Innovative Projects Realized

Using Viral Dynamics to Connect Clinical Markers of Disease Progression to Sequence Evolution for HIV-1

HIV-1 remains a global health challenge, with over 35 million people infected. The high rates of turnover and evolutionary adaptability exhibited by HIV-1 pose a particular challenge to the use of antiretrovirals, as well as the development of a vaccine. Our focus is to understand the dynamics of two of the most commonly tracked clinical markers of an HIV-1 infection: CD4+ T cells/mm3 (CD4 count) and HIV-1 RNA/ml (viral load). We are developing a dynamic mathematical model of HIV-1 infection that uses equilibration, adaptation, and inheritance to model the initial infection by a founding virus as well as successive generations of viral lineages. We have calibrated our model to match viral load set points and rates of CD4 decline from 91 HIV-infected individuals studied longitudinally during early stages of the disease. We plan to incorporate sustained tissue damage and antiretroviral treatment to study how drug resistance could develop.

L2M – Study for the Smart Risk Assessment & Micro-Segmentation of Networks

This project aims to develop an innovative and novel cybersecurity solution tailored for Canadian small and medium-sized enterprises (SMEs), focusing on smart risk assessment and automated network segmentation. Many SMEs lack full visibility into their IT infrastructure, leaving them vulnerable to cyber threats. This project will study the challenges and needs of SMEs across different sectors through direct engagement, identifying security gaps and compliance requirements under Canadian Bill C-26, PIPEDA, and provincial privacy acts. The findings will help tailor our novel solutions to address these sector-specific challenges, ensuring practical, automated risk assessment and mitigation. By reducing reliance on foreign technologies, this project strengthens Canada’s cybersecurity resilience, with potential for global adoption and economic growth in the sector.

L2M Augmented Reality Sensorimotor Training

The proposed project focuses on launching an augmented reality sensorimotor training (ARST) system to help individuals with chronic neck pain (CNP) manage their condition more effectively. ARST is designed as an engaging, non-invasive, and accessible at-home therapy that retrains sensorimotor control using augmented reality technology. The project aims to validate the business model, integrate ARST into real-world clinical settings, and develop a go-to-market strategy. The expected benefits for the partner organization include a refined commercialization plan, strategic partnerships with clinics and healthcare providers, and increased market traction for ARST. By addressing critical barriers to adoption, this project will help position the partner organization as a leader in innovative pain management solutions.

L2M – Wonder Guard: An Integrated Catheter Bag Module with Electrochemical Biosensing and Machine Learning for UTI Detection

Wonder Guard is an advanced catheter bag system that uses electrochemical biosensors and machine learning to detect urinary tract infections (UTIs). 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. During this project, interviews with healthcare practitioners will be conducted, small-scale pilot studies will be developed, and the investment required to bring this invention to real-world use will be analyzed. By gaining these insights, the partner organization will have a clearer picture of how to manufacture and distribute Wonder Guard, how to meet healthcare standards, and how to prove that it minimizes infections. This process, ultimately, will lead to an infection-reducing, cost-saving product with better patient outcomes and lower hospital expenses.

L2M – Commercialization of Natural Polymer-Based Wound Dressings

In collaboration with the Lab2Market Validate program, our goal is to transition our natural polymer-based wound dressing from the lab bench to commercial scale. Designed specifically for individuals with chronic wounds and fragile skin conditions, our hydrogel-based dressing aims to fill a critical gap in the market. Through the program, we seek to deepen our understanding of the market landscape by interviewing potential clients, including healthcare professionals and patients. Their feedback will be invaluable in refining our product to better meet user needs. Additionally, the L2M program provides an opportunity to connect with industry experts who have successfully brought similar technologies to market. We will also gain insights from regulatory specialists on securing government clearance and protecting our intellectual property.

L2M MITACS-Market Assesment for CardiAxis Medical

The study team has developed a software program called SHARP-VT that doctors can use to quickly plan non-invasive treatments of irregular heart-beats using external-beam radiation therapy. In this study the candidate will conduct a detailed review of the commercialization potential for this software program in the North American and European Union markets. This review will follow the standard methods described in the ‘Lab-2-Market – Validate’ program. This assessment will enable the study team to begin the process of venture capital funding for a company to bring this software to market. The partner DMZ Ventures will gain experience in helping to bring Canadian technology to market.

L2M-Materiax AI

This project will explore the market potential of a new technology that uses advanced artificial intelligence, powered by both classical and quantum methods, to help companies discover new materials faster and more efficiently. The intern will work closely with mentors and industry experts to identify which industries can benefit the most from this innovation and how to turn it into a successful business. The expected benefit to the partner organization is a clear plan for how to bring this technology to market, helping lay the foundation for a future startup that could support industries like semiconductors, clean tech, and advanced manufacturing.

Artificial Intelligence and Robotics – Emergent Language via Deep Reinforcement Learning

Leveraging Large Language Models for Sales & Customer Success Automation

Mash helps revenue teams at technical B2B companies streamline pre- and post-sales activities by automating knowledge-intensive tasks such as answering product questions, managing bug reports and feature requests, and prepping for meetings. Its AI platform leverages data buried in messaging platforms, wikis, CRMs, and other internal tools to deliver timely, context-aware assistance to individuals in sales and customer success roles. Significant time is spent by individuals in these roles seeking out product knowledge and technical expertise in the context of customers’ needs. An internal point-person responsible for a given customer is often juggling multiple accounts at once and may not have all the necessary knowledge to effectively serve them. This often means scouring outdated documentation, incomplete notes, and past conversations for information, and pulling in other team members for help.
Through this project, Mash aims to work with the intern to incorporate cutting-edge LLM-related technologies into its platform to further improve its customers’ ability to access internally available information. By leveraging AI to reduce the manual work and multi-party overhead associated with traditional knowledge-sharing processes, Mash’s customers will be able to serve their own customers more effectively, preventing lost leads and churn, resulting in additional revenue.

L2M – Market Assessment to Support the Commercialization of an Innovative Structural Thermal Break

Thermal bridging is a significant challenge in building design, increasing heat loss, raising energy demand, and reducing occupant comfort. As awareness of its impact grows, Canadian building standards are evolving to mandate more sustainable and energy-efficient construction practices. However, existing solutions for mitigating thermal bridging, particularly in balconies, are often ineffective, difficult to install, or require non-standard construction methods, limiting their widespread adoption.
This 4-month Mitacs Business Strategy Internship focuses on market assessment and commercialization planning for a novel Structural Thermal Break (STB) technology that mitigates balcony thermal bridging. The intern, directly involved in developing this technology, will receive specialized training in market analysis, commercialization strategy, and intellectual property (IP) development. The project will support creating a comprehensive and practical commercialization plan tailored for industry adoption by identifying limitations in current solutions and addressing barriers to market entry.
A key outcome of this project is to support the procurement of a patent, strengthening the technology’s potential for widespread implementation. This initiative aims to bridge the gap between cutting-edge research and real-world applications through market research and strategic planning, contributing to more sustainable and energy-efficient building practices across Canada.

Development of Climate and Infrastructure Forensic Analysis Systems: A BayesianPerspective

This project will upgrade the Climate and Infrastructure Forensic Analysis System (CIFAS), originally developed to characterize snow- and permafrost-related impacts to ground transportation and mine access roads in the Canadian North. My first objective is to enhance the analytical capacity of CIFAS by improving its ability to quantify uncertainties associated with empirical knowledge used to causally connect infrastructure service levels with climate-induced disturbances, as well as with climate projections from climate models. My second objective is to broaden the scope of the forensic analysis framework to consider issues related to freshwater security in Canada. I will illustrate the development of a prognostic tool for rapidly assessing the implications of climate change for lake phenology. The final deliverable will be a novel risk assessment methodology, integrated within CIFAS. Founded upon empirical knowledge, mathematical and statistical modelling, this addition will meaningfully support advancements in climate change policy making, infrastructure design, and management.

Investigation of the therapeutic potential of JAK1-inhibitors in desmin-related cardiomyopathy