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R
Randomised clinical trial (RCT)
R
Real-world data (RWD)
R
Real-world evidence (RWE)
R
Recipient
R
Record of processing activities (RoPA)
R
Regulatory intelligence
R
Re-identification risk (motivated intruder test)
R
Restriction of processing
R
Right not to be subject to solely automated decision-making
R
Right of access
R
Right of information
R
Right of rectification
R
Rights of the data subject
R
Right to data portability
R
Right to erasure ("right to be forgotten")
R
Right to object
R
Right to restriction of processing
S
Schrems II
S
Scientific research purposes (Art. 89 GDPR)
S
Secondary use of health data
S
Security breach (security incident)
S
Security of processing
S
Sensitive data
S
Serious adverse event (SAE)
S
Shadow AI
S
Site management organisation (SMO)
S
SNDS (Système National des Données de Santé)
S
Software as a Medical Device (SaMD)
S
Source data verification (SDV) and source documents
S
Special categories of personal data
S
Sponsor
S
Standard contractual clauses (SCC)
S
Start of a clinical trial
S
Storage limitation (limited storage periods)
S
Study Data Tabulation Model (SDTM)
S
Subject (clinical trial participant)
S
Sub-processor
S
Supervisory authority
S
Supplementary measures
S
Swiss Federal Act on Data Protection (FADP / revFADP)
S
Swissmedic
S
Synthetic data
T
Technical and organisational measures (TOMs)
T
Temporary halt of a clinical trial
T
Third country
T
Third party
T
Transfer impact assessment (TIA)
T
Trial master file (TMF)
T
Trusted research environment (TRE)
U
UK GDPR
U
Unexpected serious adverse reaction (SUSAR)
U
US CLOUD Act
V
Validation (computerised system validation, CSV)
V
Vendor assessment (third-party risk management)
V
Vital interests (Art. 6(1)(d) GDPR)
V
Vulnerable participants (vulnerable subjects)
W
Wearables and digital health technologies (DHT)
W
Withdrawal (of consent and from a clinical trial)
W
World Health Organization (WHO)
X
XAI (explainable artificial intelligence)
Y
Yellow Card scheme (UK)
Z
Zero-knowledge proof
Z
Zero trust architecture
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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 protection by default

Data protection by default is the obligation in Art. 25(2) GDPR for the controller to implement appropriate technical and organisational measures ensuring that, by default, only personal data which are necessary for each specific purpose are processed. The obligation covers the amount of data collected, the extent of processing, the storage period and accessibility, and specifically requires that personal data are not made accessible to an indefinite number of people without the individual's intervention.

In practice, this means that the most privacy-protective settings must be the pre-selected ones: a health app should not share data with third parties or enable location tracking unless the user turns it on; an EDC system should give site users access only to their own subjects; retention periods should be configured to the documented schedule rather than left indefinite; and optional data fields should be off unless the protocol requires them.

The EDPB Guidelines 4/2019 explain that "default" applies to both the controller's own choices and the configuration of systems bought from vendors. It complements data protection by design and gives operational teeth to the data minimisation and storage limitation principles. Failure to configure defaults properly has been the basis of several enforcement decisions against social media and adtech platforms, and is increasingly assessed in HealthTech investigations.

What does data protection by default mean for a study platform?

Configure the platform to process only the personal data needed for each purpose without requiring users to reduce unnecessary exposure themselves. Practical examples include limiting site access to relevant records, disabling unnecessary fields and setting justified retention periods. Check vendor defaults rather than assuming the standard configuration meets Article 25 GDPR.