MultiOmic Health is using a data-driven AI-enabled approach to develop tailored therapeutics for specific subpopulations of patients with metabolic syndrome-related conditions, which affect around half of the adult population worldwide
TechBio company MultiOmic Health (MOH) initially set out to build an artificial intelligence (AI)-enabled platform to research metabolic dysfunction-associated conditions. In just three years, not only has the company proven that its approach could revolutionize the diagnosis and treatment of these and similar diseases, but it has also transformed from a data-science startup into a pipeline company with novel drug programs.
Half the world’s adult population is affected by metabolic dysfunction or its downstream complications, such as heart disease, type 2 diabetes, chronic kidney disease and non-alcoholic fatty liver disease. Over $2 trillion per year (1.6 times more than the corresponding figure for cancer) is spent globally on treating these patients—and the cost is forecast to exceed $5.5 trillion by 2040 according to MOH’s analyses of published statistics. Unfortunately, there is huge variation in how these conditions progress, and many patients do not respond to one-size-fits-all, standard-of-care treatments. To address this enormous unmet need, MOH focuses on understanding and defining disease subpopulations, to develop corresponding biomarkers and precision medicines.
Deep bespoke datasets
First and foremost are the datasets. MOH carefully curates patient cohorts with specific clinical characteristics and disease stages, from studies previously conducted by its academic and healthcare collaborators. “Metabolic disorders take years to develop and are driven by a combination of genetic, environmental and lifestyle factors. To untangle this complexity, we capture longitudinal lab test results, diagnoses and medication information, and then generate new omics data (genetics, epigenetics, proteomics and metabolomics) from frozen samples collected in the original studies,” explained Celia Antonio Schell, MOH’s COO. “Building the right datasets is challenging but crucial—it’s both a skill and an art.”
MOH applies its platform to the resulting bespoke real-world patient datasets to discover endotypes—that is, patient subpopulations with distinct clinical phenotypes and unique omics signatures. This enables the development of biomarker models for patient stratification that will eventually be implemented as clinical and companion diagnostics (Fig. 1). Moreover, by combining computational analyses, literature reviews and wet lab experiments, MOH can identify and validate novel drug targets for particular endotypes.
Fig. 1 | From bespoke datasets to precision medicines and companion diagnostics. AUC, area under curve; IUO, investigational use only.
Platform proof-of-concept in diabetic kidney disease
Initial work was conducted in diabetic kidney disease (DKD), a therapeutic area with no disease-modifying treatments that reliably prevent kidney failure. In November 2024, after analyzing bio-samples and data from a study in England, MOH announced that it had stratified DKD patients into novel patient endotypes differentiated by disease-progression rate and distinct omics signatures. These endotypes were replicated in a separate larger Scottish cohort, validating their robustness and applicability. Biomarker models to predict a patient’s trajectory at an earlier disease stage were also developed and verified in a large independent cohort (the UK Biobank), and a US patent application has been filed.
“Our ability to identify patient endotypes and predict progression rates at an early stage of the disease marks a pivotal advance in precision medicine for DKD, enabling a shift from reactive to proactive care,” said Robert Thong, MOH’s co-founder, executive director and CEO. “Physicians can determine the right treatment strategy for each patient, and researchers can conduct smaller, leaner clinical trials.”
Furthermore, MOH is the first organization to identify and validate novel drug targets for treating specific subpopulations within the wider DKD patient group. By initiating multiple therapeutics programs to engineer new precision medicines based on these targets, the company has established a novel drug pipeline.
Partnering to pursue precision therapies
MOH’s first set of therapeutics programs focus on treating subpopulations of patients with DKD. Many of the drug targets identified by MOH are also relevant to other chronic kidney conditions that cause fibrosis or impact glomerular function. In April 2025, MOH announced a collaboration with Alloy Therapeutics to discover first-in-class renal tissue–targeting drugs.
MOH aims to extend its discovery platform into other chronic multifactorial conditions exhibiting heterogeneous disease-progression trajectories. Other complications of metabolic dysfunction are the obvious next focus. MOH is seeking pharmaceutical collaborators to assemble and analyze datasets in these indications to discover biomarkers and drug targets.
“Using a unique combination of deep longitudinal patient datasets, AI-enabled data science and experimental biology, MOH can discover endotypes and create the corresponding novel precision medicines and companion diagnostics,” said Michael Sierra, a pharmaceutical R&D veteran who recently joined MOH as its CSO. “This approach will transform the economics and success rates of clinical trials, leading to highly efficacious disease-modifying therapies for the benefit of patients and the healthcare system.”
