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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

Population pharmacokinetics (pop PK)

Population pharmacokinetics (pop PK) is the study of the sources and correlates of variability in drug concentrations among individuals in the target patient population receiving clinically relevant doses. Rather than intensive sampling in a few volunteers, pop PK analyses sparse samples from many patients using non-linear mixed-effects models (implemented in software such as NONMEM or Monolix) to estimate typical pharmacokinetic parameters, inter-individual and residual variability, and the influence of covariates such as body weight, age, renal function, sex, genotype and concomitant medications.

Pop PK is a cornerstone of model-informed drug development. It supports dose selection and adjustment in special populations (children, the elderly, renal or hepatic impairment), exposure-response analyses for efficacy and safety, justification of dosing in the label, and paediatric extrapolation. The FDA guidance on population pharmacokinetics (2022) and the EMA guideline on reporting pop PK analyses (2007) set expectations for model building, evaluation and reporting.

Pop PK datasets pool pseudonymised individual-level data across trials, sites and countries, often including demographic and genetic covariates that increase identifiability, and are frequently analysed by specialist pharmacometrics consultancies acting as processors. Pooling data collected under different consent documents and national legal frameworks requires a compatibility assessment under Art. 6(4) GDPR or a research legal basis with Art. 89 safeguards, and cross-border sharing of the pooled dataset is an international data transfer to be covered by SCCs or another mechanism.