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

VITAL is a genuinely good idea. Connecting de-identified clinical data from 160 hospitals across Ontario, Alberta, and Quebec to serve 20 million Canadians is real infrastructure solving a real problem. I’ve spoken with researchers who told me it can take up to two years just for co-investigators on the same federal grant to share data with each other. If this breaks those silos down? Genuinely, amazing... But here is what will actually determine whether this investment succeeds—and none of it is solved by a $100 million cheque: 1. The Incentive Problem Our current "currency" in Canadian research is academic papers, not patients helped. Clinicians and institutions are still effectively competing to publish first, rather than racing to put data into active use. Infrastructure doesn't fix a broken incentive structure. We still don't know what internal compliance and regulatory red tape individual institutions will layer on top before they actually turn on the data tap. 2. The Adoption Gap This is a federal announcement, but adoption isn’t a federal decision. Each province, hospital, and institution decides how to integrate this, how fast, and under what internal rules. This is diffusion of responsibility in its purest form—the money lives at one level of government, while the execution live at a dozen others. We won’t know if VITAL works until we see if the provinces actually move. 3. The Commercial Roadblock Even if the data flows seamlessly, what happens to the Canadian companies building on top of it? What regulatory, procurement, and compliance hurdles will they face just to access it? Once they build something world-class, will our hospital procurement systems actually adopt it? We already struggle to reimburse proven therapeutic drugs in this country; we haven’t even begun to answer how we scale and pay for AI-driven health tools. Risk aversion, inertia, diffusion of responsibility—you can watch all three behaviors play out, live, in how this single announcement unfolds over the next two years. Canada is world-class at funding the starting line. This is a real test of whether we can finally build a finish line. I want to be wrong about this. What do you think—does VITAL fundamentally change the equation, or is it just a very well-funded input into a system that still doesn't know how to use it? #InnovationParalysis #HealthTech #CanadianInnovation #HealthData #DigitalHealth #Pharma

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.