The science behind Nima
Nima’s founding team met at MIT, and the product was built by engineers and doctorates from MIT, Caltech, Stanford and Dartmouth, with experience building consumer products at companies like Nike, Google and Johnson & Johnson, and medical devices at companies like Cepheid and Agamatrix.
Nima was developed by adapting antibody-based chemistry used for protein or allergen detection, designed into a hardware device that is portable and easy to use, and using electronic sensors and proprietary algorithms to detect test results. The primary criteria considered when designing Nima were sensitivity and specificity to gluten, speed, portability and ease of use.
Nima’s scientific advisory board
The Nima experience touches many aspects of life: health, wellness, science, food service, and data. Since its inception, Nima has been supported and guided by professionals and researchers in healthcare, nutrition, and the food service space. Each one of our advisors is a pioneer in their respective space.
Peter HR Green, MD
Phyllis and Ivan Seidenberg Professor of Medicine. Director, Celiac Disease Center at Columbia University.
Jody Puglisi, PhD
Stanford University. Professor of Structural Biology.
Lucille Beseler, MS, RDN, LDN, CDE, FAND
Family Nutrition Center of South Florida.
Benjamin Lebwohl, MD, MS
Director of Clinical Research Celiac Disease Center at Columbia University.
John Garber, MD
Gastroenterology, Mass General.
Thanai Pongdee, MD
Consultant, Division of Allergic Diseases, Mayo Clinic.
Nima’s antibody-based chemistry
An antibody is a large, y-shaped protein that recognizes and binds to a specific target protein. Antibodies are routinely used to detect specific proteins in chemistry lab tests.
The Gluten Antibody
The Nima chemistry team developed a pair of antibodies specifically for the detection of gluten. There are existing gluten antibodies on the market, but none of them met the sensitivity and specificity requirements that we needed for Nima. The Nima 13F6 and 14G11 antibodies bind to a portion of the gluten protein, called the 33-mer fragment of gluten, which is known as the “toxic” portion of the gluten protein that causes an autoimmune response. Nima’s 13F6 and 14G11 antibody system was evaluated and determined to be more sensitive in a standard lab test than one of the well-recognized gold standard antibodies currently used on the market.
Nima’s gluten antibody is currently being used in the Biofront gluten Elisa kit, having been evaluated for excellent performance in sensitivity and specificity in a wide variety of foods.
The Peanut Antibody
The Nima chemistry team developed a pair of antibodies specifically for the detection of peanut. There are existing peanut antibodies on the market, but none of them were sufficient to meet the speed, sensitivity and specificity requirements that we needed for Nima. The Nima 20B10 and 16B1 antibodies bind to a peanut protein called Arah3. Although not the most antigenic, it is abundant in all types of peanut and is more stable under processing conditions such as heat due to roasting.
To read more about how the antibody is used in the Nima Peanut Sensor, please review the peanut manual.
Nima’s test capsule
Each Nima capsule contains a test strip preloaded with our antibodies. If gluten is present in the food being tested, the antibodies will bind to the gluten proteins and present a signal change on the strip that is detected by the Nima electronics and processing algorithm.Liquid extraction buffer
When gluten is present in food, the gluten protein molecules are trapped inside other food molecules surrounding them. In order to detect gluten in food, gluten molecules need to be isolated and extracted from the rest of the food molecules.
The Nima team designed an extraction buffer solution that is capable of breaking apart the bonds between gluten and other food molecules, leaving the gluten itself in a liquid solution, which reacts to the strip.Grinding and mixing mechanism
When testing food for gluten, there are several mechanical steps necessary to deliver a result. Screwing the cap shut begins a grinding process on the food to break the food into small particles to increase the amount of surface area exposed to the buffer solution.
After the food is ground, the final twist of the cap will expose the food to the extraction buffer solution. Nima uses a motor to mix the food and the buffer in the capsule. Once the mixing is complete, the solution passes onto the test strip loaded with antibodies, where the chemical reaction begins.
Nima’s sensor and algorithm
As the test strip develops, an electronic sensor and associated algorithm detect the test result. Reading the result electronically eliminates the need for a trained operator to be evaluating the results (as is required with other lab-format tests) and reduces the likelihood of misinterpreting results (as often happens with at-home pregnancy tests). The algorithm is improved and updated via Bluetooth connection through the Nima mobile app. The algorithm can be updated by downloading the latest firmware updates from the app.
The Nima system has been extensively tested with thousands of tests in our labs, in the field and in third-party labs.
In our own internal testing of hundreds of food tests, Nima demonstrates the following accuracy:
- For foods containing gluten at or above 20 ppm, Nima reported “gluten found” 99 percent of the time.
- For foods containing below 2 ppm, Nima reported “gluten found” 7.8 percent of the time.
We designed Nima to be more sensitive to minimize false smiles (gluten-free when gluten is present at or above 20 ppm). Learn more about our threshold here.
A full report on the efficacy of Nima is pending publication in a peer-reviewed journal, and will be shared with our community when available.
The Nima Research & Development team conducted thousands of tests across numerous foods to confirm the sensitivity of the device. In addition to in house testing, Nima also enlisted the help of several third party labs. The results were as follows:
To access each report or our webinar please provide your email below: