Principal Investigator Dean Eckles
Principal Investigator Evan Ziporyn
Customer Analytics
Endor: Predictive analytics on customer data without data scientists FindOurView: Customer insights with language understanding Paradigm Sift: Applying cultural context to understand customers at scale Cerebri.ai: AI-based next actions to drive customer engagement Assetario:Â Â Personalizes the in-app purchase to drive user happiness and revenue
Customer Engagement & Technology
GoWith: Enhancing the airport passengers' experience every step of the way. Voomer: AI to empower people for video communication ServiceMob: Making customer service access simple with AI Posh: Conversational AI for customer service & helpdesk Silverthread: Improving software health and economics at scale
For a little over a dozen years, our group has been developing, integrating, and testing various bihormonal (insulin and glucagon) bionic pancreas technologies for autonomous regulation of glycemia in people with type 1 diabetes (T1D). The technology has evolved over the years from a crude and clumsy system of interconnected pumps and sensors cobbled together around a laptop computer, to a system that runs on an iPhone, which wireless communicates with two infusion pumps and a sensor, and, finally, to its ultimate embodiment as a dual-chamber infusion pump, a sensor, and mathematical algorithms all housed within a single compact integrated device, which we call the iLet (in homage to the pancreatic islets of Langerhans which contain the alpha and beta cells that secrete glucagon and insulin).
The laptop version of our bionic pancreas was tested first in a diabetic swine model of T1D at Boston University (BU) between 2005 and 2009 and then in inpatient clinical trials with our collaborators at the Massachusetts General Hospital (MGH) between 2008 and 2012 in adults and adolescents with T1D. Between 2013 and 2016 we conducted outpatient clinical trials of the iPhone version of our bionic pancreas together with our clinical collaborators at MGH, Stanford, the University of North Carolina, and the University of Massachusetts. Results of these studies will be presented along with our plans for the final pivotal trials of the iLet and the pathway ahead for regulatory approval.
2016 MIT Digital Health Conference