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MultiOmic Health, Mesh Bio Partner to Study Chronic Metabolic Disease for Drug, Dx Development

NEW YORK – UK drug discovery company MultiOmic Health and Singapore-based predictive analytics startup Mesh Bio said Thursday that they are collaborating to apply artificial intelligence to improve diagnostics and advance drug discovery in chronic metabolic disease.

The companies will conduct an observational study in patient populations in Asia that will also look at risk for complications such as chronic kidney disease.

Under the partnership, Mesh Bio will work with its customer network of healthcare providers to recruit patients, while MultiOmic will generate genomic, proteomic, and metabolomic data from anonymized samples taken from the research cohort. MultiOmic will combine this information with existing datasets from both companies to create a multiomics dataset to build AI-based computational biology models for analysis.

The partners also said they would conduct other, unspecified projects to assist with patient stratification for clinical-stage R&D at pharmaceutical and biotech firms.

"Mesh Bio is committed to driving precision clinical interventions in the management of chronic metabolic disease, in order to improve patient outcomes. Our vision is for holistic patient assessment, powered by analytics on full-stack biology," Mesh Bio Cofounder and CEO Andrew Wu said in a statement.

"This partnership gives us access to a population base in Asia exhibiting high and increasing prevalence of metabolic syndrome-related conditions," added Robert Thong, cofounder and CEO of MultiOmic.

"Longitudinal multiomics data combined with deep clinical phenotyping is essential to developing transformative therapeutics and diagnostics in chronic multi-factorial diseases," said Angeli Möller, cofounder of the Alliance for Artificial Intelligence in Healthcare. "In contrast to most of the historical research for these diseases that has relied on Caucasian patients, this partnership will generate new and much needed insights specific to populations in Asia."

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