Nov 8, 2022

Member Spotlight: Dr. Dave Anderson

Dr. David Andersion-UofC

University of Calgary, Cumming School of Medicine
• Senior Instructor: Department of Biochemistry & Molecular Biology
• Alberta Children's Hospital Research Institute
• PubMed link

What inspired you to originally pursue bioinformatics?
My path to working in bioinformatics was a bit circuitous. I started with an undergraduate degree from the Arts and Science program at McMaster University, where I focused on physics and astronomy. (My first publication from my undergraduate thesis was in astronomy). I pivoted to the life sciences as a graduate student and got really interested in developing analysis tools for large genetic libraries. Since then, I’ve found a rewarding place in the health science research ecosystem by being a computational (“dry”) scientist.
How did you become interested in AI and precision medicine?
I was aware of how AI tools could be used in a research context for a long time, but I only recently got involved in precision medicine applications.
     My interest emerged from different projects that are, I think, emblematic of many of the kinds of applications currently being developed: The first involves identifying molecular biomarkers (e.g. genetic, transcriptomic) that could be used prognostically to identify future health conditions. The second uses radiology imaging to improve diagnosis and treatment recommendations.
     Both projects are quite different in terms of the datasets used and the ultimate goals but are united by leveraging the power of AI models and the scale of health-related data that we now have to improve outcomes.

What excites you the most about the possibilities of AI in healthcare?
Ultimately, the most exciting thing is the prospect of improving lives. We are now in an era where we can generate more data about individuals than we used to be able to generate about entire populations. This opens up so many opportunities to use AI tools in their most effective way to target interventions and approaches.
     I am also particularly excited about using AI for prevention. In other words, to identify cases where interventions can happen that will prevent the development of disease, saving people from having to even enter the health care system.
What outcomes do you hope your work will eventually lead to?
I think the most important work I am involved in right now is developing new educational programs and courses that reflect the transition of our health system to this “big data” era.
     In particular, I’m very excited to see the outcome of our precision health graduate program. I am hopeful about the impact our students will have as they move forward in their careers and take on these great opportunities (and challenges).
What projects are you working on right now that you’re really excited about?
One initiative I’m involved in right now is engaging with patient advocates around the development, delivery, and governance of our education programs in medicine.
     We have been developing a partnership with the Imagine Citizens Network, a phenomenal group of community volunteers, to model the “coproduction of care” in our education programs.

What’s your best advice for students following in your footsteps?
AI applications are as varied as they are powerful. Because of that, the number one piece of advice I offer students interested in this area is to identify the problem where you are most passionate about having an impact, and then be creative about all the ways you can apply these powerful tools. It’s an amazing (and lucky!) time to be studying in this field!