Precision or personalised medicine is an emerging approach for disease treatment and prevention that considers individual variability in general environments and lifestyle.

This two-part blog series will explore the takeaways from this workshop; starting with the vision, research, informatics enablers and public policy needed to enable precision medicine, and followed by an exploration of the challenges and opportunities for precision medicine.

Orion Health CEO, Ian McCrae, opened the workshop by sharing his vision for precision medicine. McCrae predicts a huge explosion of data will take place in the next eight years (50 times what we have now) which will impact the job of clinicians. This explosion will allow them to make care decisions based on data, not intuition or clinical trials. As a result, Health information Exchanges (HIE) and Electronic Health Records (EHR) will need to be expanded to include data sources like social determinants of health and genomic, microbiomic and epigenetic data. McCrae noted that countries with more data in electronic form will lead the global transformation of health and make some major breakthroughs in the next five years – specifically in the U.K., Denmark, Netherlands and New Zealand.

However, Canada won’t be left behind. Presentations by three lead researchers at Dalhousie University underscored the growing importance of genomic research in support of precision medicine: 

Assistant Professor, Dr. Ian Weaver, shared a report on epigenetic research in Canada. The report is a result of research by the Atlantic Pathology Group, which collected data on Atlantic Canadians regarding smoking status, exposure to toxins and arsenic pre-natal, post-natal.  Early life experiences have long term effect on an individual’s health and disease risk into adulthood.  Through this, the group is focused on creating, communicating and translating the latest knowledge on early childhood development to improve the health and well-being of Canadians.

Dr. Rob Beiko shared his findings on a microbiome analysis of frail populations. He described different types of microbiomes and how they are associated with diet, immune development, infectious disease, living conditions, neurological conditions and any association with frailty.  The long-term vision is to provide rapid, personalised assessment of the “microbial health” of older individuals, including risks of antibiotic-resistant infections and opportunities to improve health via probiotics and diet.

Dalhousie’s Dr. Raza Abidi presented research by kNowledge Intensive Computing for Healthcare Enterprise (NICHE) –  a group dedicated to developing health informatics solutions for preventive, predictive and personalised lifetime healthcare interventions. Predictive medicine is a branch of medicine that aims to identify patients at risk of developing a disease, thereby enabling either prevention or early treatment of that disease.  The research’s goal is to protect, promote, and maintain health and wellbeing in order to prevent disease and disability through personalised risk assessment, therapeutic planning, self-management and behaviour modification interventions.

Orion Health’s own CMO and CPO, Dr. Chris Hobson, also shared Orion Health’s perspective. Walking the audience through our seven stage journey to precision medicine, he described the need for acquisition of data through integration engines,  aggregation of data, the analysis of said data through open platforms, access to that data through portals, applications and mobile devices, actioning that data through clinical pathways, referrals, messaging, care coordination, transition of care and finally the adoption of that solution.

But the workshop didn’t end with great presentations, we were also privy to great discussion. The workshop addressed the policy perspectives and barriers that will impact the adoption of precision medicine:

Privacy and security, and the public’s expectation that everything will be private and secure.

  • Finding out what works, then prioritising and improving that data.
  • Using validated tools to get precise data.
  • Incorporating data with other sources, as there is no one number or sole data point that can accurately predict a measure of patient’s health.
  • Using big data to improve policy and population health.
  • Emulating Ontario’s walled garden model where researchers can access the data and leave their results in the ‘walled garden’ so others can benefit from it.
  • Challenge of pulling data from databases – particularly linking primary care into the other aspects of continuity of care.
  • Preparing ourselves for the certification of Machine Learning Algorithms in support of Clinical Decision Support.

This is only a glimpse of the insights shared at the workshop. Subscribe to be notified when part two of this blog is released.