
Pathogen Program
Transforming how the world understands and responds to infectious disease.
Graham Binns
Graham Binns is Director of Data Platforms for the Pathogen Program at EIT. He leads the technology platforms that support the programme's scientific work: the pathogen data platform and isolate resource, research computing, and the digital systems used to acquire, manage and connect laboratory data. He also leads the development of research tools and the digital capabilities needed for diagnostic-device research and development.
Prior to joining EIT, Graham led the Architecture and IT Strategy function at Genomics England. His work covered the secure cloud-first research environment, integration of whole-genome testing NHS pathways, hybrid-cloud high-performance computing and partnerships that enabled genomic research at scale. He also supported genomics transformation initiatives including applying multimodal AI and machine learning to accelerate discovery, the newborn screening study and distributed nanopore sequencing for rapid cancer diagnostics
Earlier in his career, Graham led architecture at NHS Improvement, following its evolution from Monitor into an organisation focused on technology-enabled improvement across the NHS. He shaped national digital and analytical services designed to improve productivity, quality and patient safety, and served on technology advisory and programme governance boards. He has also advised NHS Online and organisations across the public and private sectors on technology strategy, target architecture and digital transformation.
Graham holds a degree in Computer Science from the Victoria University of Manchester. Outside of work, he enjoys trail running, diving and watchmaking.
Latest News
Work withGraham Binns
The Pathogen Program is developing an end-to-end diagnostic tool to support the diagnosis, prevention and treatment of infectious diseases, starting with respiratory infections and sepsis. A database of global sequencing data will provide the crucial information needed to explain the origin of the pathogen and whether it is resistant to existing treatments. This type of full-stack system will be beneficial in diagnosing disease and supporting pandemic preparedness in the future.


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