This is part of a series of blog posts on decisions we’ve made in the course of business, to provide some insight into our business and product development process. Posts are not chronological. This post examines decisions around going with chemistry-based gluten detection.

As previously noted, Shireen came up with her one decision, what to build. She had to now figure out the right way to solve this problem. Partnering with people she met through connections at MIT, she realized there were a couple different ways to attack this problem. In an ideal world, you’d wave your hand over the food and just know via some sort of magic implant or look upon the food with your laser-enhanced eye to check it out. However, as with all innovation, it is a matter of taking into account current and emerging technologies and bending those to bear on the problem at hand.

Several methods were examined and discarded. Among these is spectroscopy, the method employed by both Scio and TellSpec. While these devices are very cool and provide a needed service, they wouldn’t suffice for people who needed to know very precisely what was happening in their food with allergens. Spectroscopy allows for assessment at the part per thousand level of detection resulting in data around things like carbohydrate or fiber levels. Allergens are a little trickier – you need part per million detection. The required level for an item to be considered gluten-free in the US is 20 parts per million. That’s wee. That’s a 200th of a teaspoon. Something stronger would be needed.

As Shireen and her nascent team began explorations, they realized a chemistry-based solution would be needed. Our product would have to be able to detect key proteins in the food that caused immune and allergic responses. After 6 months of market research, it was clear that any method of protein detection in food had to be fast, portable, reliable and affordable for consumers to use consistently.

To focus on speed, portability, reliability and affordability, the team saw an opportunity to innovate on both the chemistry reaction and the sample preparation to detect proteins in food. Other considerations in the decision were time to market and capital expenses for R&D. Recognizing a timely market opportunity for gluten detection in food, the team focused on developing a rapid gluten sensor as the first product, with the aims of developing other allergen detection products to follow gluten.

In about 6 months of time, the team was able to develop a sensing technology that was 10X faster than existing methods to detect gluten in foods. The technology is transferrable to other proteins. Peanuts and dairy are next!