HistoIndex and Consortium Partners Awarded S$1.2M for the Development of AI-based Diagnostics Tool in the Identification of High-Risk Nonalcoholic Fatty Liver Disease Population
HistoIndex joins forces with a consortium of partners from NHS Health Boards,UK universities and technology companies for the development of a novel AI-based integrated diagnostic tool.
There is currently no available method to accurately identify patients with NAFLD who are at a higher risk of developing a more progressive form of liver disease (non-alcoholic steatohepatitis or NASH) that can lead to cirrhosis,liver cancer and premature death. NASH is an unmet liver condition that awaits an FDA-approved treatment.
Having an AI-based diagnostics tool that provides a fully quantitative and accurate assessment of fibrosis will provide clinicians with a deeper understanding of the disease and its progressive features,which will aid in enrolling high-risk patients for NASH clinical trials.
SINGAPORE,Dec. 15,2020 -- HistoIndex,an AI-based digital pathology company in the stain-free assessment of NASH and other fibrosis,has joined INTErPRET-NAFLD,an international liver R&D collaboration aimed at developing an integrated precision AI diagnostics tool for High-Risk Nonalcoholic Fatty Liver Disease (NAFLD). Led by the University of Edinburgh,the multi-centre collaboration was recently awarded with a S$1.2M (750,000 Euros) innovative research grant. This will support the collaborators' mutual goal of developing and validating a tool that can accurately identify NAFLD patients who are at a higher risk of progressing to NASH,which can lead to adverse outcomes such as the irreversible cirrhosis,liver cancer and premature death.
NAFLD is the most common liver disease with a worldwide prevalence of 25%. It is caused by non-alcoholic and metabolic conditions like obesity,which is rising in low- and middle-income countries,particularly in urban settings. Looking at the increase in obesity from childhood,diabetes and other factors,the prevalence of NAFLD along with the proportion of those with advanced liver disease is projected to increase [1]. The presence of fibrosis is the most important predictor of adverse outcomes in NAFLD and NASH. However,challenges in drug development today include enrolling such patients who are at risk of developing advanced fibrosis rapidly [2]. There is currently no FDA-approved treatment for NASH.
Says Professor Jonathan Fallowfield,Chair of Translational Liver Research at the University of Edinburgh's Centre for Inflammation Research,and clinical lead of the UK-based SteatoSITE project,"I'm delighted to be working with HistoIndex on this important project. By evaluating advanced liver tissue metrics in the context of gene expression signatures and real-world clinical data,we hope to develop a new and actionable tool for predicting disease progression and clinical outcome in NAFLD. This could be transformational for clinical care pathways and efficient trial design."
Identifying High-risk patients with Stain-free AI Digital Pathology
HistoIndex's AI-based digital pathology platform,with its Second Harmonic Generation (SHG) microscopy,will be used for the imaging of unstained liver biopsy slides from SteatoSITE* to obtain granular data on visible as well as subtle fibrosis in a fully quantitative,objective and consistent manner; this is usually a challenge to obtain with existing stain-based biopsy slides. The augmented data will greatly reinforce the identification of patients who are fast or slow progressors of NASH. HistoIndex's AI digital pathology platform is currently used in multiple FDA Phase II/III NASH clinical trials for the continuous measurement of fibrosis along with NAFLD disease activity.
Says Dr Gideon Ho,Chief Executive Officer of HistoIndex,"HistoIndex is excited to be part of this consortium that accelerate advances for patients with progressive NAFLD,as they are in urgent need of treatment. Being in this collaboration as well as partnerships with other consortiums focused on NASH,HistoIndex is strategically positioned to carry out a pivotal role to drive initiatives in NASH screening,diagnosis,and treatment. Also,special thanks to the teams in EUREKA Globalstars,Enterprise Singapore and Innovate UK for working tirelessly during this period of time to administer the research grant."
Says Mr. Clemens Zielonka,Managing Director,Eureka Association,"I am delighted to lend our support to this R&D project,which is an excellent example of how Eureka mobilises partners in different parts of the world to collaborate on projects whose outcome has significant societal benefit. Through Eureka-- the world's biggest public network for international cooperation in R&D and innovation,present in over 45 countries,Singaporean and British partners in this project are helping improve patient management with AI technology. HistoIndex together with a consortium of British partners,having participated in a recent Eureka-Globalstars call for international R&D collaboration,joins one of thousands of cross-border Eureka collaborations,bringing innovative solutions to improve standards for better patient outcomes."
Notes for Editors
*SteatoSITE is a GBP1.7M Innovate UK-funded collaboration that created a pan-Scotland patient database of ~1000 cases with available tissue from the complete NAFLD disease activity and fibrosis stage spectrum. Patient timelines are fully annotated with clinical features,outcome development of up to 12 years,and blood tests,all time-stamped with respect to the tissue acquisition point. SteatoSITE allows the sharing of genomic and clinical information from patients with NASH,leading researchers to a deeper understanding of appropriate tests and treatments that may be most effective for individual patients.
References
Nonalcoholic Fatty Liver Disease 2020: The State of the Disease
Thomas G.Cotter,Mary Rinella. Gastroenterology Volume 158,Issue 7,May 2020,Pages 1851-1864.
Looking Into the Crystal Ball: Predicting the Future Challenges of Fibrotic NASH Treatment
Alkhouri N,Lawitz E,Noureddin M. Hepatol Commun. 2019;3(5):605-613. Published 2019 Mar 28. doi:10.1002/hep4.1342.
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