Unleashing the Potential: The Transformative Role of Artificial Intelligence in Precision Medicine

Unleashing the Potential: The Transformative Role of Artificial Intelligence in Precision Medicine

By: Shantala Hari Dass

 From left to right: Dr. Naveed Aziz, Fanny Sie, Dr. Devin Singh, Dr. Tracie Risling


The landscape of health care is on the cusp of transformation, and Artificial Intelligence (AI) holds the key to revolutionizing patient outcomes, refining clinical decision-making, and streamlining costs. However, this transformative potential is accompanied by a set of challenges and ethical considerations that demand careful consideration.

CGEn curated an insightful panel discussion on November 13, 2023, at the Canadian Science Policy Centre’s annual conference in Ottawa, titled ‘The Role of Artificial Intelligence in Delivering Precision Medicine of the Future’, moderated by Dr. Naveed Aziz, CEO at CGEn. Renowned panelists—Dr. Devin Singh, Emergency Medicine Physician and Clinical Lead in Artificial Intelligence and Machine Learning at SickKids, Dr. Tracie Risling, Associate Professor in the Faculty of Nursing at The University of Calgary, and Vice-President of the Canadian Nurses Association, and Fanny Sie, Head of AI and Emerging Technology External Collaborations at Roche Global Integrated Informatics—shared profound insights into the opportunities and challenges presented by the integration of AI into precision medicine, with a focus on ethical, regulatory, and societal implications. This report encapsulates key take-aways and poignant quotes from the discussion.

Three Key Takeaways:

1. Innovation in Policy for AI in Precision Medicine:

There is an urgency to innovate policies governing the implementation of AI solutions in precision medicine. This sets the tone for the broader discussion on adapting regulatory frameworks to unlock potential benefits. A unified approach would contribute to mitigating potential risks and fostering a secure pipeline for AI industry development.

“It would be nice for the Federal Government to come up with a broad implementation strategy that can be adjusted and adopted in Provinces and Territories across the country.”– Fanny Sie

“There is an opportunity for Canada to learn from policy models in the US and EU to mitigate potential harms and build a pipeline for the industry that is deeply aligned with citizen privacy.”- Devin Singh

2. Collaborating to Build AI Tools for Precision Medicine:

How well-informed is the general public in Canada about AI and precision medicine? This question is pivotal, considering the collaborative efforts required between patient partners and practitioners in co-designing solutions.  These AI tools should be built in collaboration and cooperation with patients and healthcare professionals such as doctors and nurses. In this process, we must caution against making assumptions based on social determinants of health, stressing that individuals facing challenges like food insecurity or lack of housing can still be valuable contributors to the development and implementation of emerging technologies.

The gaps extend to the workforce as well with the massive gaps in education around ethical AI use. Concerns were raised about creating a workforce ill-equipped to implement AI solutions effectively and equitably, stressing the need for comprehensive education.

“We need a better handoff between academic research outputs and industry to get Canadian-made technology/AI solutions into the Canadian healthcare system”- Fanny Sie

“For an effective implementation of AI in health care, you need practitioners with IA – intelligence amplification. AI won’t replace practitioners, but it will be on the shift with them,” – Tracie Risling

3. Diversity and Sustainability in AI Implementation:

AI is pushing the diversity question to the forefront, necessitating attention in ways that previous technologies did not. However, the lack of reflective data from these diverse communities has hindered the capitalization of this potential. 

Canada has some of the most diverse communities in the world whose expertise and data can be used to build equitable AI tools“- Devin Singh

“If you want scale and sustainability, you need long-term engagement of patients and practitioners, and trust.” – Tracie Risling


The CGEn panel has illuminated the intricate landscape of AI’s role in the future of precision medicine. The discourse navigated through the urgent need for policy innovation, the imperative of closing educational gaps, and the importance of data reciprocity to empower patients. The panelists stressed that diversity is not just a checkbox but a catalyst for developing equitable AI tools. Furthermore, multidisciplinary collaboration and trust emerged as critical elements for scaling AI initiatives in healthcare. As we forge ahead, learning from global policy models and establishing a broad federal implementation strategy could position Canada at the forefront of AI-driven precision medicine. Summarising the need for such discussions, Naveed Aziz highlights,” In the realm of precision medicine, the transformative alliance of AI beckons for a thoughtful discourse—a vital conversation that navigates the potential benefits, ethical considerations, and necessary policies to ensure responsible and impactful integration for the betterment of health care. These cannot be one-off events but instead, ongoing dialogues that inform policy, practice, and implementation at all levels.” The panel discussion at the Canadian Science Policy Centre’s annual conference has not only fostered an essential dialogue but also charted a course for the future of healthcare outcomes for all Canadians.

DNA Day 2023

DNA Day 2023: A Call for Diverse Genomic Datasets – Time for Canada to Step Up

By: Naveed Aziz, CEO, CGEn

Diverse, large-scale health genomic resources are key to realizing the true potential of research, and to fully exploit the power of new health technologies based on artificial intelligence (AI), to improve health for all. The data these resources hold is used to identify and study genetic variations associated with disease, which in turn can enable clinicians to provide personalized care to patients based on their genetic makeup, known as Personalized Medicine.

However, the lack of diversity in population genomic data has been a systemic challenge; the research community must work collaboratively with underserved communities to integrate inclusion and diversity in all aspects of study designs to advance health equity.

Until recently, genomic datasets have been largely limited to individuals of European descent, leaving out other ancestries and populations. This lack of diversity can have serious implications for downstream health research and care. For example, treatments and therapies developed for one population may not be as effective across all populations, while groups underrepresented in the data are potentially missing out on tailored care. All of this compounds established and existing socially determined health care disparities.

In Canada, researchers currently lack access to a large-scale human genomic resource that is fully representative of our population. While Canadian investigators can access data from the UK Biobank, 94% of its participants self-identify as White British or other White background. The United States’ AllofUs initiative data is more diverse, but it is currently only available to US-based researchers.

Canada is a country of immense diversity, composed of people from a variety of backgrounds, including Indigenous peoples, immigrants, and refugees. In fact, the 2021 Census reported more than 450 ethnic and cultural origins, 200 places of birth, 100 religions and 450 languages. The ability to research Canadian population-level data would provide a unique opportunity to study the effects of variations in genetic backgrounds on research outcomes and provide insights into the disparities arising from diverse cultural and social contexts.

Recently, CGEn’s HostSeq Initiative, funded through Genome Canada’s CanCOGeN network, built a national databank that includes the genomes of over 10,000 Canadian residents impacted by COVID-19 along with in-depth clinical data. HostSeq demonstrated that Canada is capable of generating human genomic data at-scale and produced a blueprint for genomic health data sharing, analysis and access. 

Through community partnerships and inclusion of diverse groups within study teams, Canadian researchers have begun to make in-roads with previously underrepresented populations to engage in genomics and other research. These partnerships must be built upon when considering a Canadian genomic data generation project at a population scale. The AllofUs initiative, as an example, has prioritized diversity and inclusion with dedicated participant engagement teams working within communities to enrol participants from previously underrepresented groups.

We now have the tools to organize and mine genomic data at scale. AI-based tools are being developed and used across sectors – including health care. In the context of large-scale genomic and health data, AI can help maximize its use and impact by providing insights that would otherwise be difficult to uncover. For example, predictive models can be developed for the identification of individuals at risk for certain diseases or conditions, or to inform personalized treatments based on an individual’s genetic profile, including identifying new therapeutic targets and drug candidates.

Canada must ensure it has access to the necessary data to support AI research and maintain its competitive edge in this area, as the accuracy of AI models is dependent on the data used to train them and in order to produce AI-based genomics tools that will be effective across a population, large-scale, high-quality and diverse data resources are needed. At the same time, even the best AI models can be difficult to interpret and explain, and further research into the ethical and legal implications of using AI in genomics research is greatly needed to ensure our health care systems are equipped to properly and equitably implement them.

The future of genomics in personalized medicine is bright and full of possibilities for Canada. Genomic testing has already revolutionized the diagnosis and treatment of many diseases, and it will become even more valuable in health care, if supported by research based on large-scale diverse data and other technology developments. The resulting more precise, targeted, and effective treatments provided to patients, will lead to better outcomes and health care system efficiencies and savings.

In the last 5 years, the Federal government has invested in CGEn, building and supporting the large-scale infrastructure required to produce health data at scale. However, Canada is lagging behind other countries in capturing its genomic diversity due to a lack of funding and resources dedicated to the collection and analysis of genomic health data at a population-scale. We must build a foundation of diverse and equitable datasets and research that is inclusive and representative of the diversity within the Canadian population. I urge all of us to take action now to prioritize the ethical, legal, and social implications of genomics in health care and to work to ensure equitable access to personalized medicine for all patients.

Finally, we must collaborate across different fields and sectors to bring together the expertise and resources needed to advance personalized medicine in Canada. This includes healthcare providers, researchers, policymakers, industry leaders, patient advocates, representatives from equity-deserving groups and other stakeholders. By working together, we can unlock the full potential of genomics to improve health care and provide better outcomes for patients. On DNA Day, let us take this call to action to help create a future where personalized medicine is expected, and every Canadian receives the best possible care based on their unique genetic makeup.