Innovative Projects Realized

Improving the flame resistance of lyocell fibres using nanoparticles

Worldwide demand for man-made cellulosic fibres is increasing as availability of cotton fibre is limited. The regenerated cellulose lyocell process offers large advantages over other processes in terms of environmental and social impacts. However, cellulose is flammable. Current strategies to prepare flame-resistant (FR) regenerated cellulose fibre involve the incorporation of a fine powder of organophosphate or silica additives in the fibre or the use of phosphorylated cellulose pulp. Unfortunately, it reduces the strength of the fibre when used at a high enough ratio to achieve the level of flame resistance required for application for FR workwear and personal protective equipment (PPE).

As an alternative solution, this project aims to explore the use of nanoparticles to render lyocell fibres FR while preserving their strength as well as their biodegradability. The work will include the synthesis of the FR nanoparticles and their incorporation into the cellulose dope to prepare FR lyocell fibres. Ultimately, this research will allow the development of made-in-Canada FR and environmentally-friendly lyocell fibres using local sources of cellulose such as hemp and recycled textiles. It will provide a local source of FR fibre for the Canadian FR workwear and PPE industry, insuring a more stable and traceable supply chain.

Reconstitution de la variabilité climatique holocène au centre du Canada à partir des assemblages de chironomes subfossiles

Le climat de la planète se réchauffe rapidement, et les régions boréales du Canada sont parmi les plus touchées. Pour comprendre comment ces forêts réagiront au réchauffement actuel, il est essentiel de connaître comment le climat a évolué dans le passé. Ce projet cherche à reconstituer les variations de température des 13000 dernières années au centre du Canada, à partir d’insectes appelés chironomes dont les larves se développent dans les lacs.
Les chironomes sont très sensibles aux changements de températures, et laissent dans les sédiments lacustres des restes fossilisés. En les étudiant au microscope, il est possible d’estimer les températures qui régnaient au moment où ils vivaient. L’étudiante du projet analysera les sédiments d’un lac du sud du Manitoba pour retracer, avec une grande précision, l’évolution du climat depuis la fin de la dernière glaciation jusqu’à aujourd’hui.
Ces nouvelles données permettront de combler un vide important dans les archives climatiques du Canada et d’améliorer notre compréhension des variations de température à l’échelle nationale. En comparant les résultats obtenus avec ceux de l’est et de l’ouest du pays, le projet contribuera à reconstituer une vision cohérente du climat de l’Holocène et à mieux anticiper les impacts du réchauffement futur sur les forêts boréales.

Design of an Augmented Reality Interface for Ultralight eVTOL Aircraft

Mostavio is a Toronto-based aerospace company developing ultralight electric vertical takeoff and landing (eVTOL) aircraft designed for safe, efficient, and sustainable personal air travel. The company focuses on lightweight structures, automation, and human-centered design to make advanced air mobility more accessible. This project explores the use of augmented reality (AR) to improve how pilots and operators interact with eVTOL systems. The intern will evaluate various AR headsets and build a prototype interface that displays key flight data—such as altitude, speed, battery status, and GPS position—directly in the pilot’s field of view. The goal is to create a lightweight, easy-to-read AR display that enhances situational awareness and reduces the need for conventional cockpit instruments. For Mostavio, the research will provide valuable insights into integrating AR technology into future eVTOL models. The project will help demonstrate how immersive visualization can improve safety, comfort, and user experience in next-generation electric aviation.

Outdoor air pollution and cancer in Canadian children

Outdoor air pollution is a human carcinogen. This classification is based largely on a series of studies that has shown it increases respiratory cancers in adults. There is more limited evidence that that suggests it increases the risk of childhood cancer. To date, there have been few Canadian studies on this topic, and none that have been national in scope. This study will make use pre-existing cohort data assembled at an individual level that was created by the record linkage of national birth, cancer incidence, and mortality and income tax databases between 2000 and 2021. Air pollution surfaces have been generated that can be linked to place of residence of the children. This will allow us to estimate the risk of developing childhood cancer among those living in more highly polluted areas relative to those less polluted. These risks will be generated separately for common types of childhood cancers, including leukemia, brain tumors, and lymphomas. We will examine biological sex differences in air pollution risks by estimating risks separately for boys, and girls. The study will be carried out at Carleton University and include an interdisciplinary team of researchers including those within the federal government.

Mathematical Models of Oncolytic Virotherapy Including Oxygen Dependent Phenotypic Adaptation

This project develops mathematical models to investigate how tumour heterogeneity and oxygen availability influence the efficacy of oncolytic virotherapy (OVT). OVT employs genetically engineered viruses to selectively infect and destroy cancer cells, yet its therapeutic success is often hindered in hypoxic tumour regions, where low oxygen levels promote cellular adaptations that reduce viral replication and therapeutic response. The proposed models will integrate oxygen gradients and phenotypic diversity to elucidate their combined impact on viral dynamics and treatment outcomes. By quantitatively characterizing these interactions, this work aims to provide mechanistic insights that can inform the design of more robust oncolytic viruses and optimized combination therapies capable of overcoming the barriers imposed by hypoxic and heterogeneous tumour microenvironments.

Prompt optimization method to maximize the accuracy and reliability of LLM outputs

Draft & Goal (D&G) is a Canadian artificial intelligence (AI) company developing a no-code platform that automates marketing workflows using AI agents for writing, search engine optimization, and fact-checking. The integration of large language models (LLMs) is central to their software solution: it allows non-technical users to harness advanced AI for content creation. However, unlike traditional software systems, LLMs are inherently non-deterministic and opaque, making their behavior difficult to predict or control.
Currently, D&G’s developers rely heavily on manual trial-and-error strategies to craft effective prompts (i.e., instructions input to the LLM) [1, 2]. This process is time-intensive, brittle, and often produces results that fail to generalize across domains or models [3]. The lack of systematic tools for prompt design leads to inefficiencies in development, higher operational costs, and limited scalability. Therefore, automating prompt optimization is critical for D&G’s ability to deliver consistent, high-quality outputs at scale.
Through this project, D&G aims to integrate data-driven methods for refining prompts, informed by execution feedback. The anticipated benefits include increased efficiency in product development, improved reliability of AI outputs, and a stronger competitive position in Canada’s growing AI software market. This project will also reduce costs and broaden accessibility of advanced AI tools for non-technical users.

État des connaissances sur la vulnérabilité aux changements climatiques de l’approvisionnement québécois en énergies renouvelables

Les changements climatiques posent un défi croissant pour l’approvisionnement en énergies renouvelables au Québec. Au-delà de l’hydroélectricité, déjà bien étudiée, des filières comme l’éolien, le solaire, la biomasse, la géothermie et le gaz naturel renouvelable (GNR) demeurent sous-analysées. Pourtant, elles sont appelées à jouer un rôle clé dans la transition énergétique de la province. Ces filières sont exposées à divers aléas climatiques : modification des régimes de vent, vagues de chaleur, givrage des pales, sécheresses, inondations, feux de forêt ou encore événements météorologiques extrêmes. Ces perturbations affectent non seulement la production d’énergie, mais également la durabilité des infrastructures, les coûts d’exploitation et la sécurité des travailleurs.
Le projet proposé vise à dresser un premier état des connaissances sur la vulnérabilité des filières renouvelables québécoises face aux changements climatiques et à explorer des mesures d’adaptation. Pour ce faire, une revue exploratoire de la littérature scientifique et grise sera menée, combinée à l’analyse d’indicateurs de vulnérabilité adaptés au contexte québécois. L’accent sera mis sur l’identification des aléas climatiques pertinents, la classification des vulnérabilités selon le cycle de vie des technologies (conception, construction et installation, exploitation, maintenance, fin de vie), ainsi que la recension des stratégies d’adaptation recensées à l’international et applicables localement.
Les résultats

Functional genomic analysis of patient-derived pre-clinical models of renal cancers to identify novel therapeutic targets

Clear cell renal cell carcinoma (ccRCC) is the most common form of kidney cancer. Its metastatic form (mRCC) remains incurable and resistant to chemotherapy and radiation. Current treatments targeting the tumor microenvironment offer limited benefit, highlighting the need for new strategies based on disease biology. ccRCC is difficult to target due to its cellular heterogeneity and limited understanding of its vulnerabilities.
Our lab’s single-cell RNA sequencing (scRNA-seq) of patient-derived xenograft (PDX) models identified a subpopulation of cells with progenitor-like features capable of differentiating into multiple tumor cell types. These findings support the existence of cancer stem cells (RCC-CSCs) driving tumor growth, aggressiveness, and therapy resistance.
This project aims to identify essential genes for RCC development by targeting RCC-CSCs. From scRNA-seq data, we identified genes upregulated in RCC-CSCs and will perform a focused CRISPR-Cas9 dropout screen in patient-derived 3D organoid models to pinpoint genes required for tumor initiation and maintenance.
The screening will take place in Dr. Michael Boettcher’s lab at Martin Luther University Halle-Wittenberg, leveraging expertise in CRISPR functional genomics. Results will define RCC-CSC vulnerabilities and guide new therapeutic approaches for metastatic ccRCC, a currently incurable malignancy.

In vivo screening of interactions between glycans and immune cells

The proposed Research Plan is to evaluate the active targeting effect of glycan ligands for the delivery of conjugated lipid nanoparticles (LNPs) to human bone marrow CD34 + hematopoietic stem and pluripotent cells (HSPCs) and human peripheral blood mononuclear cells (PBMCs) such as T cells and B cells. A reporter mRNA will be formulated into LNPs with or without glycan ligand conjugation. The activity of these LNPs will be assessed both in vitro and in vivo.

Co-creating digital tools to support learning communities

In Canada and worldwide, health systems are facing tremendous capacity pressures with aging populations putting increasing demands on health services. Caregivers play a vital role in supporting older adults at home. Caregivers often experience distress and burnout and need help navigating the health system. The overall goal of the project is to evaluate the feasibility of building a learning health community (LHC) for informal caregivers to share knowledge and acquire skills to support their caregiving journey, as well as codevelop navigation tools for supporting older adults to stay at home longer. We define a LHC as a community of learners who use tools to collect data and information for generating community knowledge in continuous learning cycles.

Caractérisation génomique et phénotypique d’Enterococcus cecorum : vers le développement d’un modèle d’infection expérimentale chez le poulet

Ce projet de recherche vise à mieux comprendre une bactérie appelée Enterococcus cecorum, qui cause des infections graves chez les poulets de chair. Depuis quelques années, cette bactérie est devenue l’un des principaux problèmes de santé dans les élevages avicoles, entraînant boiteries, mortalité et pertes économiques importantes pour les producteurs. Les chercheurs vont analyser les caractéristiques génétiques et biologiques de différentes souches de cette bactérie pour identifier celles qui sont les plus virulentes. Grâce à ces analyses, ils pourront développer un modèle d’infection en laboratoire, une étape essentielle pour tester des méthodes de prévention et de traitement de la maladie. L’objectif est de trouver des alternatives aux antibiotiques, afin de protéger la santé des animaux tout en respectant les meilleures normes d’élevage le tout dans un contexte de production durable. Ce projet contribuera à améliorer la santé des poulets de chair, à soutenir les éleveurs et à renforcer l’innovation scientifique au Canada dans le domaine de la santé animale.

Mitigating the risk of business value erosion associated with delayed or insufficient AI adoption

Small and medium-sized enterprises (SMEs) are facing an inflection point in their digital journey, with artificial intelligence (AI) emerging as a foundational technology for operational efficiency, customer experience, and strategic differentiation. However, despite increasing awareness, a substantial number of SMEs remain hesitant or unprepared to adopt AI technologies, risking competitive stagnation or decline. This project addresses a critical and underexplored challenge: how can SMEs assess whether their core business value is at risk due to delayed or insufficient AI adoption?