| EPSRC Reference: |
EP/X041298/1 |
| Title: |
[SaFEGen]: A Statistical Framework for efficient Evidence Generation in diagnostics |
| Principal Investigator: |
Wilson, Dr K J |
| Other Investigators: |
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| Project Partners: |
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| Department: |
Sch of Maths, Statistics and Physics |
| Organisation: |
Newcastle University |
| Scheme: |
Standard Research |
| Starts: |
01 January 2024 |
Ends: |
31 December 2026 |
Value (£): |
663,175
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| EPSRC Research Topic Classifications: |
| Statistics & Appl. Probability |
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Summary on Grant Application Form |
Diagnostic tests are a critical component of any modern healthcare system: it is estimated that approximately 70% of clinical decisions are influenced by the use of in vitro diagnostics (IVDs). They are used both to enable diagnosis and to rule out causes of ill health. They are also used to monitor, screen and assess people for potential health problems. Increasingly, they allow people with chronic disease to manage their own conditions. However, less than 1% of the NHS budget is dedicated to the uptake of new and innovative IVD products, and it typically takes more than 10 years and considerable resources to achieve widespread adoption of a novel diagnostic test. Despite these challenges, diagnostics play a significant role in the UK economy, employing over 8,000 people, and in the UK the IVD market accounts for over £1.1 billion pounds annually.
An independent report on diagnostic tests was commissioned by the Royal Statistical Society (RSS) in part since "the RSS has been particularly concerned that many new diagnostic tests for SARS-CoV-2 antigen or antibodies were coming to market for use both in clinical practice and for surveillance without adequate provision for statistical evaluation of their analytical and clinical performance. Against a wider background of concern about standards applied to the evaluation of in vitro diagnostic tests, there was a need for clear statistical thinking on the principles of diagnostic testing in general, and their application in a pandemic in particular". One of the key recommendations of the report was that "undertaking well designed, adequately powered and correctly analysed studies of the clinical performance of an in vitro diagnostic is important for each intended use of the test." In this project we aim to develop a statistical framework that ensures that not only are diagnostic studies well designed, adequately powered and correctly analysed, but also make the most efficient use of data between development stages and takes advantage of cutting-edge advances in conventional clinical trial design.
The SaFEGen project will achieve a step change in the time to market of novel diagnostic tests by developing cutting-edge integrated statistical methods for the design and analysis of diagnostic studies from inception to adoption into the NHS. SaFEGen will make best use of data to save time and money in the development of novel diagnostic tests by developing adaptive (modifying a study design during a study based on data observed so far) and seamless (combining separate studies to reduce time and increase efficiency) designs. The effect of the uptake of the framework will be a faster and more efficient evidence generation process for development of diagnostics, with no loss of rigour, and, ultimately, better outcomes for patients when high-quality diagnostics reach the NHS more quickly.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.ncl.ac.uk |