MHSc in Medical Physiology Off to a Remarkable Start
Congrats to the first cohort of the Department's MHSc in Medical Physiology program who graduate November 18th. Our students are now thriving in industry positions, professional, and PhD programs, and are publishing in major journals. Read on for more!
What is the MHSc in Medical Physiology?
This program has been several years in development and seeks to meet the rapidly emerging need for professionals with a deep understanding of human physiology who are also equipped to interpret big data sets and collaborate effectively with teams in the healthcare space.
Over the course of two semesters, students immerse themselves in elective courses to deepen their physiology education, as well as four core courses specially designed for the MHSc program: Big Data and Healthcare, Collaboration and Commercialization, Professional Development, and Clinical Physiology. The students also prepare a publication-quality literature review with the help of a faculty mentor. In concert, this training prepares students for a work placement over the summer term, where they apply their new skills and become workplace ready in a total of just twelve months.
Set Up For Success:
Program Director, Dr. Helen Miliotis spread the word throughout her professional networks about our uniquely skilled cohort and students reached out to organizations of interest as well. Students attained well-matched placements at a wide variety of organizations from Neurofit — a start-up developing virtual reality solutions to brain injury rehabilitation — to labs working on reproductive and mental health, to Future Fertility, a company using artificial intelligence to redefine the fertility space, to name but a few.
Elly Zhou, whose placement was at UHN’s Latner Thoracic Surgery Research Lab, immediately applied skills learned in her Collaboration and Commercialization course in support of her lab’s efforts to bring a new diagnostic test to market. “The class helped in terms of being familiar with all the concepts of the whole commercialization process. It was very easy to follow and help out during my placement. It's like a textbook-in-real-life sort of scenario.”
Skills attained in the Mentored Literature Review component proved readily transferable as well. Bastien Moineau, R&D Lead at the wearable device start-up Myant Inc. who hired two MHSc candidates for summer placements, spoke to the value of the students’ proficiency in this area. “Sara [Bennett] and Katrina [Innanen] could really go deep into the literature even in topics they were not familiar with,” he said. “The fact that they were fresh out of academia and used to reading a lot of papers and extracting information — that was really valuable.
“The work they did helped us both internally and for consumer-facing messaging,” Moineau continued. “They provided advice on how to use data on heart rate and steps, why inactivity is dangerous...they also understood what data is, what an ECG is supposed to look like, so we didn’t have to explain health monitoring 101 to them.”
Innanen agreed. “Being able to practice my presentation skills, such as the business pitch we had to do in the Commercialization course helped me convey information better,” she said. “The Big Data course also definitely proved useful in that I was able to read the codes and understand how we would have to change them for horses,” she said of her work in Myant’s animal division.
The company produces wearable garments for both humans and horses, designed to track key health indicators and report these on a smartphone app. A concerned child of an elderly parent, or a horse owner living far away from their animal, can keep an eye on various metrics and address potential issues in a timely manner. “It was really cool to take my human physiology background and see how that can be related to different areas,” Innanen said. “Sometimes I couldn't make the code changes on my own but I knew enough of what was going on that I could go to the engineers and be like, ‘Can you help me do this?’”
Zhou, too, was able to readily use what she learned in the Big Data course. “I loved it. Especially the machine learning aspect. I was able to apply a lot of those concepts in my current project, because we’re trying to improve AI-based diagnostics in lung transplants. It feels meaningful and we can hopefully help more patients as we develop the algorithm.”