Abstract & Details
Description
Award ID: 2051417
The broader impact /commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to help the 32 million people in the US suffering from Food Allergy (FA). FA brings psychological, medical and financial consequences for patients and their relatives. The proposed project aims to leverage the latest advances on behavioral science and digital tools to create a platform that supports the implementation of the newly FDA-approved Oral Immunotherapy (OIT) treatments. OIT is a proactive approach that, contrary to other reactive treatments, achieves better patient outcomes. The proposed project will increase scientific understanding about FA through data collection. This Small Business Innovation Research (SBIR) Phase I project seeks to help FA patients and clinicians in the implementation of OIT treatments. OIT has enormous potential to minimize the severity of an FA reaction before it happens, even eliminating the eventual health risks and inconvenient experiences compared to traditional treatments. Still, the preliminary OIT experiences have shown limitations due to needs for customization for each patient and data flow between patients and doctors. The main objective of this research is to develop and validate a digital platform that leverages behavioral science approaches and Machine Learning (ML) to facilitate adherence to OIT treatments, dosing management, treatment personalization, and patient-clinician communication. The specific work will involve: 1) Developing, training and evaluating a series of proprietary ML algorithms capable of providing new insights and predicting events; 2) Developing and testing other software assets required for the completeness of the platform (mobile app, HIPAA-compliant database and API to integrate with 3rd-party systems); and 3) validating the system in real experiences with FA patients. 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.
NSF Program Director: Alastair Monk
The broader impact /commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to help the 32 million people in the US suffering from Food Allergy (FA). FA brings psychological, medical and financial consequences for patients and their relatives. The proposed project aims to leverage the latest advances on behavioral science and digital tools to create a platform that supports the implementation of the newly FDA-approved Oral Immunotherapy (OIT) treatments. OIT is a proactive approach that, contrary to other reactive treatments, achieves better patient outcomes. The proposed project will increase scientific understanding about FA through data collection. This Small Business Innovation Research (SBIR) Phase I project seeks to help FA patients and clinicians in the implementation of OIT treatments. OIT has enormous potential to minimize the severity of an FA reaction before it happens, even eliminating the eventual health risks and inconvenient experiences compared to traditional treatments. Still, the preliminary OIT experiences have shown limitations due to needs for customization for each patient and data flow between patients and doctors. The main objective of this research is to develop and validate a digital platform that leverages behavioral science approaches and Machine Learning (ML) to facilitate adherence to OIT treatments, dosing management, treatment personalization, and patient-clinician communication. The specific work will involve: 1) Developing, training and evaluating a series of proprietary ML algorithms capable of providing new insights and predicting events; 2) Developing and testing other software assets required for the completeness of the platform (mobile app, HIPAA-compliant database and API to integrate with 3rd-party systems); and 3) validating the system in real experiences with FA patients. 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.
NSF Program Director: Alastair Monk
| Status | Closed |
|---|---|
| Effective start/end date | 07/01/21 → 06/30/22 |
Funding
- SBIR Phase I: $255,331.00
Active Fiscal Year
- FY2022
Start Fiscal Year
- FY2021
TIP Programs
- SBIR Phase I
Small Business
- Yes
Key Technology Areas
- Artificial Intelligence
- (confidence score: 95%)
- Data and Cybersecurity
- (confidence score: 89%)
Technology Foci
- Data and Cybersecurity (Broad)
- (confidence score: 100%)
- Artificial Intelligence (Broad)
- (confidence score: 100%)
Congressional District at Award
- District n. 04 of Michigan
Current Congressional District
- District n. 13 of Michigan
United States
- Michigan
Core Based Statistical Area (CBSA)
- Detroit-Warren-Dearborn, MI
County
- County: Wayne, MI
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