A Winning Formula for Building Regional Innovation Capacity: Skills, Research and Collaboration
Organized by: Colleges and Institutes Canada and National Alliance of Provincial Health Research Organizations
Speakers: Pamela Gray, Vice President of Project Development, BioTalent Canada; Diane Burt, Associate Vice President, Research and Program Innovation, New Brunswick Community College; Kevin Holmes, Managing Director, Social Innovation Lab, Algonquin College; Christina Weise, Chief Executive Officer, Research Manitoba
Moderator: Jeffrey Crelinsten, CEO, Research Money
Innovation is not a synonym for research. Innovation is about creating value for someone, making someone’s life better.
A successful research-industry collaboration is the Prairie Research Kitchen in Manitoba. It brings researchers at Red River College together with industry and farmers to help local companies innovate. (e.g., development of a gluten-free perogy provided a local company with local pea protein products.)
It can be difficult for students to address pressing industry or societal challenges as projects often have to align with school semesters.
Labour market research can provide insight into the job-ready talent industry needs and where skills gaps are. (e.g., BioTalent Canada’s wage-subsidy programs provide funds to onboard and train new talent, providing an incentive to hire people they may not otherwise consider.)
Among the challenges: how to honour and credit knowledge-keeping in indigenous communities, how to bring urban innovations to rural areas, and how to ensure each sector has training opportunities to understand how other groups work and what their needs are.
Adopt best practices that spur innovation and build regional capacity, such as:
Integrate applied research into the education curriculum, including partnering within the community or with industry. (e.g., New Brunswick Community College students developed a food product from the waste materials of a lobster processing company.)
Value student’s skills and perspectives to get them excited about innovative projects. (e.g., at Algonquin College’s Social Innovation Lab, students decide which projects they will work on, and connect with community organizations they believe they can help.)
Use policy and funding requirements to encourage groups with different skillsets to collaborate.
Funding application processes can encourage more inclusive collaborations that are open to new approaches (e.g., social innovation), rather than being tailored only to academia or industry.
Organized by: Christina Stachulak and Nicole Arbour, National Research Council Canada
Speakers: Christian Sarra-Bournet, Executive Director, Institute Quantique, Université de Sherbrooke; Aimee Gunther, Policy Officer, Defence Research and Development Canada; Arman Zaribafiyan, Head of Quantum Computing, 1QBit; David Cory, Professor & Canada Excellence Research Chair Laureate, Quantum Information Processing, Institute for Quantum Computing, University of Waterloo; Gail Murphy, Vice-President, Research and Innovation, University of British-Columbia
Moderator: Geneviève Tanguay, VP-Emerging Technologies, National Research Council of Canada
Four decades of investment in quantum computing has put Canada at the global forefront of this nascent industry (e.g., ranks high in number of scientific publications, startups, patents and funding by government and industry).
Canada’s fundamentals in quantum are strong but industry take up has been slow. Government can play a critical role as an early adopter of quantum.
Canada currently lags many countries in developing a national quantum strategy.
A proposal for a national strategy is under development. The strategy would allow Canada to:
Consolidate an active ecosystem composed of academic institutions, industry and government laboratories;
provide support for university-based quantum research, focusing primarily on medium- to large-scale projects;
Take a more coordinated, collaborative and multidisciplinary approach to translating research into tangible impacts that can help companies scale;
Address a critical quantum skills shortage in Canada; and
Share best practices and other proven ideas (e.g., mentoring programs).
Other disciplines (e.g., engineering, materials science) need to be aware of how quantum computing can offer solutions in diverse sectors.
The public may have a general awareness of quantum but some may fear its potential negative consequences. The Department of National Defence’s quantum strategy attempts to address this by communicating the positive impacts quantum can have (e.g., sensors that keep Canadians safe).
Promote Canada’s leadership in quantum: “If you think quantum, think Canada”.
Continue to support quantum technologies throughout the innovation continuum, from fundamental research through to industry adoption and scale up.
To effectively engage policymakers on quantum, focus on its potential impact (i.e., According to a study commissioned by the National Research Council, Canada’s quantum technology industry is forecast to grow to $8.2 billion by 2030, employing 16,000 people)
Better coordination is needed among existing funding programs to accelerate advances in, and adoption of, quantum technologies.
Connect with early adopters in diverse industry sectors by focusing on their problem, not the technology.
Make students aware of job opportunities in quantum. For example, the Q2 program at the University of Sherbrooke’s Institut Quantique is a student-driven initiative that supports entrepreneurship and linkages with potential employers.
Create a platform that can showcase the strength of Canada’s quantum sector to multinationals and the world.
Supports for Women Entrepreneurs: Discussion on Existing Knowledge, Research and Innovative Methods to Dismantle Barriers
Organized by: Dr. Wendy Cukier, Ryerson Diversity Institute
Speakers: Mariam Zohouri, Invest Ottawa; Wendy Cukier, Associate Professor, Director of the Diversity Institute, Ryerson University; Laura McGee, Founder & CEO, Diversio; Astrid Pregel, President, Feminomics Inc.
The current definition of entrepreneurship is narrow and doesn’t reflect the reality that entrepreneurship can come in many different forms (e.g. for-profit business as well not-for-profits, social enterprises and social activism).
One of the biggest barriers for women is access to capital. There is a huge gap between the venture capital financing obtained by women and the numbers of start-ups and businesses women create.
Without targets and tracking we won’t see an increase in women entrepreneurs.
It’s good practice to hire and then promote women and others from equity-seeking groups to show you have confidence in their ability to contribute.
There are still “invisible barriers” women grapple with when starting out. These include “exclusive networks” (golfing), “boys clubs,” the cultural capital and unspoken elements that continue to keep women from succeeding as entrepreneurs.
Work on creating a new vision and definition of what an entrepreneur in Canada looks like.
To achieve Canada’s goal of doubling the number of women entrepreneurs by 2020, Canada’s largest banks could set targets around the flow of capital to women relative to men.
We can learn from female-powered organizations like SheEO, which act on the concept of “radical generosity” rather than “radical profits”.
Collaborate with the people in power to understand how you can help one another (e.g., mentorships).
Organizations vying for the same government grants need put competition aside and share information, resources and networks to achieve their goals.
Champions and mentors need to support women and people from diverse groups through the entire journey, not only at the beginning.
Bridging the Gap: Timely Patient Access to Innovative Medicines in the Rare Disease and Disorder Space
Rare diseases have a significant impact on individuals, their families and society, yet treatments are only
available for approximately 200 rare diseases. The unmet need in rare diseases is a pressing concern that must be addressed. The lack of a Canadian Rare Disease Framework means drugs for rare diseases are subject to the same review, evaluation framework and evidence requirements as other drugs. Evaluating these drugs with the current review process and recommendation framework limits decision making.
This panel explored how novel mechanisms and innovative constructs, effectively applied in other
markets, may enable Canadian regulators and health technology assessment bodies to bridge the gap;
overcoming systemic barriers and lengthy delays in patients accessing life altering drugs for rare disease.
Organized by: Hoffmann-La Roche Ltd.
Speakers: Tania Stafinski , Co-Founder and Director, Health Technology and Policy Unit in the School of Public Health at the University of Alberta; Adrian Thorogood, Lawyer and Academic Associate, Centre of Genomics and Policy (CGP), McGill University; Durhane Wong-Rieger, President & CEO, Canadian Organization for Rare Disorders, Judith Glennie, President, J.L. Glennie Consulting Inc.
Moderator: Bill Dempster, CEO, 3Sixty Public Affairs
The current process in Canada for getting therapies to rare disease and disorder patients is too lengthy.
Only 30% of patients who need access to a rare disease drug or therapy can actually do so.
Patients play an integral role through the entire life cycle of a therapy. Engaging patients early and often improves the quality of research and ensures drugs are delivering value to patients.
Confidentiality is an issue for patients with rare diseases. Genomics and other data can make rare disease and disorder patients more identifiable, even when data are anonymized.
Our limited understanding of rare diseases makes it more challenging for health technology assessment agencies to evaluate clinical data to determine if a potential treatment is cost-effective.
Genome Canada’s proposal to establish a Canada-wide whole genome sequencing program for rare disease patients could improve diagnostic rates.
Quebec revised its review processes in 2018, to align with Quebec’s renewed Strategie Quebecoise des Science de la Vie, with particular emphasis on DRDs. The revision recognized the significant challenge in generating data to demonstrate clinical value of DRDs.
The Canadian payer determines whether patients get access to the products, so demonstrating a drug’s value to them is critical. In the rare disease space, value beyond the pill in the rare disease space needs to be redefined. Most rare diseases are genetic in nature; if we solve the genetic challenges we will find solutions for some of the more common ones.
The lack of a Canadian Rare Disease Framework subjects drugs for rare diseases to the same review and evaluation framework and evidence requirements as other drugs, where submissions tend to be more complete, to demonstrate clinical benefit and cost effectiveness of that drug. Subjecting DRDs to the same review process and recommendation framework limits decision making, as the process is not designed with the consideration of data limitations associated with clinical trials.
We cannot study these conditions without collaborating internationally, including sharing common infrastructure to support clinical trials, surveillance and learning about early access mechanism, such as managed access agreements, that other countries have implemented.
Rare diseases disproportionately affect minors. As such, children should be engaged by their physicians, their parents and researchers in decision making.
There is an opportunity to implement a Provincial/Territorial framework that would compel agencies to articulate how they will contribute to the process and what changes they will adopt to move this process forward.
The provinces and territories can learn from countries like France and Colombia, which created processes to increase efficacy in getting treatments to patients with rare diseases and disorders. Europe has implemented e-consent, which ensures patient medication information is regularly updated online.
Open Science is transforming the research landscape
Organizer: Damien Chalaud, Montreal Neurological Institute and Hospital Speakers: Inez Jabalpurwala, President and Chief Executive Officer, Brain Canada Foundation; Viviane Poupon, Director, Scientific Development and Partnerships, Neuro – the Montreal Neurological Institute and Hospital, McGill University; Aled Edwards, Chief Executive Officer, Structural Genomics Consortium; Alan Bernstein, President and Chief Executive Officer, CIFAR
Moderator: André Picard, Health Columnist, The Globe and Mail
A movement to make research literature open and accessible to the widest possible audience is now expanding to do the same for the data and materials that sustain research enterprises.
Medical researchers in stalled fields, where little headway has been made on disease treatment for decades, could begin to see progress if data and materials were freely available and shared by all investigators.
Although universities have long wanted to transform their research outputs into revenue-generating commodities, they have generally been unable to obtain commercial value from their inventions.
Individual governments continue to fund science, which is ostensibly an internationally collaborative undertaking, but these nations invariably remain eager to see the benefits of such work accrue to themselves.
Open science in health research creates efficiencies, improves quality of data, speeds up scientific discovery, and enables collaboration across borders and disciplines.
A capitalist research model based on using science to turn a profit (i.e., the pharmaceutical sector) should not be demonized as these companies are performing their accepted role in society, which is to bring economic benefits. However, in drug discovery, economic gain comes directly from high drug prices. These conflicts can be resolved using an open platform based on shared interests, so that the two systems can coexist to their mutual advantage.
Industry and academia should pool their expertise and resources on tough problems with broad social or economic effects, such as understanding and treating Alzheimer’s disease.
Open science should be embraced to support and encourage an emerging generation of researchers who have become disillusioned with a traditional peer-review model of publishing that has attended primarily to its own interests.
Major research partners can be enticed to take part in an open science platform if that is where the best young talent is working.
Canada needs to be ambitious and develop its own models of innovation.
Decision-makers need to construct policy to support the adoption and implementation of Open Science.
Examining the Role of Data Trusts in Smart Cities Governance
Organized by: Monique Crichlow, Compute Ontario and Dr. David Castle, School of Public Administration & Gustavson School of Business, University of Victoria
Speakers: Monique Crichlow, Director, Strategy & Policy Development, Compute Ontario; Karen Hand, Director of Research Data Strategy, Food for Thought, Agriculture and Agri-Food Canada; Teresa Scassa, Canada Research Chair in Information Law and Policy, University of Ottawa; Ryan Oliver, Executive Director, Pinnguaq Association; Angela Orasch, PhD Candidate, McMaster University
Moderator: David Castle, Professor, School of Public Administration and Gustavson School of Business, University of Victoria
Studies show that citizens worry how their data will be used by smart cities in certain circumstances (e.g., targeted advertising, policing, selling data to private corporations) but are more open to it being used for practical purposes like traffic, transit and city planning.
Citizens are more willing to share their data when they can see the direct applications and improvement in their own lives and when they have a clear understanding of how that data are collected, who is using it and for what purposes, and feel confident that their data will be secure and their privacy protected.
There are other models around the world (e.g., Barcelona) we can look to as examples for citizen-focused approaches to building smart cities.
Engage the community/citizens in every aspect of the process of smart city creation – from initial consultation to the development of any data policy to ongoing feedback and engagement.
When smart cities are being planned, the conversation should start with the needs of the citizens; i.e., what the outcomes of the project will be for them, as opposed to what technology could be involved or how participating companies may benefit.
Data trusts are one mechanism that can be used to create frameworks for data governance for data sharing, but they are not the only option;. More research is needed to identify other models for creating dynamic and complex data governance systems and/or frameworks.
These systems must be transparent and trustworthy, incorporate community engagement, and be agile/responsive enough to adapt to the varied and contradictory nature of what constitutes public interest, as well as the rapidly changing nature of our data environment.
The Canadian government should review and update the existing legal infrastructure to ensure it can properly support the development of data governance frameworks (e.g., creation of enforcement mechanisms for misuse of data, data protection laws that allow for sharing with governance bodies, etc.).
Whose Facts Actually Matter? How to Truly Embrace Inclusiveness in Science, Innovation and Policy
Organized by: Dr. Marisa Beck, Institute for Science, Society and Policy, University of Ottawa
Speakers: Brenda Kenny, Board Chair, Alberta Innovates; Jeff Kinder, Executive Director, Science and Innovation, Institute on Governance; Angel Ransom, Director of Operations, The First Nations Major Projects Coalition
Moderator: Monica Gattinger, Full Professor, School of Political Studies, Director, Institute for Science, Society and Policy, University of Ottawa
Wisdom is not created by data; it is a human process. Machine learning and big data allow us to operationalize wisdom-seeking.
Science does not and never has spoken with one voice, and therefore the evidence doesn’t always point in one direction. Ultimately it is up to decision makers (not scientists) to make the decisions.
The role of chief scientist is vital as they bring disparate view points from the science world together, and package them in a way that allows decision makers to grapple with inconsistencies, draw conclusions and make informed choices.
More non-traditional models for science advice are needed for policy and science to interact in a non-binary way (i.e., for deliberation and inquiry to overlap), and to allow for additional voices (i.e., society) to be included in the conversation.
Governmental decision-making should be properly informed by community needs and Indigenous worldviews (not just token acknowledgements). Community-built tools can be effective in enabling this process (e.g., the First Nation Major Projects Coalition’s Major Projects Assessment Standard for environmental assessments).
We need more tools – like the Major Project Assessment Standard – developed by Indigenous peoples for Indigenous peoples, and these tools need to be properly integrated into governmental and industry processes.
The government and other agencies need to create more Indigenous-led committees that have the power to review and directly inform policies and regulations (e.g., the Indigenous Implementation Committee).
Policymakers and researchers need to recognize that more data or clearer data will not create knowledge or understanding – they need to look at how that evidence has been built and what values are embedded in it.
Governments and researchers need to find consensus-oriented approaches to policymaking and research, challenge their own assumptions in an ongoing way, engage multiple stakeholder groups, and work to build trust in the overall system (as opposed to just on singular issues).
Work at the interface between society, science and policy can be enabled in a number of ways, including science-policy hack-a-thons, open science, young academies, innovation challenge prizes, citizen scientists, science cafes, science advice crowdsourcing, open foresight and participatory technology assessments.
Organized by: Christina Stachulak and Nicole Arbour, National Research Council Canada
Speakers: Sebastian Hadjiantoniou, Co-Founder and CEO, Incuvers; Ted Hewitt, President, Social Science and Humanities Research Council of Canada, and Chair of the Canada Research Coordinating Committee; Miroslava Cuperlovic-Culf, Senior Research Officer and Team Leader, National Research Council Canada; Rab (Robin) Scott, Professor of Industrial Digitalisation; Head of Digital at the AMRC, University of Sheffield’s Advanced Manufacturing Research Centre
Moderator: Carolyn Watters, Chief Digital Research Officer, National Research Council Canada
Canada still needs informed policies related to artificial intelligence (AI), though has shown leadership on the issues of ethics, privacy, and the responsible use AI (e.g., The Toronto Declaration related to human rights and machine learning, and the Montréal Declaration for Responsible Development of Artificial Intelligence).
Disadvantages to not having AI policies: lack of industry investment and adoption of AI; a lack of standards for AI; and lack of direction when it comes to having a common AI infrastructure for Canada.
The biggest barriers to industrial adoption of AI are social and societal: lack of time or financial and human resources to experiment with the technology; lack of skills related to technology transfer and implementation; and a lack of understanding among leaders of the potential value of AI.
The next generation of workers do not always see how new technologies like AI can benefit traditional industries like manufacturing – a missed opportunity for rejuvenating an aging workforce.
Sharing large datasets in real time from around the world can create a shared metric for how research is reproduced. Reproducibility is a particular challenge in biology.
Enough data and the right data, as well as the involvement of subject experts, will help to make AI more effective and less bias.
Technology Readiness Levels are going up, while Societal Readiness Levels are going down which hinders technology adoption (i.e., concerns over use of private data).
AI comes with many uncertainties, including how past data will be used in the future.
Adopt regulatory frameworks and policies that support “responsible AI” by focusing on both its social and economic benefits.
Remove barriers that limit deployment and adoption of AI and data analytics. This may include reforms to intellectual property law, privacy laws, data policies and international standards.
Engage in an open and transparent dialogue about the social responsibilities and benefits that come with ceding some privacy to algorithms.
Educate industry leaders, workers and the public about these new technologies. Start in the primary grades.
Ensure companies have opportunities to test and demonstrate new technologies before fully implementing them.
Go big: governments need policies that are more ambitious in advancing AI.
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