MIT, Mass General team up on health IT
Data analytics and remote monitoring integral to new partnership
The Massachusetts Institute of Technology has teamed up with the Bay State's largest hospital in a new partnership aimed at addressing three major obstacles in clinical medicine, tapping data analytics and digital health tools.
MIT is joining with Massachusetts General Hospital to further develop disease diagnostics, create new prevention and treatment approaches for autoimmune diseases and fine-tune diagnostics for those with neurodegenerative and psychiatric diseases. Key to this will be data analytics and remote monitoring, officials say.
Both groups have pledged to fund research projects that address these three challenges by up to $3 million over a two-year period.
"MIT and MGH have uniquely synergistic and complementary strengths," said Arup Chakraborty, the Robert T. Haslam professor of chemical engineering, chemistry and biological engineering at MIT, in a press statement.
[See also: MIT center to develop new health technologies]
"Developing the cost-effective diagnostic tools, therapies and vaccines needed to overcome some of the daunting challenges facing human health today can be achieved by bringing approaches from engineering and basic science together with clinical medicine and that a strategic partnership between our institutions could achieve much more toward advancing human health," added Chakraborty, who is also the director of the MIT Institute for Medical Engineering and Science.
The first round of grants, which were announced this past September, are aimed at using digital health tools and analytics to improve diagnosis accuracy and cost-efficiency. The first series of grants were awarded to:
- Michael Cima of MIT and Herbert Lin of MGH: Development of a portable, noninvasive device capable of accurately measuring blood volume using nuclear magnetic resonance.
- Anande Dighe from MGH and Peter Szolovitz of MIT: Use of machine learning to analyze changes in a patient's lab test results over time to facilitate early diagnosis or predict the development of clinical problems.
- Matt Bianchi from MGH and Dina Katabi of MIT: Clinical trial of device using wireless signals to monitor breathing without touching a patient's body for improved diagnosis of sleep apnea.
- MIT's Brian Anthony and MGH's Anthony Samir: Adaptation of an optical system for localizing the position of ultrasound transducers, which compensates for individual operator differences, to the noninvasive monitoring of tissue loss in chronic kidney disease.
- Sangeeta Bhatia of MIT and Raymond Chung, MGH: Evaluation of liver-targeting nanosensors for the noninvasive monitoring of liver damage caused by nonalcoholic fatty liver disease and other disorders.
- Michael Filbin from MGH and Thomas Heldt of MIT: Building an archive of data collected from bedside monitoring and the electronic medical record to develop algorithms predicting the transition from sepsis to septic shock.
