| NSF Org: |
TI Translational Impacts |
| Recipient: |
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| Initial Amendment Date: | January 22, 2020 |
| Latest Amendment Date: | January 22, 2020 |
| Award Number: | 1938257 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Erik Pierstorff
epiersto@nsf.gov (703)292-0000 TI Translational Impacts TIP Directorate for Technology, Innovation, and Partnerships |
| Start Date: | February 1, 2020 |
| End Date: | October 31, 2021 (Estimated) |
| Total Intended Award Amount: | $224,995.00 |
| Total Awarded Amount to Date: | $224,995.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
98 AMBERFIELD LN DANVILLE CA US 94506-1332 (510)409-1814 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
2953 Indiana St. San Francisco CA US 94107-3007 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | SBIR Phase I |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.084 |
ABSTRACT
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is substantial, considering the fact that gut microbiome is now known to be one of the primary role-players in a range of diseases from asthma to inflammatory bowel disease. These diseases affect more than 120 million people and cost more than $580 B in the US. Standard treatments for many of these diseases have variable efficacy and serious side effects, calling for novel therapeutic approaches. While microbiome therapies (MBTs) have proven useful as a new class of therapeutics, their efficacy is largely affected by highly variable gut microbiota composition between individuals. Since there is no reliable approach to personalize MBTs prior to administration, MBTs are developed as a one-size-fits-all treatment. As a result, a major need exists for the development of cost-effective techniques for personalization of MBTs. By enabling new treatment scenarios and mitigating the risks associated with MBT treatments, our technology will help reduce the cost of treatment and the overall economic burden of these diseases worldwide.
This Small Business Innovation Research Phase I project addresses an essential need at the intersection of microbiome research and precision medicine by developing the first technology to efficiently and reliably personalize MBTs prior to their administration. A growing body of research is unearthing the close associations between a range of diseases and the gut microbiome. As a result, MBTs are emerging as a new paradigm in medicine to fight various diseases by modulating the gut microbiota. A primary challenge, however, is the highly variable compositional and functional landscape of the gut microbiome across individuals. Despite extensive research on gut microbiome medicine over that past several years, a reliable and robust technology has proven elusive due to many impediments. The biggest challenge in personalization of MBTs is the lack of a mechanistic or statistical link between individual-specific omics data and MBT-gut interactions. Using machine learning techniques and advanced optimization approaches, we will develop a computational platform as a virtual, cost-effective tool to personalize MBTs.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
This Small Business Innovation Research (SBIR) Phase I project developed a first-of-its-kind computational technology, at the intersection of microbiome research and precision medicine, for efficient and reliable personalization of microbiome-based therapeutics; enabling the development of more effective microbiome-based therapeutics for a range of diseases such as allergic diseases, metabolic diseases, and gastrointestinal diseases.
Numerous studies have identified close associations between the human gut microbiome and various diseases, affecting a staggering number of people worldwide and, collectively, affecting more than 120 million people and carrying a cost burden of over 580 billion dollars per year, only in the US. These discoveries have led to an increasing interest to modulate the gut microbiome using microbiome-based therapeutics to target different diseases. Primarily, due to the fact that current standard care of treatments for many of these diseases have variable efficacy and serious side effects, calling for novel therapeutic approaches.
Microbiome-based therapeutics contain consortia of live microorganisms, rationally designed to prevent/treat diseases. A primary challenge in design of microbiome-based therapeutics, however, is the high variability of functional and compositional landscape of gut microbial community across individuals, resulting in patient-to-patient variations in response to treatment strategies. Accordingly, since microbiome-based therapeutics directly target the gut microbiota, they demonstrate varied efficacy amongst the target population. Therefore, leading researchers have identified that development of therapeutics tailored to an individual?s gut microbiota will form the new frontier in the field of precision medicine. Therefore, personalization of microbiome-based therapeutics is crucial for effective treatment/prevention. However, all existing microbiome-based therapeutics are developed as one-size-fits-all, primarily because of the lack of a cost-effective approach to personalize such therapeutics.
Despite extensive research on gut microbiome medicine over that past several years, a reliable and robust technology has proven elusive due to many impediments. For example, gut microbiome associated diseases are usually influenced by multiple elements of the target microbiota, which is further complicated by the large and inter-connected network of microorganisms in the gut microbiota. The biggest challenge in personalization of microbiome-based therapeutics is the lack of a mechanistic or statistical link between individual-specific omics data and microbiome-based therapeutics interactions with the gut microbiome.
Through data generation from the technical development and experimental validation of our prototype, we demonstrated that our novel technology could reliably personalize microbiome-based therapeutics for different target gut microbiomes and improve the effectiveness of microbiome-based therapeutics for different patients according to their baseline gut microbiome characteristics. Therefore, this computational platform will increase the odds ratio that microbiome-based therapeutics would be effective; eventually, reducing the overall non-responder rate as well as potential complications associated with the treatment. This technology will ultimately help improve and save the life of millions of patients suffering from a range of diseases in the U.S. and around the world.
Last Modified: 01/30/2022
Modified by: Mohammad Soheilypour
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