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Sarcoidosis

Population Size

Not reported
Population Size statistic card

Years

2022

Years statistic card

Associated BioSamples

None/not available

Associated BioSamples statistic card

Geographic coverage

International

Geographic coverage statistic card

Lead time

2-6 months

Lead time statistic card

Summary

The aim of the project is to accelerate the development of lung disease treatments to improve outcomes for all patients. This is the first time that significant volumes of data from minority ethnic people will be structured and made available for complex lung disease research and drug development.

Documentation

Idiopathic Pulmonary Fibrosis (IPF) is a type of complex lung disease that affects roughly 50 in every 100,000 people. It causes the lungs to become scarred, leading to severe breathlessness and coughing, and owing to a lack of effective medicines and treatments, it currently has a survival time worse than most cancers. Applying cutting-edge AI tools, to unlock insights from existing IPF patient data, could help extend the lives of thousands of UK patients each year.

Dataset type

Health and disease

Provenance

Image contrast

Not stated

Biological sample availability

None/not available

Structural Metadata

Details

Publishing frequency

Static

Version

1.0.0

Modified

30/04/2025

Citation Requirements

SDE031

Coverage

Start date

01/09/2022

Time lag

2-6 months

Geographic coverage

International

Accessibility

Language

en

Alignment with standardised data models

LOCAL

Controlled vocabulary

LOCAL

Format

SQL

Data Access Request

Dataset pipeline status

Not available

Access rights

Information Governance and Ethics - West Midlands Secure Data Environment (https://westmidlandssde.nhs.uk/information-governance-and-ethics)

Time to dataset access

2-6 months

Access request cost

Please email wmsde@uhb.nhs.uk

Access method category

TRE/SDE

Access service description

Data Request Process - West Midlands Secure Data Environment (https://westmidlandssde.nhs.uk/research/data-request)

Dataset Types: Health and disease

Collection Sources: