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Version: 1.0.0 | Published: 5 Mar 2026 | Updated: 116 days ago

Imperial Health Knowledge Bank (IHKB) Blood Samples with Linked Health Data

Dataset

Documentation

Description:
Blood Samples with Linked Health Data are a secure, ethically governed resource that integrates high-quality biological samples with corresponding anonymised clinical data from across Imperial College Healthcare NHS Trust. Designed to support translational research, this platform provides approved researchers with access to richly annotated blood samples linked to longitudinal health records. By connecting blood sample type with both phenotype and genotype, the resource enables deeper insights into the molecular and clinical dimensions of disease. This bridges biospecimens with real-world data; these Blood Samples enable advanced investigations into disease mechanisms, personalised medicine, and biomarker discovery. This integrated approach accelerates research, enabling scientific insights, and contributes directly to improving patient care. We currently store three types of blood samples: Whole Blood, Plasma, and Serum. These samples are collected under strict ethical governance and linked with anonymised health data to support advanced research.

Coverage

Spatial:
Imperial College Healthcare NHS Trust
Typical Age Range:
18-120
Follow Up:
Continuous

Provenance

Origin

Purposes:
Research cohort
Sources:
  • EPR
  • LIMS
Collection Situations:
Cohort, study, trial

Temporal

Accrual Periodicity:
Monthly
Start Date:
01 January 2025
Time Lag:
2-6 months

Accessibility

Access

Access Request Cost:
Costed a project by project rate
Delivery Lead Time:
1-2 months
Jurisdictions:
UK
Data Controller:
NIHR Imperial Biomedical Research Centre – Digital Health
Data Processor:
NIHR Imperial Biomedical Research Centre – Digital Health

Usage

Data Use Limitations:
General research use
Data Use Requirements:
Collaboration required
Resource Creators:
NIHR Imperial BRC

Format and Standards

Vocabulary Encoding Schemes:
LOCAL
Conforms To:
LOCAL
Languages:
en
Formats:
sql