Click here to open the filter panel
#
21 CFR Part 11
#
510(k) premarket notification
A
Accountability
A
Accuracy
A
Adequacy decision
A
Ad hoc services
A
Adverse event
A
AI literacy (Art. 4 EU AI Act)
A
AI Officer
A
ALCOA+
A
Analysis Data Model (ADaM)
A
Anonymisation
A
APPI (Japan's Act on the Protection of Personal Information)
A
Appropriate safeguards
A
Article 29 Working Party (WP29)
A
Artificial intelligence (AI)
A
Authorised representative (EU AI Act)
A
Automated individual decision-making
A
Auxiliary medicinal product
B
Best-in-class drugs
B
Binding corporate rules (BCR)
B
Biobank
B
Biometric data
B
Biotechnology
B
Blinding and unblinding
B
Breakthrough therapy designation
B
Broad consent
B
Business associate agreement (BAA)
C
CDASH (Clinical Data Acquisition Standards Harmonization)
C
CDISC
C
Central imaging
C
Central laboratory
C
Chemistry, Manufacturing and Controls (CMC)
C
Clinical outcome assessment (COA)
C
Clinical research
C
Clinical study
C
Clinical study report (CSR)
C
Clinical trial
C
Clinical trial agreement (CTA)
C
Clinical trial phases
C
ClinicalTrials.gov
C
Clinical Trials Information System (CTIS)
C
Clinical trial site
C
Clinical Trials Regulation (CTR) 536/2014
C
Clinician-reported outcome (ClinRO)
C
CNIL (Commission nationale de l'informatique et des libertés)
C
Codes of conduct
C
Common Rule (45 CFR 46)
C
Common Technical Document (CTD)
C
Companion diagnostic
C
Conformity assessment (MDR & AI Act)
C
Consent
C
Contract research organisation (CRO)
C
Controller
C
Cookies
C
Covered entity (HIPAA)
C
CPRD (Clinical Practice Research Datalink)
C
Cross-border processing
D
Data Act
D
Database lock
D
Data concerning health
D
Data Governance Act (DGA)
D
Data management plan (DMP)
D
Data minimisation
D
Data monitoring committee (DMC)
D
Data processing agreement (DPA)
D
Data protection authority (DPA)
D
Data protection by default
D
Data protection by design
D
Data Protection Impact Assessment (DPIA)
D
Data Protection Officer (DPO)
D
Data Protection Representative (DPR)
D
Data quality
D
Data retention
D
Data subject
D
Data subject access request (DSAR)
D
Decentralised clinical trial (DCT)
D
Define-XML
D
De-identification (HIPAA)
D
Differential privacy
E
Early termination of a clinical trial
E
Electronic case report form (eCRF)
E
Electronic clinical outcome assessment (eCOA)
E
Electronic data capture (EDC)
E
Electronic health record (EHR)
E
Electronic informed consent (eConsent)
E
EMA Policy 0070
E
Encryption
E
End of a clinical trial
E
Enterprise
E
ePRO (electronic patient-reported outcome)
E
Ethics committee
E
EU AI Office
E
EU Artificial Intelligence Act (AI Act)
E
EUDAMED
E
European Data Protection Board (EDPB)
E
European Data Protection Supervisor (EDPS)
E
European Health Data Space (EHDS)
E
European Medicines Agency (EMA)
E
EU-US Data Privacy Framework (DPF)
Click a letter to view all its definitions
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.

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

Artificial intelligence (AI)

Artificial intelligence is a field of computer science concerned with systems that perform tasks normally requiring human intelligence, such as pattern recognition, prediction, natural language understanding and decision support. In EU law, an "AI system" is defined in Art. 3(1) of the EU AI Act as a machine-based system designed to operate with varying levels of autonomy, that may exhibit adaptiveness after deployment, and that infers from the input it receives how to generate outputs such as predictions, content, recommendations or decisions.

In life sciences, AI is used across drug discovery, patient recruitment, imaging analysis, software as a medical device, pharmacovigilance signal detection and large language models for medical writing. Most of these use cases process health data and many are high-risk AI systems under Annex III or, when embedded in a CE-marked device, under Annex I of the AI Act.

The regulatory consequences are cumulative: GDPR rules on profiling and automated decisions, AI Act obligations on risk management, data governance and human oversight, and MDR/IVDR requirements where the system is a medical device. See iliomad's AI compliance services.

Does using AI in a clinical workflow replace the need for a data protection assessment?

No. AI functionality does not itself establish permission to use personal data. Assess the purpose, data inputs, parties involved, security and effects on individuals. Where the processing is likely to result in high risk, a DPIA is required under Article 35 GDPR. Keep that assessment distinct from evaluating the tool’s scientific performance.