Innovative Projects Realized

L2M – InsurEasy: A Multilingual AI Agent for Transparent, Commission-Free Coverage in Canada

InsurEasy is a multilingual AI insurance agent that provides Canadians with transparent, commission-free coverage recommendations, making insurance more affordable and easier to understand for everyone.

L2M – Commercialization Strategy and Indication Prioritization for Oncolinc Therapeutics

This project will help Oncolinc Therapeutics, a cancer therapeutics company, build a clear strategy for bringing a new type of cancer treatment to market. Oncolinc Therapeutics is developing therapies that target long non-coding RNAs (lncRNAs), which are molecules that help some tumours hide from the immune system and resist current immunotherapies. Oncolinc needs guidance on where to start, which cancer types to focus on first, who the key decision-makers are, and how and when to partner with larger drug companies. Over four months, the project will evaluate different cancer indications, such as liver cancer and ER-positive breast cancer, to determine which offers the best opportunity for early success. It will also map out the perspectives and needs of clinicians, researchers, and pharmaceutical partners to understand how a new lncRNA-targeting therapy could be adopted in the real world. Finally, the project will outline a partnership and business model strategy to help Oncolinc plan for investment, collaboration, and long-term growth. This work will give Oncolinc a practical roadmap to guide its next steps, reduce risk, strengthen its commercial readiness, and support its goal of delivering new treatment options for patients who do not respond to current immunotherapies.

L2M – Market Entry and Human Factors Strategy for an Edge AI-Based Care Platform

This project focuses on launching and evaluating the NewGen Smart-Cup platform in clinical settings. NewGen Smart-Cup enables rapid, digital urine testing to support early detection of conditions such as preeclampsia and gestational diabetes. Building on prior validation work, this phase will study how healthcare teams adopt and integrate the technology into existing prenatal care routines. Through close collaboration with obstetricians, nurses, and clinic staff, the project will examine usability, workflow fit, and patient engagement to ensure the solution enhances, rather than disrupts care delivery. Insights from these real-world pilot implementations will guide large-scale deployment, training design, and commercialization strategy.

Enhance analyses and improve processes for communication of infectious disease trends and insights

Globally, there have been challenges in pulling together data, analyses, epidemiological insights, and unusual infection disease trends into comprehensive and regular reporting, that support pharmaceutical and life sciences organizations with timely intelligence for decision making. BlueDot has the knowledge and expertise to bring together these insights in a highly visual, easily understandable regular reporting format, by leveraging proprietary and publicly available data. However, there are challenges in scaling across diseases and locations to meet the growing demand for this content, as well as limited resourcing to improve upon processes, analyses, and methods to deepen our insights and improve efficiency.
Through previous MITACS projects, BlueDot began developing the infrastructure for the regular reporting format, by automating data pipelines and repeatable analyses and processes. In this project the interns will be leveraging the pre-built data pipelines and models to conduct repeatable and scalable analyses of global infectious disease trends. They will contribute their growing expertise by developing data-driven insights, and continue building upon the foundation that has been developed by adding new statistical and mathematical models and data visualizations as automated repeatable analyses across diseases and locations to meet the variety of needs of our clients.
This project has several challenges and opportunities that interns with subject matter expertise and experience with relevant data can help with and learn from. The interns can be helpful every step of the way – determining usability of new data sources for communication of disease trends, thinking about how the data can be used for generating actionable insights, producing these regular reports with support from senior team members, including more complex analyses, and improving the overall processes for report generation and automation.

L2M – Transforming Pediatric Neurodevelopmental Interventions: A Novel Model for Enhancing Social Skills and Reducing Challenging Behaviors in Children with ASD and ADHD

The Interactive Multisensory Physical Movement (IMPM) model addresses a critical and growing gap in pediatric neurodevelopmental care. It offers a rigorously designed, non-pharmacological therapeutic approach for autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD). Current treatments often focus on short-term symptom management, have adverse side effects, and produce limited long-lasting improvements in social functioning, attention regulation, and daily living (Cook et al., 2022; Reijnders, 2019).

The IMPM utilizes a multifaceted approach, integrating holography, immersive virtual and augmented reality, and advanced eye-tracking technology to create a multisensory therapeutic environment. This environment facilitates simultaneous multisensory stimulation and movement-based learning, targeting fundamental neurodevelopmental mechanisms such as sensory integration, attentional networks, motor planning, and social reciprocity. The IMPM approach enables measurable and sustained functional improvements, avoiding the risks associated with pharmacotherapy.

By validating a scalable, technology-enabled, holistic intervention that is both clinically effective and cost-conscious, IMPM has the potential to transform pediatric neurodevelopmental services. This transformation would improve developmental trajectories, reduce long-term care burdens, and deliver higher quality of life for millions of children and families. The pathway from validation to commercialization is meticulously designed to yield peer-reviewed evidence, regulatory alignment, and robust stakeholder engagement, thereby facilitating the expeditious adoption of responsible practices within healthcare and educational systems on a global scale.

Stage IREC – Intégration des NWA (Non-wire alternatives) dans le contexte québécois de transition énergétique

Dans un contexte de transition énergétique, le Québec prévoit accroître sa production d’énergies renouvelables comme l’éolien et le solaire. Cependant, cette évolution ne peut reposer uniquement sur de nouveaux investissements massifs dans les infrastructures électriques. Les Non-Wire Alternatives (NWA) telles que la gestion de la demande, le stockage d’énergie, les microréseaux ou les plateformes numériques de flexibilité représentent des solutions locales, évolutives et souvent plus économiques. Déjà utilisées ailleurs dans le monde, elles permettent de stabiliser le réseau, d’optimiser les installations existantes et de faciliter l’intégration des énergies renouvelables. Au Québec, ces approches restent peu développées. Le modèle actuel, centré sur une planification centralisée par Hydro-Québec, évolue toutefois sous la pression des objectifs climatiques et des besoins de développement régional. Cette situation ouvre une fenêtre d’opportunité pour repenser notre gouvernance énergétique. Ce projet vise à analyser comment les NWA pourraient s’intégrer dans le contexte québécois économique, réglementaire et politique afin de soutenir à la fois la transition énergétique et la vitalité des régions.

L2M-Local Connect

This project aims to develop a scalable, data-driven model for regional food distribution that connects local producers with restaurants, retailers, and institutions through an efficient cold-chain supply network. By addressing current logistics challenges—such as fragmented delivery routes, inconsistent volumes, and lack of shared infrastructure—the project will design a system for demand aggregation, route optimization, and coordinated supplier distribution, reducing empty miles, emissions, and operational costs while improving food security and producer profitability. Building on Local Connect’s existing operations, the internship will focus on gathering purchasing data, negotiating supplier pricing, forecasting volumes, and testing real-world delivery routes to validate a financially sustainable and environmentally responsible model for regional food systems. This proposal directly supports Mitacs’ goals by advancing innovation in supply chain processes, enhancing economic resilience in the agri-food sector, and creating a replicable framework that strengthens local economies and community food access.

L2M Launch – Wonder Guard: An AI-Powered Catheter Sensor System to Detect and Predict Infection

Wonder Guard is an AI-powered catheter sensor system that is capable of detecting and predicting infection. We are developing an infection surveillance system using electrochemical DNA biosensors and AI-driven analytics to make assisted diagnoses. The device is a module add-on to existing hospital catheter systems that can continuously produce and analyze data to monitor UTIs, with faster results than standard urine cultures and richer insights than urine dipsticks. This project will be run by Lab2Market Launch as a four-month program that will turn this project into a scalable venture through structured mentorship and hands-on workshops to build a clear, fundable business case.

L2M – InclusivAI: AI-powered Instructional Design Agent

This project focuses on validating InclusivAI, an AI-powered instructional design agent that helps faculty redesign courses for greater inclusivity and accessibility. Grounded in established frameworks for inclusive education and accessibility, InclusivAI applies AI to support evidence-informed course design and faculty development. Through the Mitacs Lab2Market Validate program, the project will analyze insights from faculty and institutional leaders, test a low-fidelity prototype using no-code tools, and assess its feasibility for institutional integration. By advancing InclusivAI from a research concept to a validated and scalable solution, the project contributes to Canada’s goals for digital equity, lifelong learning, and innovation in higher education.

L2M – The Edge-Aware Diffusion for Contrast Enhancement

Artificial intelligence tools for contrast enhancement in medical imaging often improve visibility but may remove subtle structural details, reducing diagnostic reliability and clinical confidence. This project focuses on validating and preparing for the commercialization of the Edge-Aware Diffusion for Contrast Enhancement framework, which uses an edge-aware diffusion process to improve image contrast while preserving fine anatomical boundaries.

Through the Lab2Market Validate program, this internship will connect with radiologists, imaging engineers, and artificial intelligence specialists to evaluate clinical usability, interpretability, and integration needs. Insights from expert interviews will guide prototype refinement and the development of a business model and commercialization plan.

The project supports the growth of Canada’s medical technology sector by combining scientific validation with stakeholder engagement to build safer, more reliable imaging tools that improve diagnostic accuracy and reduce healthcare costs.

L2M – SensRIM

For manual wheelchair users, mobility means pushing thousands of times each day, often leading to pain, fatigue, and upper-limb injuries. SensRIM is an innovative, sensor-integrated ergonomic pushrim designed to transform this daily effort into data-driven mobility, enhancing independence, comfort, and health outcomes. By embedding soft tactile sensors that directly measure propulsion forces and detect user intent, SensRIM provides a novel, intuitive control input surface for power-assist applications while delivering real-time feedback on propulsion technique. This enables smarter power-assist control, fitness tracking, and clinical insights for rehabilitation. Bridging the gap between manual and power-assist mobility solutions, SensRIM offers a lightweight, ergonomic, and low-maintenance alternative that minimizes the moving parts found in traditional force-inferred control systems. With broad potential across rehabilitation, smart mobility, and health monitoring, SensRIM addresses critical unmet needs in a global wheelchair market projected to exceed USD 10 billion by 2032, offering a smarter, safer, and more independent approach to mobility.

L2M – GradientX

Nowadays, many young Canadians [2] and newcomers [1] begin their financial journey with limited access to guidance on saving and investing, which leaves them at risk of debt and missed opportunities to build wealth. Existing tools are often complex and designed for experienced investors, not beginners. This project aims to develop and validate GradientX, an AI-powered financial tutor that helps individuals improve their financial literacy through personalized guidance, real-time market insights, spending analysis, and a risk-free virtual investing “sandbox“. Through participation in the Lab2Market program, the project will conduct user discovery and market validation to identify key pain points and refine the business model. The collaboration will benefit Lab2Market by contributing to its mission of translating academic research into viable market solutions and fostering Canada’s next generation of entrepreneurial researchers.