London, UK, and Singapore, 30th June 2022 / Sciad Newswire / MultiOmic Health, an artificial intelligence (AI)-enabled drug discovery company, and Mesh Bio, a digital health startup transforming chronic disease management through predictive analytics, today announce their partnership to conduct an observational clinical study on patients with chronic metabolic disease and increased risk of complications such as chronic kidney disease. The partnership will provide access to data from patient populations in Asia that have historically been underrepresented in chronic metabolic disease studies.

Mesh will collaborate with its network of healthcare provider customers to recruit patients for the study. MultiOmic will generate genomic, proteomic, metabolomic and potentially other omics data from anonymized body fluid samples. These will be combined with anonymized data from clinical and diagnostic tests for both companies to build a rich multi-omics dataset and derive AI-based computational biology models.

The study will enable MultiOmic and Mesh to progress their respective R&D programs to develop precision therapeutic and diagnostic products that will transform the lives of patients with metabolic syndrome-related conditions. They will also jointly conduct collaborative projects to enhance patient stratification for other biopharma and medtech companies’ clinical-stage R&D programs.

Metabolic syndrome-related conditions such as type 2 diabetes mellitus (T2D), chronic kidney disease (CKD), atherosclerotic cardiovascular disease (ASCVD), non-alcoholic fatty liver disease (NAFLD) and polycystic ovary syndrome (PCOS) arise from a common set of risk factors present in half the world’s adult population. These age-related conditions can lead to serious consequences, including heart attack, stroke, blindness, nerve damage, foot amputation, kidney dialysis and liver failure. Prior to the COVID-19 pandemic, they accounted for half the world’s deaths and nearly US$ 2 trillion in global healthcare spending1. This burden will be further exacerbated by the pandemic. A significant proportion of COVID-related hospitalizations and fatalities arose in patients with metabolic syndrome conditions2 and recent studies have indicated that COVID survivors have an increased risk of being diagnosed with T2D3 and CKD4.

“Longitudinal multi-omics data combined with deep clinical phenotyping is essential to developing transformative therapeutics and diagnostics in chronic multi-factorial diseases,” said Angeli Möller, PhD, Vice-Chairperson and co-founder of the Alliance for Artificial Intelligence in Healthcare, the global advocacy organization for applying AI solutions to improve patient lives. “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.”

“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 fullstack biology,” said Andrew Wu, PhD, Co-Founder and CEO of Mesh. “We are delighted to partner with MultiOmic Health on this important study for patients in Asia. Their therapeutic development programs for metabolic disease intervention have deep synergies with Mesh Bio’s mission to develop digital care delivery solutions for these diseases.”

“This partnership gives us access to a population base in Asia exhibiting high and increasing prevalence of metabolic syndrome-related conditions,” said Robert Thong, Co-Founder and CEO of MultiOmic. “We are delighted to collaborate with Mesh Bio as a like-minded and capable strategic partner working with healthcare providers that have many patients in our target chronic medical conditions. Our product development programs and technical teams also complement each other.”


For further information, please contact:

MultiOmic Health
Esra Berkol

Mesh Bio via Redhill Communications
Daphne Quek

Sciad Communications, Media Relations
Richard Anderson / Sophie Protheroe
T: +44 (0)20 3405 7892

Notes to Editors

About Mesh Bio

Mesh Bio is a digital health startup focused on addressing the growing global clinical burden of metabolic diseases driven by an aging population, and challenges in care delivery. Mesh Bio develops clinical decision support analytics and automation solutions for management of chronic disease, such as cardiovascular disease and type 2 diabetes. These solutions enable data driven care delivery, improving patient engagement, and health outcomes. Mesh Bio’s DARA® is a Health Intelligence Platform that empowers precision clinical intervention at scale. Predictive analytics on multidimensional health data streams and clinical workflow automation enables health care providers to enhance operational efficiency, personalize care delivery and increase patient engagement.

About MultiOmic Health

MultiOmic Health is an AI-enabled drug discovery (AIDD) company dedicated to chronic multi-factorial diseases, with an initial focus on the metabolic syndrome-related conditions. It partners with research institutions, healthcare providers and healthtech companies to source de-identified patient data and samples. Drawing upon these carefully selected and exclusive data sources, MultiOmic’s MOHSAIC® platform combines integrated multi-omics analysis and computational systems biology modeling with targeted wet laboratory experiments to originate novel precision therapeutic concepts. MultiOmic subsequently partners with established biopharma companies to take its therapeutic concepts into global clinical trial programs 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.

1) MultiOmic Health estimates from aggregating published statistics for cardiovascular disease, type 2 diabetes, chronic kidney disease, non-alcoholic fatty liver disease and polycystic ovary syndrome.
2) Diabetes Care 2021;44(9):1916–1923
3) Article in Nature:
4) Article British Medical Journal:

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