Columbia University researchers have developed a personalized algorithm that predicts the impact of particular foods on an individual’s blood sugar levels. The algorithm has been integrated into an app, Glucoracle, that will allow individuals with type 2 diabetes to keep a tighter rein on their glucose levels-the key to preventing or controlling major complications of the disease.
“While we know the general effect of different types of food on blood glucose, the detailed effects can vary widely from one person to another and for the same person over time,” said lead author David Albers, PhD. “Even with expert guidance, it’s difficult for people to understand the true impact of their dietary choices, particularly on a meal-to-meal basis. Our algorithm, integrated into an easy-to-use app, predicts the consequences of eating a specific meal before the food is eaten, allowing individuals to make better nutritional choices during mealtime.”
The algorithm uses a technique called data assimilation, in which a mathematical model of a person’s response to glucose is regularly updated with blood sugar measurements and nutritional information to improve the model’s predictions.
Glucoracle allows the user to upload finger stick blood measurements and a photo of a particular meal to the app, along with a rough estimate of the nutritional content of the meal. This estimate provides the user with an immediate prediction of post-meal blood sugar levels. The estimate and forecast are then adjusted for accuracy. The app begins generating predictions after it has been used for a week.
The researchers are preparing for a larger clinical trial and estimate that the app could be ready for widespread use within two years.
This article was adapted from information provided by Columbia University Medical Center.
