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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.

A

Automated individual decision-making

Automated individual decision-making refers to a decision based solely on automated processing, including profiling, which produces legal effects concerning a natural person or similarly significantly affects them. Under Art. 22 GDPR, data subjects have the right not to be subject to such a decision, unless it is necessary for a contract, authorised by Union or Member State law, or based on explicit consent.

Where an exception applies, the controller must implement suitable safeguards, at minimum the right to obtain human intervention, to express one's point of view and to contest the decision. Decisions based on special category data such as health data are only allowed with explicit consent or for reasons of substantial public interest, with suitable safeguards. The Court of Justice (SCHUFA, C-634/21) has confirmed that producing a score that a third party relies on decisively is itself a "decision".

In healthcare and clinical research, examples include algorithmic triage, automated eligibility screening for trials or fully automated insurance and reimbursement decisions. Clinical decision support systems where a clinician makes the final call are generally not "solely" automated, but they may still be high-risk AI systems under the EU AI Act, which adds transparency and human oversight requirements.

Does every use of an algorithm trigger GDPR Article 22?

No. Article 22 concerns decisions based solely on automated processing that have legal or similarly significant effects, subject to its exceptions and safeguards. A tool that helps organise information is not automatically such a decision. Assess the actual effect on the person and the reality of human involvement, not just the presence of an algorithm.