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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.

K

Kinetics (pharmacokinetics and pharmacodynamics)

Kinetics, in health research and drug development, refers to the study of rates of change over time: how quickly a drug is absorbed, distributed, metabolised and eliminated (pharmacokinetics, PK), how the concentration of the drug at its site of action translates into effect over time (pharmacodynamics, PD), and, in the underlying chemistry, the rate at which reactions such as enzymatic metabolism proceed. PK/PD modelling links these to identify dose regimens that achieve therapeutic exposure with acceptable toxicity.

Kinetic data is generated in Phase I trials through intensive blood sampling schedules, in later phases through sparse sampling analysed with population pharmacokinetic methods, and increasingly through model-informed drug development accepted by the EMA and FDA in place of some dedicated studies. Results feed the investigator's brochure, the IMPD and the clinical pharmacology section of the marketing application.

Kinetic datasets are individual-level health data: timed concentrations, body weight, renal and hepatic function, and frequently pharmacogenomic variants that explain metabolic differences. Samples are often analysed by a specialised bioanalytical laboratory acting as a processor, and residual samples may be banked for future assays. The associated data flows, retention of samples and future-use consent should be described in the DPIA and informed consent form like any other trial data.

What is the practical difference between pharmacokinetics and pharmacodynamics?

Pharmacokinetics describes how drug concentrations change over time, while pharmacodynamics concerns the drug’s effects. Linking them helps assess how exposure relates to response. In a study dataset, accurate dose and sample times are therefore important alongside outcome measurements; a concentration value without its timing context can be difficult to interpret.