A Model Approach To Microbiome Therapeutics
Posted 16th November 2017 by Jane Williams
By any measure, momentum in the microbiome space keeps building. The 2017 Silicon Valley Bank mid-year Microbiome Investment Trends report provides one of the most up-to-date snapshots: close to USD 1 billion has been invested in microbiome companies globally since 2010, and SVB’s analysts predict the total capital in disclosed equity investments in 2017 alone could be reaching north of USD 400 million by year-end. And my own analysis of Microbiome Partnership Trends, published earlier this year, documents the dramatic increase in partnerships during 2016, a trend that has shown no signs of slowing down.
But with such impetus also comes great responsibility (and pressure…) to deliver. Clearly, many fundamentals are in place – therapeutic need, novelty, market size. Unlocking the full therapeutic potential of the microbiome, however, still hinges on us reaching a deeper understanding of the complex dynamics and interactions of the microbiome.
“Features such as prevalent organisms, functional networks and metabolic pathways have been used to describe microbiomes, both in health and in disease,” says Curtis Huttenhower. “But adding population-scale epidemiology and deep clinical studies into the mix will be necessary to help refine microbiome-centric disease models. Such highly integrated models of health and disease will, in turn, offer the key to accelerating translation in the microbiome space.” Huttenhower is associate professor of computational biology and bioinformatics in the Harvard School of Public Health and a co-leader of the Inflammatory Bowel Disease (IBD) Multi’omics Database.
And this is exactly the approach some players are adopting: to build drug development strategies that start off by establishing integrated microbiome-centric disease models that provide the basis for designing and optimizing potential therapeutic interventions.
Second Genome’s drug discovery platform relies on the integration of microbiome and host biology data for the identification of novel targets and drugs. A proprietary data analysis platform enables the company to carry out an integrated evaluation of microbial composition and function both in health and in disease. New insights are then used to design therapeutic interventions ranging from small molecules to microorganisms to affect relevant microbe-microbe and microbe-human interactions.
Second Genome’s lead candidate is SGM-1019, a small molecule inhibitor of an undisclosed target in IBD-related inflammation and pain. SGM-1019 has completed a Phase I trial. The company has additional preclinical programs for a range of chronic indications.
Similarly, Seres Therapeutics uses a proprietary approach to analyze the composition and biology of the gut microbiome in health and disease. In addition, Seres evaluates the microbiome environment to refine the search for an optimal combination of healthy donor-derived microorganisms to correct dysbiosis. The company draws from its extensive library of well-characterized bacterial strains to achieve this goal.
Recently, Seres expanded its modeling capabilities by entering into a collaboration with Emulate, a biotech developing a micro-engineered, living-tissue-based intestine-on-a-chip, to test novel bacterial combinations with therapeutic potential.
Seres has SER-262, a ‘designer cocktail’ of bacteria developed using the above principles, in a Phase 1b study for treating adults with primary Clostridium difficile infection. Other preclinical products being developed using the integrated disease model platform include SER-287 and SER-301 for IBD and SER-155 for the prevention of graft-versus-host disease.
Vedanta adds yet another twist to the approach by generating models of disease that include human datasets from interventional studies obtained from the company’s clinical collaborators. By incorporating deep clinical datasets, Vedanta is in a position to identify strong associations between bacterial engraftment and clinical response. Proprietary bioinformatic tools then provide the means for creating consortia that optimize the pharmacological interactions of the assemblages with their human host.
Vedanta has VE303, an oral product candidate consisting of a rationally defined live bacterial consortium to treat C. difficile infection. A second product candidate, VE202, is in development for IBD in partnership with Janssen.
Finally, new company Gusto Global, a recent University of Chicago startup, is taking the integration of microbiome composition and functional data with databases from human studies to the farthest point of the four companies featured here. Gusto Global’s proprietary computational modeling platform allows the company to predict how bacteria interact with each other and the human immune system in a patient-relevant context. Based on the insights gained from directed studies, Gusto Global decides on the indications with the highest potential for subsequent drug development and contextualized biomarker discovery.
According to Daniel van der Lelie, CSO and co-founder of Gusto Global, “the key to advancing innovation in the microbiome space is to develop bioinformatics platforms that allow researchers to build models of dysbiosis and potential interventions by nesting biotherapeutic models within metabolic and functional models of the human host.” The final goal is to stabilize potential biotherapeutics by designing consortia that maximize functional diversity while minimizing the metabolic burden on individual therapeutic bacteria.
Gusto Global has two programs in preclinical development for undisclosed indications.
Many hurdles remain on the path to unraveling the intricate biology of the microbiome, but these four players, together with others coming on the scene as we speak, are well on their way to reaching that goal.
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Gaspar Taroncher-Oldenburg is Consultant-in-Residence for Global Engage. He was previously Founding and Managing Editor of Nature’s SciBX: Science-Business eXchange (now BioCentury Innovations) and scientific editor of Nature Biotechnology.
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