Research Implementation Challenges

Canada spends $50 billion a year on R&D and commercializes less than 2% of it. Why are we so bad at this? I spent years working with university incubators across University of Waterloo, University of Toronto, York University, and McMaster University. The pattern was always the same: brilliant innovators who couldn't build their products alone, and a VC ecosystem that wouldn't invest in IP-based companies before revenue. The bottleneck isn't invention. We're exceptional at that. It's the Vision-to-Execution Gap. Non-technical founders can't translate their IP into Production-Ready MVPs without burning $400k on scoping fees or getting trapped in vendor lock-in. So the IP either dies in the lab or gets assigned to foreign companies. More than half of the IP we generate here ends up owned elsewhere. We don't have an innovation problem. We have a translation problem.

How does impact-focused funding influence researchers’ knowledge mobilisation activities? This recent study of Canadian researchers funded through the Natural Sciences and Engineering Research Council of Canada provides a sobering answer. Rather than consistently increasing engagement in knowledge mobilisation (KMb), the authors find that more researchers disengaged from KMb after receiving funding than began engaging. In short, impact-oriented funding alone may not reliably translate into sustained impact practice. The study draws on document analysis of publicly available professional webpages, CVs and social media profiles. As the authors acknowledge, this approach may lead to systematic under-reporting of engagement activity. For me some interesting take-home messages: 1. Funding requirements may not be enough: Even where impact expectations are embedded in funding criteria, researchers face structural barriers: limited time, weak institutional support, disciplinary norms, and competing academic incentives. Without an enabling environment, impact activity remains fragile. 2. Disengagement matters as much as engagement: The finding that previously active researchers disengage after securing funding is as important as patterns of uptake. It suggests that impact may still be treated as instrumental, something to demonstrate for funding, rather than as a practice supported across the full research lifecycle. 3. What we measure shapes what we see: While methodologically careful, reliance on document analysis inevitably under-captures informal or confidential forms of engagement and, crucially, it cannot tell us why researchers stop engaging. That last point feels particularly important and I do feel this study would have been strengthened by speaking directly with researchers to understand: ↳ how they are mobilising knowledge in practice ↳ why they disengaged  ↳ what could have supported them to stay engaged For me, the implication is not that impact-focused funding is misguided, but that funders, institutions and impact support need to work in together. Funding can set expectations, but sustained impact requires aligned practical support and space for reflection - especially if we want knowledge mobilisation to be meaningful rather than performative. #KnowledgeMobilisation #ResearchFunding #ImpactEvaluation

We need new research metrics if we are to address disparity. All Canadian research granting councils have made commitments to greater equity and inclusion. https://lnkd.in/gsi4GqfU Through funding programs such as the New Frontiers in Research Fund they have also committed to transformative research. However, the standard metrics used to evaluate research and development outcomes perpetuate disparity, even in the projects whose primary purpose is to promote greater inclusion and transformative change. Research projects are traditionally judged by their impact in numbers. For example, a project to address employment must show how many additional people are hired as a result of the project activities. This encourages projects to avoid people that face the greatest barriers to hiring, and to work with people that are more likely to succeed. With our current metrics, the overall impact of the research investment is that people that face the greatest barriers to inclusion will continue to be excluded. It will be assumed that the problem has been addressed, thereby abandoning people who are struggling the most, creating further divides. Impact metrics in numbers also means that the projects are far less innovative and transformative. Metrics like the number of outputs or solutions produced and implemented encourages researchers to tackle the simple things with the greatest likelihood of success rather than the hard things. It encourages the production of redundant outputs or incremental outputs that already have an established demand, rather than truly transformative outputs. This is further incentivized by tight timelines that don’t provide the time needed to address the more challenging problems. This pattern is reinforced by peer review processes which disadvantage peerless research. It is in tackling the more difficult challenges that true innovation happens. Tackling the most confounding barriers is a means of ultimately achieving benefit for all. Rather than traditional impact metrics, if we are authentically committed to reducing disparity and supporting transformative innovation we should measure: - whether we have reached and made a substantive difference for the diversity of people who face the toughest barriers to inclusion, -  the degree to which we have tackled the more difficult challenges that might take longer and require more effort but yield more transformative results. (While we are at it, to support sustainability, we should also move from dependency on solutionism to capacity building: empowering and equipping the communities that experience the challenges to frame the problems and work together to address them.) VRAIE IDEA, Social Sciences and Humanities Research Council of Canada (SSHRC), Natural Sciences and Engineering Research Council of Canada (NSERC) #InclusiveDesign #Innovation #Transformation #ResearchMetrics

Primary Care Transformation Series Post#13: A Holiday Gift....A report from the Institute of Health Economics For those working on primary care transformation as we close out 2025, Alberta's Institute of Health Economics just released a 177-page rapid review on team-based primary care—synthesizing national and international evidence. Kudos to the authors. Here are five things I took from reading the report. 1. We keep naming the same barriers at three levels. Macro: funding, regulation, workforce. Meso: governance, structure, technology. Micro: communication, roles, trust. Across 35 studies and 35 grey literature sources, the pattern repeats. The evidence isn't the problem. Our inability to work across all three levels simultaneously is. 2. Terminology is a mess—and it matters. Interprofessional. Multidisciplinary. Collaborative. Integrated. The review found these terms used interchangeably with varying definitions across jurisdictions. One researcher's "team-based care" is another's "collaborative practice." This isn't semantic quibbling—it undermines our ability to learn from each other and compare outcomes. 3. Fee-for-service alone doesn't support collaboration. The evidence is now definitive: blended and capitation-based funding models better support teamwork than fee-for-service alone. Yet across Canada, payment reform remains patchy. We know what works. We struggle to implement it. We have no navigation system 4. Patient outcomes improve .. whole system aligns.Evidence of improved chronic disease management, reduced ED visits, and higher patient satisfaction when team-based care is properly resourced. But the phrase "when properly resourced" carries a lot of weight. What does that mean? We lack guidance. 5. Equity requires intention, it is not an accident. The most vulnerable populations—rural, Indigenous, those with complex needs—face the greatest barriers to team-based care. Several promising models exist, but equity must be embedded in design, not added as an afterthought. Equitable access to teambased primary care is the goal to enable upstream care. What strikes me most: we have evidence. We lack coordination across jurisdictions, across organizations, across levels. That's not a research gap. It's a leadership gap. Contrary to the report we do have evidence based frameworks to advance teambased primary care. We have been talking about them in this series. Would love to hear your thoughts... How does this report broaden our collective thinking? Happy reading over the holidays!! Link to full report here and in comments. https://lnkd.in/gXA_ViFC

While some aspects of research funding in Canada are positive, two things that I and many colleagues get super frustrated by is that (1) research funding typically requires industry funding, and (2) there are no avenues for funding academic research projects without some form of stipulation. For the latter, some might point to New Frontiers in Research Foundation - Exploration, but this requires an unconventional collaboration. For example, I had a proposal rejected because a collaboration between a bioinorganic chemist and a chemical engineer was not unconventional enough. Forcing researchers to create "unconventional collaboration" is an idea that makes sense only to non-scientists. Others might point to the NSERC Alliance Society, but this has vague requirements that end users directly benefit. Not sure what to make of this. All of this is in stark contrast to the NSF in the USA, where the NSF has sub-programs dedicated to different fields and open calls for innovative research. You have an awesome idea? Cool. Submit it! Here in Canada, if you have an awesome idea, there's often literally no place that you can just write a proposal and try your luck. All of this incentivizes applied, iterative research that will not place Canada in a leadership role moving forward. Canadian research funding is definitely due for a re-think.

The biggest hurdle to economic benefit from Canadian academic research is the valley of death, the gap that exists between the point at which research grants dry up and private sector funding can take over. In their position as the source of most of the deep tech IP funnel, universities are uniquely positioned to both bridge the valley of death and to derive benefit from doing so. 𝘛𝘩𝘪𝘴 𝘪𝘴 𝘵𝘩𝘦 𝘧𝘪𝘳𝘴𝘵 𝘰𝘧 𝘧𝘰𝘶𝘳 𝘱𝘰𝘴𝘵𝘴 𝘴𝘶𝘮𝘮𝘢𝘳𝘪𝘻𝘪𝘯𝘨 𝘵𝘩𝘦 𝘭𝘢𝘵𝘦𝘴𝘵 𝘪𝘵𝘦𝘳𝘢𝘵𝘪𝘰𝘯 𝘰𝘧 𝘣𝘺 𝘊𝘢𝘯𝘐𝘯𝘯𝘰𝘷𝘢𝘵𝘦 𝘯𝘦𝘸𝘴𝘭𝘦𝘵𝘵𝘦𝘳. 𝘠𝘰𝘶 𝘤𝘢𝘯 𝘧𝘪𝘯𝘥 𝘵𝘩𝘦 𝘧𝘶𝘭𝘭 𝘢𝘳𝘵𝘪𝘤𝘭𝘦 𝘢𝘵 𝘭𝘪𝘯𝘬 [1] 𝘪𝘯 𝘵𝘩𝘦 𝘤𝘰𝘮𝘮𝘦𝘯𝘵𝘴.  In recognition of this, in recent years there have arisen an increasing number of university-attached sources of funding for commercialization of academic IP. While a few have been operating for long enough to have exits, most are relatively new, and the approach being taken varies widely between universities. Over the last several months, I have been surveying sources of first cheques into deep tech companies available from across Canada. The goal of this effort was primarily to learn what has and what has not worked, and to synthesize the lessons learned into a document that can be used to guide design and iteration of such funds across the country. I was pleasantly surprised to find that while variation exists in implementation, there is clear consensus as to best practices and consistency in the lessons learned. In this article, you can find both a synthesis of my findings and a partial source document, which summarizes some of the content of the conversations that led to this article and serves as the beginnings of a map of the Canadian deep tech funding ecosystem. This is not a comprehensive ecosystem map, as many funds are not yet represented and will be added as more information becomes available. Both the source document and the primary article will be updated from time to time to reflect the addition of new interviews and additional guidance on best practices. Given the relatively short time that some of these funds have been in operation, ongoing information as to their evolution and success rates will be important in ensuring that this information remains relevant and useful. If you are involved in a relevant fund (defined as any organization that seeks to get the first cash injection above $25,000 into a startup company commercializing IP arising from a Canadian academic institution) that is not represented here, please reach out to schedule an interview. I would like to extend a heartfelt thanks to everyone who contributed to the research that went into this article. Your willingness to discuss the complexities and challenges of university commercialization projects and the first-hand insights you shared are invaluable in finding ways to address Canada’s challenges with deep tech commercialization. 

The "Canadian healthcare is broken" conversation usually starts and ends with wait times. But if we want to fix the wait times, we have to talk about the plumbing: how money actually flows through the system. In Canada, our single-payer model has created a "Global Budget" trap that is arguably the single greatest barrier to healthcare innovation. Most Canadian hospitals operate on fixed global budgets set by the province. Unlike a business where more "customers" (patients) equals more revenue to reinvest, in a Canadian hospital, a patient is often viewed financially as a cost driver. When an innovative startup proposes a tool that could help a hospital see 20% more patients, the hospital administration often sees 20% more costs they can’t afford, rather than a growth opportunity. In a system where funding is tied to historical spending rather than patient outcomes, efficiency is rarely rewarded. If a clinic finds a way to move patients through the system faster or prevent readmissions, their budget for the following year is often clawed back because they "didn't need it all." Innovation requires risk, but our bureaucratic incentive structure rewards stability and status quo over experimental efficiency. Because money flows from a single provincial source, procurement is centralized and risk-averse. Decision-makers prioritize lowest-unit-cost over value-based procurement. This is why Canadian health-tech companies often have to sell to the U.S. or Europe first just to prove their worth to their own backyard. Finally, money for hospitals, primary care, and long-term care comes from different "buckets." An innovation in a nursing home that prevents a hospital ER visit might save the system money, but because the savings happen in the hospital’s bucket and the cost happens in the nursing home’s bucket, the incentive to collaborate vanishes. We don't have a shortage of brilliant doctors, nurses, or tech innovators. We have a misalignment of incentives. Until we move toward funding models where money follows the patient and "value" is measured by outcomes rather than just line-item costs, Canada will remain a graveyard for healthcare innovation. We need to stop viewing healthcare as a cost to be managed and start viewing it as an infrastructure for innovation. Joshua Liu, MD Colin Deacon 🇨🇦🇺🇦 Brett Belchetz #HealthcareInnovation #CanadaHealth #HealthTech #PublicPolicy #DigitalHealth #HealthcareReform

AI doesn’t have a research talent problem. It has a productization talent problem. In Canada, we have world-class researchers, labs, and PhDs pushing the boundaries of AI. However, prototypes often stall at the pilot stage due to the lack of a clear path from research to scalable products. I wrote about why traditional product managers struggle to make the leap into AI, why it matters for Toronto’s AI economy, and what we can do to close the gap. What do you think is the biggest blocker to turning AI research into real, scalable products?