Alongside South East Genomics, we are co-leading a national Genomic AI Network, a national community working together to discuss, explore, promote, test and ultimately shape how artificial intelligence should be used within genomic medicine. Our community is made up of clinicians, patients and AI experts with a range of views and perspectives to ensure all voices are heard and considered.
The use of artificial intelligence in healthcare is becoming commonplace. This forum explores how we could and should use AI to benefit genomic medicine. By working together as a community, we will ultimately create a framework to enable the NHS to harness the potential of AI for genomics for the benefit of patients. Hearing from patients and communities will be central to the development of this framework.
Central and South Genomics are leading on the establishment and management of the Genomic AI Network Public Perspectives Forum, with our own PPI Chair Tony Thornburn taking charge of this work. Tony’s valuable experience in patient representation will inform his approach to establishing the network. Under his guidance, we will hear from a wide range of people on how AI could and should be used to benefit genomic medicine.
Public Perspectives: the use of AI in genomic medicine
Another key part of this work for Central and South Genomics is the development of GenePy, an AI tool for optimising Genomic Data analysis – and assessing its impact on improving genomic diagnostic accuracy, reducing manual curation burden, and turnaround-times.
Genomic data analysis is a major contributor to the turnaround time for genomic tests, with significant backlogs, particularly in routine Whole Genome Sequencing (WGS). The analysis of large volumes of complex genomic data is challenging and there is an opportunity to improve efficiencies through implementation of new bioinformatics techniques that could help alleviate the manual curation effort.
This proof-of-concept project aims to leverage AI through the development and evaluation of GenePy, a tool designed to simplify genomic data by assigning a single pathogenicity score to each gene per individual. By doing so, the project seeks to enhance diagnostic accuracy, reduce manual curation, and accelerate processing times. Key deliverables include optimising the GenePy pipeline for large-scale use, testing its impact on retrospective and prospective genomic data, benchmarking against current methods, and exploring broader adoption with commercial partners.
To read more about the Genomics AI Network, please click here.
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