MultiOmic Health and Queen’s University Belfast join forces to transform diabetic kidney disease diagnosis 

Wed, 07/02/2024 - 07:00

London, UK, 7th February 2024 / Sciad Newswire / MultiOmic Health, an artificial intelligence (AI)-enabled drug discovery company, is embarking on a collaborative project with the Centre for Public Health at Queen's University Belfast (QUB) in Northern Ireland to develop data-driven diagnostic tools for Diabetic Kidney Disease (DKD). The two-year project is partially funded by a grant recently awarded to MultiOmic Health under Innovate UK's £20 million Advancing Precision Medicine programme, supporting industry-led research projects to enable more accurate diagnosis and treatment stratification within the UK National Health Service (NHS).1  

 

MultiOmic will deploy its MOHSAIC® platform to analyse data generated from de-identified samples collected previously as part of the Northern Ireland COhort for the Longitudinal study of Ageing (NICOLA) and the Finnish Diabetic Nephropathy Study (FinnDiane). The project seeks to tailor DKD treatment based on patients’ underlying characteristics, leading to improved health outcomes for patients. 

 

MultiOmic and QUB will draw on their collective expertise to explore molecular-level similarities and differences in kidney disease amongst patients with type 1 and type 2 diabetes. The aim of the project, which began in December 2023, is to identify diagnostic and prognostic biomarkers for diabetic kidney disease progression and likely complications within specific patient subpopulations. 

 

Chronic kidney disease (CKD) is common in people with both type 1 and type 2 diabetes and has a substantial economic cost of £7 billion per year in the UK, including £6.4 billion in direct costs to the NHS.2 The increasing prevalence of CKD in people with diabetes poses a significant challenge, contributing to increased risk of kidney failure and cardiovascular events. Current treatment options adopt a one-size-fits-all approach, failing to address the tailored needs of the diverse diabetes population. MultiOmic’s data-driven approach aims to overcome these limitations, offering a way to advance personalised approaches for DKD management. 

 

“Previous studies in diabetic kidney disease lacked molecular-level comparisons using the multiple omics modalities that are needed to understand the combined impact of genetic, environmental and lifestyle factors," explained Robert Thong, CEO of MultiOmic Health. "Through this approach, we aim to deepen our understanding of the factors contributing to the onset and progression of this disease across the diabetes population. This first-of-its-kind study has the potential to revolutionise how we approach and treat diabetic kidney disease.” 

 

"Our collaboration utilises resources from the NICOLA study, which was initiated in 2014 to investigate ageing and lifestyle impact on health outcomes," said Bernadette McGuinness, Clinical Professor of Ageing at QUB and Principal Investigator of the NICOLA study. "With over 8,500 participants from Northern Ireland aged 50 and above, the study provides a robust baseline to leverage further research. Combining QUB’s phenotype and molecular expertise with MultiOmic’s computational analysis capabilities, we are excited to use this opportunity to generate multi-modal omics data for a specific sub-cohort to uncover new insights in DKD.”  

 

“Since 1997, the Finnish Diabetic Nephropathy Study (FinnDiane) has become a pivotal resource in diabetes research, playing a key role in uncovering the risk factors and mechanisms of diabetic complications in patients with type 1 diabetes,” said Niina Sandholm, co-Principal Investigator of the study group. “Now, in this project, we are eager to explore the molecular parallels of kidney disease between type 1 and type 2 diabetes, helping to push forward strategies in diabetes prevention and treatment.” 

 

The outcomes of this project will lay the groundwork for future diagnostic tools, providing clinicians with valuable insights into disease progression, complication risks, and drug responsiveness. This patient-centric approach to DKD management promises to optimise healthcare resource allocation, reduce disease progression, and enhance the overall quality of life for individuals with DKD. 

 

ENDS

 

For further information, please contact:

 

MultiOmic Health 
Esra Berkol 
E: esra@multiomic.health 

 

Queen’s University Belfast 
Sian Devlin 
E: s.devlin@qub.ac.uk 

 

Innovate UK, Media Relations 
Emma Reed 
E: emma.reed@iuk.ktn-uk.org 

 

Sciad Communications, Media Relations 
Sophie Protheroe 
E: multiomic@sciad.com 
T: +44 (0)20 3405 7892 

 

Notes for Editors

 

About MultiOmic Health 

 

MultiOmic Health is an AI-enabled drug discovery (AIDD) company dedicated to developing novel treatments for metabolic syndrome-related conditions, the world’s largest healthcare burden. It partners with research collaborators across the UK NHS and continental Europe to source de-identified clinical records and patient bio-samples for precision medicine discovery.

 

MultiOmic’s MOHSAIC® platform combines integrated multi-omics analysis and computational systems biology modelling with targeted wet laboratory experiments. Defined patient subpopulations with distinct clinical phenotypes and multi-omics signatures are used to originate novel precision therapeutic concepts that will lead to smaller and shorter clinical trials with higher success rates compared to historical programmes in this disease space. MultiOmic subsequently partners with established biopharma companies to take its therapeutic concepts into global clinical trial programmes and market the ensuing medicines. Its experienced leadership team blends commercial, technical and operational expertise from across the pharma, systems biology and AI/big data arenas. 

 

All participant information provided to MultiOmic by its research collaborators is de-identified, fully consented and in compliance with relevant privacy and data protection legislation, regulations and guidance, including but not limited to the General Data Protection Regulation (GDPR) in both the European Union and the United Kingdom. 

 

About Queen’s University Belfast 

 

A member of the Russell Group UK's 24 leading research-intensive universities, Queen’s University Belfast is an international centre of research and education, with a student-centred ethos. Queen’s is ranked 4th in the world for international outlook (Times Higher Education World University Rankings 2024), 2nd in the UK for entrepreneurial impact (Octopus Ventures, 2022) and in the top 150 in the world for research quality (Times Higher Education World University Rankings 2024). Queen’s is also ranked 85th in the world in the Times Impact Rankings 2023. 

 

Our research shapes worlds and continues to make a difference to lives and livelihoods, with 88% assessed as world leading or internationally excellent (Research Excellence Framework 2021). 

 

The university is a lead partner in the Belfast Region City Deal which will unlock £1 billion of transformative co-investment, bringing forward projects in advanced manufacturing, clinical research and secure, connected digital technologies. 

 

Queen’s sits at the heart of the diverse and vibrant city of Belfast which has the lowest cost of living in the UK (Mercer Cost of Living City Ranking 2023). 

 

About Innovate UK 

 

Innovate UK is creating a better future by inspiring, involving and investing in businesses developing life-changing innovations. 

 

We provide targeted sectors with expertise, facilities and funding to test, demonstrate and evolve their ideas, driving UK productivity and economic growth. Join our network and communities of innovators to realise the potential of your ideas and accelerate business growth. 

 

Innovate UK: inspiring business innovation. 

 

References 

 

  1. https://apply-for-innovation-funding.service.gov.uk/competition/1573/overview/910e2dcf-796d-49e4-bf12-efa1f2be06db  
  2. https://www.kidneyresearchuk.org/wp-content/uploads/2023/06/Economics-of-Kidney-Disease-full-report_accessible.pdf