The MIT Abdul Latif Jameel Clinic for Machine Learning in Health (J-Clinic)

The MIT Abdul Latif Jameel Clinic for Machine Learning in Health (J-Clinic) was co-founded by MIT and Community Jameel in 2018 with the aim to revolutionise the prevention, detection, and treatment of disease.

The MIT Abdul Latif Jameel Clinic for Machine Learning in Health (J-Clinic) was co-founded by MIT and Community Jameel in 2018 with the aim to revolutionise the prevention, detection, and treatment of disease. J- Clinic concentrates on creating and commercialising high-precision, affordable, and scalable machine learning technologies in areas of health care ranging from diagnostics to pharmaceuticals, with three main areas of focus:

  • Preventative medicine methods and technologies with the potential to change the course of non-infectious disease by stopping it in its tracks.

  • Cost-effective diagnostic tests that may be able to both detect and alleviate health problems.

  • Drug discovery and development to enable faster and cheaper discovery, development, and manufacture of new pharmaceuticals, particularly those targeted for individually customised therapies.

J-Clinic’s work focuses on a wide range of conditions that affect millions, from cancer and neurodegenerative disorders such as Alzheimer’s and Parkinson’s to chronic illnesses such as diabetes, kidney disease, and asthma. J-Clinic’s holistic approach utilise MIT’s strong expertise in cellular and medical biology, computer science, engineering, and the social sciences, amongst other areas.

J-Clinic leverages MIT’s strong relationship with industry, Boston-area and international hospitals to test, integrate, and deploy new technologies. It also seeks to advance patentable research that could commercialise and spin-out through licensing to startups and pharmaceutical companies putting these advances into real-life practice.

As part of its work, J-Clinic supports research projects, education, workshops, and other activities, such as the MIT AI Powered Drug Discovery and Manufacturing conference, at the intersection of machine learning and biology.