Symbiont, which has been peer reviewed in Gastroenterology, is a process that identifies and selects ingredients that address bacterial and fungal dysbiosis in target cohorts uncovered in BIOHM’s proprietary dataset.
BIOHM’s dataset, one of the largest in the world, combines bacterial and fungal genetic sequencing with more than 50 metadata points.
This collaboration marks a significant step forward in the development and commercialisation of condition specific dietary supplements based on a more complete understanding of the microbiome.
It is believed that Symbiont will revolutionise the product formulation process, allowing for thousands of iterations to quickly optimise ingredient selection for dietary supplements.
“In navigating the intricate web of the microbiome's influence on our health and longevity, this important initiative will expedite and amplify our capacity to develop innovative, effective ingredients targeted at addressing critical health challenges,” says Sam Schatz, CEO of BIOHM Health.
BIOHM Health is renowned for its groundbreaking work in microbiome research, leveraging its dataset to develop the next generation of targeted microbiome-based products.
Currently, most microbiome-targeted products only focus on bacteria when, in fact, fungi are an equally important component of the microbiome.
With a mission to unlock the potential of the microbiome, the company is committed to leveraging cutting-edge technology to address key health challenges.
“We believe the microbiome is at the centre of human wellness and Symbiont will more precisely hone our formulations to target organisms that cause dysbiosis,” said Dr Mahmoud Ghannoum, Chief Scientific Officer at BIOHM Health and Director of the Center for Medical Mycology at Case Western Reserve University.
The partnership with Virginia Tech will focus on accelerating the capabilities of BIOHM's Symbiont platform through the development of predictors using state-of-the-art machine learning algorithms.
These predictors will link microbial populations to specific phenotypes, enabling the extraction of features for biomarker identification. By harnessing the power of deep machine learning, BIOHM aims to accelerate the discovery of novel ingredients and formulations with targeted health benefits.
In addition to machine learning, Symbiont will incorporate intelligent search functionality to analyse public data sources such as research publications, ingredient efficacy studies, patents, and clinical trials.
This innovative approach will enable the identification of proprietary formulations that can modulate identified biomarkers in targeted cohorts, ultimately enhancing the efficacy of dietary supplements.
Dan Sui, Virginia Tech’s Senior Vice President for Research and Innovation, said: "Research collaborations with industry are key to fuelling innovative solutions and scientific breakthroughs that ultimately improve the human condition. We are excited to work closely with BIOHM using our machine learning expertise.”
