Summary
This narrative review examines two principal approaches for aggregating and analysing diverse clinical datasets in precision medicine research: centralised and federated models. The authors compare the methodological strengths, weaknesses, and recent advances of each approach, whilst highlighting implementation challenges and future opportunities for improving disease understanding through multi-source data integration.
Regional applicability
The paper addresses methodological infrastructure challenges relevant globally, including in United Kingdom precision medicine initiatives and the NHS's use of clinical data for research. Transferability depends on UK data governance frameworks, privacy regulations (GDPR, Data Protection Act 2018), and integration with existing NHS data infrastructure.
Key measures
Not applicable; this is a methodological review comparing analytical frameworks rather than reporting quantitative outcome measures.
Outcomes reported
The review compares centralized and federated models for aggregating and analysing diverse clinical datasets. It examines methodological progress, inherent strengths and weaknesses of each approach, and associated analytical challenges.
Topic tags
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