Data Management and ICH E6(R3) set the professional standards, and the EMA guideline on computerised systems and electronic data in clinical trials (2023) expects documented data flows and system validation.

The DMP is usually authored by the sponsor's or CRO's data management function, approved before first patient in, version-controlled and filed in the trial master file. It is complemented by a data validation plan, a data transfer agreement or specification for each external vendor, and the statistical analysis plan. Inspectors use it to reconstruct how data moved and changed, so gaps between the plan and actual practice are common findings.

The DMP is also the natural place to operationalise data protection requirements that the DPIA identifies: which identifiers may appear in the database (minimisation, no names, initials or full dates of birth), how free-text fields are controlled and reviewed for leakage of identifying information, how pseudonymisation is preserved across data transfers between vendors, role-based access and blinding rules, encryption and secure transfer standards for data exchanges, procedures to apply a restriction flag or process a participant's rights request, retention and secure destruction of interim datasets, and the location of each system to identify international transfers. Aligning the DMP, the DPIA and the processor agreements ensures that the controls promised in the informed consent form exist in the systems that actually hold the data.