The Glasgow Molecular Pathology Node will exploit, align and integrate substantial existing infrastructure to create a dynamic platform to accelerate molecular pathology development.

The University is a founding member of Glasgow Biomedicine which supports clinical research by enabling access to an NHS patient base of 2.8million with high levels of morbidity and health inequality.

Available infrastructure includes: the Robertson Centre for Biostatistics (internationally recognised in clinical trials, epidemiology and health economics); state-of-the-art clinical research facilities; excellent biorepository; and, through the Safe Haven and The Farr Institute, the ability to readily access high quality data via the Community Health Index (CHI) number, a unique patient identifier used in Scotland for all health communications, enabling detailed patient-based analysis and follow-up.

Our £10M Wolfson Wohl Cancer Research Centre (WWCRC) has significant expertise and capacity in genomics. Our Precision Medicine Laboratory is equipped with cutting edge sequencing technology including a fleet of Illumina HiSeq XTENs and will be a satellite of NHSGGC Pathology and Molecular Genetics to satisfy diagnostic laboratory regulatory approval requirements. Processes will be linked via the Node for sample inflow (e.g. using 2D barcodes) and return of results. Our investment includes significant computing power with duplicate systems to comply with evolving regulatory frameworks for diagnostic NGS data analysis and storage. The WWCRC also houses the Glasgow Polyomics Facility, encompassing NGS, microarrays, proteomics and metabolomics.

Cross disciplines

Across disease categories and with EPSRC funding, Glasgow engineers, materials chemists and polyomics researchers are developing novel devices capable of cheap and easy quantification of bespoke metabolite biomarkers within clinical diagnostic laboratories. The computing science contribution is cross cutting: from computational procedures for model parameter estimation, and inference mechanisms for handling large and diverse data sets, to new technologies for modelling and analysing pathway mechanisms based on process algebras and logics. Prerequisite to these activities, and critical for validation of biomarkers emerging from high-throughput studies, is a computational environment for seamless linkage of genomic, proteomic and metabolomics data with clinical, laboratory and histopathologic data arising from those patients: its provision will be enabled through the Glasgow Node.

Having the confidence to make an early ‘no-go’ decision is important to avoid wasting valuable resources by taking forward the development of biomarkers unlikely to change clinical practice. Health economics enables prioritisation across the disease-based workstreams by providing a common metric by which to make go/no-go decisions in relation to taking forward promising biomarkers. The starting point is an early assessment of clinical utility in different disease areas. Clinical utility at the patient level is scaled up by the size of the population to give an assessment of the Expected Value of Perfect Diagnostic Information. This can then be used to prioritise promising biomarkers and gives the framework for commercial development. Final downstream benefits to the health system/population can be measured in terms of health gain (quality adjusted life years: QALYs). By focusing on value early, health economic assessment will enable efficient development of appropriate biomarkers to maximise population health and economic growth potential.

Research capacity and facilities