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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
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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.

E

Electronic data capture (EDC)

Electronic data capture (EDC) refers to the software system used to collect, clean and manage clinical trial data electronically, replacing paper case report forms. The EDC system hosts the eCRFs, applies edit checks, manages data queries between data managers and sites, integrates external data from central laboratories, imaging vendors and eCOA platforms, and produces the locked database exported into SDTM for analysis. Widely used platforms include Medidata Rave, Veeva Vault EDC and Oracle Clinical One.

EDC systems must be validated for their intended use, maintain complete and tamper-evident audit trails, support electronic signatures and role-based access, and comply with FDA 21 CFR Part 11, EU Annex 11 principles and the EMA guideline on computerised systems and electronic data in clinical trials. Sponsors remain responsible for vendor oversight, including periodic audits and review of the vendor's own quality system.

From a data protection standpoint, the EDC vendor is a processor to the sponsor (and indirectly to the site), acting under a data processing agreement meeting Art. 28 GDPR. Hosting location and the vendor's sub-processors determine whether standard contractual clauses are needed. Because EDC data is pseudonymised rather than anonymous, the platform must be included in the record of processing activities, covered by the trial's DPIA and configured so that sites cannot enter directly identifying data.

Does selecting an established EDC vendor remove the need for study-specific checks?

No. A platform’s existing validation does not by itself demonstrate that the study’s configuration works as intended. Check the forms, edit checks, interfaces, user roles and critical workflows relevant to the trial. Document responsibilities between sponsor and provider, including change management and access to records throughout the required retention period.