Temerty Centre Speaker Series: Dr. Stephen Friend
DATE: February 22, 2022 (Tuesday)
TIME: 12pm to 1pm
METHOD: Zoom webinar
NOTE: This event is CPD accredited for physicians
Register
https://us06web.zoom.us/webinar/register/WN_ScDtyxQ7RR6jaQXyyesJ2w
Talk
How digital devices might allow us to follow symptom transitions and the effects of the fabric of life on chronic conditions.
Each day signals continuously emanate from us and also signals arise by what we do in the physical and virtual world that go discarded while we puzzle how to better follow symptoms and behaviours that impact our wellness and journeys between health and disease. We have been starting a series of feasibility studies to ask how could these signals be retrieved and more importantly how could this knowledge be returned to individuals to empower how they wished to navigate their health.
Biography
Dr. Friend is an authority in the fields of genetic resilience, cancer biology, and digital health. At Dana Farber and MIT his team cloned the first human cancer susceptibility gene. While on the faculty at Harvard, he was jointly recruited with Lee Hartwell to co-found "The Seattle Project” at the Hutch and then co-founded and led Rosetta Impharmatics where they developed the RNA expression approaches to assess the aggressiveness of breast cancers. Merck acquired Rosetta and as SVP for Oncology he rebuilt the cancer franchise using molecular profiling techniques, which would later show value in assessing the sensitivity of tumors to Keytruda. After working at Apple from 2014-2017 on digital health, he is now a co-founder and President of 4YouandMe, the Founder and Chairman of Sage Bionetworks, and based at Oxford University as a Visiting Professor of Connected Medicine. Dr. Friend is both an Ashoka Fellow and AAAS Fellow.
Learning Objectives
1. Understand what is "multi-modal data"
2. Understand the risks and benefits of using “ Participant Centered trials"
3. Give examples of how to modify app functionalities during the running of trials based on participant feedback
