Pain Point: This Small Business Innovation Research Phase I project proposes to develop an unprecedented, all-in-one handheld device that integrates food processing, assay chemistry and data interpretation, thereby allowing consumers to easily test their food for peanut and, in the future, other food allergens. Food allergies are a growing food safety and public health concern in the United States (Gupta, R. JAMA Pediatrics, 2013; Liu, AH. J Allergy Clin Immunol, 2010), affecting 6-8% of the children under 4 and 3.7% of adults (Report of the NIH Expert Panel on Food Allergy Research, 2006). Peanut allergy is the most common cause of food allergy- related fatalities in the US (Bock, S.A. J Allergy Clin Immunol, 2007). Among children, peanut is the most prevalent dietary allergy, accounting for 25% of all food allergies. A strict, and life-long peanut-free diet is the only currnt treatment for these patients, but it can be difficult to adhere to because of (a) cross-contamination during food manufacturing and preparation processes and (b) inadequate labeling and testing mechanisms (Remington, B.C. Food Chem Toxicol, 2013). Traditional peanut tests are (1) complicated - most kits require 7+ steps and certain steps involve equipment that is not readily available to the user, such as a scale or grinding device; (2) expensive - costing more than $14 per test; and (3) time consuming - taking longer than 18 min per test. Fundamentally, there does not exist a consumer-oriented product that peanut-sensitive individuals can use to proactively ensure the safety of their food. Technological Innovation: 6SensorLabs is building the first and only rapid and user-friendly solution that enables consumers to test their food for dietary allergens. The all-in-one, handheld device, NimaTM, internally grinds the food, extracts allergen proteins (specifically peanut protein under this proposal) with our proprietary extraction solution, performs the immunoassay and interprets the result, all within 2 minutes. Performing all of these operations internally significantly simplifie the test, minimizes opportunities for user error and variation, and builds confidence in the test result. Further, users will have the option to automatically upload test results via Bluetooth to a mobile app that 6SensorLabs is building. Results will be collected by both consumers and the 6SensorLabs team and automatically entered into a database.
We aim to build the largest living allergen (and gluten) test result database in the US, which will serve as a resource to the community living with food allergies, so that consumers can make smarter decisions about where and what to eat. Broader Impacts of the Technology are to provide food sensitive individuals, their parents or other caregivers, health care providers, and food manufacturers with an easy means of testing foods, ensuring food safety and improving health. While our first two products will be focused on gluten and peanut detection, we expect to expand this technology platform to the detection of other common food allergens or irritants, including tree nuts, dairy products, eggs and soy, among others, in the near future.

Public Health Relevance

The objective of this project is to develop and commercialize an economical, accurate, fast, and portable device for peanut allergen detection in foods, which can be readily used by consumers on a regular basis. It will provide peanut allergy sufferers, parents of children with food allergies, health care providers, food manufacturers and restaurants with a means of testing foods to better ensure safety, thereby improving consumer health and quality of life, as well as reducing long-term medical costs. Ultimately we plan to extend this platform to the detection of all major food allergens.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Small Business Innovation Research Grants (SBIR) - Phase I (R43)
Project #
1R43AI124907-01
Application #
9139247
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Minnicozzi, Michael
Project Start
2016-02-01
Project End
2016-07-31
Budget Start
2016-02-01
Budget End
2016-07-31
Support Year
1
Fiscal Year
2016
Total Cost
Indirect Cost
Name
Nima Labs, Inc.
Department
Type
DUNS #
079298970
City
San Francisco
State
CA
Country
United States
Zip Code
94110