Mass General Brigham’s location in the Massachusetts biotech and academic medical communities creates enhanced collaborations with partners from academia, industry, and venture capital to help stimulate the development of our discoveries into lifesaving therapies for our patients.
The greatest minds at our hospitals have a history of pushing the boundaries of medicine and leading innovative science for over 200 years. We have a legacy of medical achievement, with numerous medical firsts and 13 Nobel Laureates.
Click to view research institutes at Mass General Research Institute
Research at Massachusetts General Hospital suggests a novel strategy for enhancing the efficacy and safety of cell replacement therapy in the nervous system: co-transplantation of dopamine progenitor cells.
Julie K. Silver, MD, a physical medicine and rehabilitation clinician at Spaulding Rehabilitation Hospital, authored or co-authored several papers examining gender, racial, and ethnic diversity in practice guideline development. She argues that expanding diversity is good for physicians and scientists — and for patients.
Brigham scientists developed a method to simultaneously detect more than 2,000 CD1 lipid molecules that are displayed to T cells in the human immune system. This resulted in the first integrated CD1 lipidomic map, guiding the investigation of lipid T cell antigens and cleft blockers in any cellular system or disease.
The effects of blind spots caused by eye disease, injury, or surgery can be difficult to understand and even more difficult to illustrate. New research from Eli Peli, MSc, OD, of Mass Eye and Ear, offers a glimpse of the world as seen by people with blind spots.
Researchers at Brigham and Women’s Hospital have demonstrated that mice with ovarian failure caused by chemotherapy can restore their fertility using induced pluripotent stem cells (iPSCs). Not only were the mice able to make functional eggs from the iPSCs, but those eggs developed into pups that could reproduce.
Researchers at Mass General have developed machine learning algorithms, a form of artificial intelligence, that accurately predict prolonged length of stay after primary total hip arthroplasty.