Innovative Projects Realized

Improving Community Care Outcomes with Data Analytics

Practicare aims to leverage technology to improve community care outcomes through a holistic lens of worker and organizational excellence. The company plans to directly tackle the #1 problem articulated by both care organizations and the clients that they support: the availability, skill, and turnover of care workers; and the direct impact this has on community care outcomes. Improving the care worker issues requires a rethinking of the processes and success-measures combined with the effective use of technology and data analytics throughout the care worker lifecycle – from recruitment, onboarding, and skill development through to worker engagement, retention and attrition.

Available technologies to support the processes and workflows typically focus on organizational efficiency, however, they often operate in silos or with loose connections and typically have disparate data systems with duplication and/or inaccurate information. While historical data is sometimes aggregated and summarized when sufficient data quality exists to provide a snapshot of the past; little attention has been placed on the insights available through data analytics and artificial intelligence, or on the collection of important information to help understand and influence care outcomes.

CAUDS Coalition Project

The intern will work on a project to develop a coalition of cross-sector community leaders in a mental health-care setting. The project will contribute to new solutions to community challenges in Canada surrounding the pharmacological treatment of alcohol use disorder. The intern will train in research skills, interdisciplinary teamwork, and community-based research methodologies. The intern will support long-term relationships among academia, industry, and communities, and establish new ones.

Design and development of a benchtop ophthalmic device for the treatment of vitreous floaters.

PulseMedica is developing a medical device platform to treat vitreoretinal eye diseases that affect over 500 million people worldwide. Our device consists of a state-of-the-art 3D imaging and surgical platform that allows for comprehensive patient treatment including machine learning based disease detection, surgical planning, surgical treatment, and post-surgery evaluation.

This device uses multiple laser-based imaging modalities to provide real-time 3D data about the posterior chamber of the eye. The imaging systems are then used to precisely guide light from a treatment laser to a target location. Both imaging systems, as well as the treatment laser delivery system are complex optical systems that take much time, effort, and expertise to design and build.

PulseMedica has decided to pursue vitreous floaters as its beachhead market. Vitreous floaters is a widespread eye condition that has a large unmet clinical need. Approximately 76% of the adult population has vitreous floaters and for 5% of people, vitreous floaters cause severe impairment. What makes this clinical indication a lucrative market opportunity is that, currently, there aren’t any widely accepted treatment options.

Enhancing software developer and user productivity

This project will investigate how software developers work with structured information. It will use information about that interaction to improve tools needed by developers. It will assess whether those tools improve the productivity of software developers. The project will also compare the access patterns of users of business intelligence applications to those of developers to determine if tools useful for developers might apply to more general knowledge workers. SAP may benefit from improved productivity of its developers and may benefit from ideas and knowledge to improve the applications it builds and deploys.

Quantification of anti-SARS-CoV-2 spike RBD IgG antibody and SARS-CoV-2 virus

The project is focused on designing and developing a novel point of care analytical device using functional magnetic microparticles that can quantitatively determine the concentration of anti-SARS-CoV-2 antibody and SARS-CoV-2 viruses in human saliva and serum. This approach will allow mass testing in the general population to assess past or current infection. Furthermore, it can guide decision-making regarding the optimal time to deliver subsequent vaccine doses and booster shots. The device will give enough information about immunity grown among the general population due to vaccination or prior infection to the virus. A proper market research will allow deciding the next step of commercialization.

A Lipo-Polymeric Approach to Breast Cancer Gene Therapy

Nucleic acid-based therapies such as DNA and siRNA has equipped us with the freedom to customize in our
battle against specific cancers and other diseases. Especially the non-viral approach to deliver the therapeutic
nucleic acids in a clinical setting provides a safer alternative to the viral gene therapy systems. However, to
achieve a clinically relevant outcome using non-viral systems, it requires the design and development of powerful
delivery vehicles capable to delivering multiple payloads to the disease cells while leaving the healthy cells
unaffected. Given the specificity of the TRAIL protein against cancer cells, this project will develop a platform for
long-term expression of TRAIL protein through the delivery of TRAIL DNA using a safe non-viral system and test
them in cell culture and animal disease models and aim for a clinical outcome.

Apprentissage automatique pour la résolution de problèmes de planification de rendez-vous dans des tournées de véhicules

La planification de rdv à domicile (infirmières ou pour rdv de techniciens) est complexe. Elle nécessite des compétences géographiques et une connaissance métier de répartiteur. Ce processus prend énormément de ressources. Ce projet vise donc projet à concevoir une méthode de suggestion d’horaire de rendez-vous sans avoir à réoptimiser de lourds emplois du temps.

Flame Spray Pyrolysis for Nanomaterial Based Electrodes

The research project will be focusing on the manufacturing of nanoparticles for the processing of symmetrical fuel-electrode half cells (as part of solid oxide cells). This will be conducted via flame spray pyrolysis, which uses aqueous salt solutions to produce metal oxide nanoparticles on electrolytes. Hereby, a fine mist is sprayed into a flame, which results in the formation of small droplets. In the subsequent pyrolysis reaction, the salt transforms to metal oxides that aggregate into nanoparticles. The use of the nanoparticles for symmetrical anode half cells is of great importance, as the operating temperature of the resulting solid oxide cells (SOCs) can be decreased from 800°C to 500°C, making them more energy efficient and consequently more climate neutral. In that, we are mostly interested in the symmetrical fuel-electrode half of the cell, as they have been less investigated, especially when it comes to the use of flame spray pyrolysis.

Émission d’hydrogène naturel associée aux gisements d’or dans la ceinture de roches vertes de l’Abitibi (Québec)

L’origine de l’hydrogène naturel, une alternative aux énergies fossiles, est encore mal contrainte dans les roches continentales. Nous avons récemment proposé un nouveau modèle dans lequel l’hydrogène est produit lors de l’altération des gisements d’or. Ce projet vise à effectuer des mesures de terrain dans la ceinture verte de l’Abitibi pour tester notre modèle. Il servira à financer un séjour de 2 mois à l’Université du Québec à Chicoutimi ainsi que 10 jours de terrain pour une stagiaire de Master 2. Le travail de la stagiaire consistera à préparer la mission de terrain, effectuer des mesures de gaz dans les sols et dans les mines, et à échantillonner de probables roches sources. Les données obtenues seront combinées pour déterminer le rôle joué par l’altération des roches des gisements d’or dans la production d’H2. Ce projet est hautement stratégique dans un contexte global d’estimation de la ressource en H2.

A soft magnetic small-scaled robot for biomedical applications

This study aims to develop a soft and flexible magnetic millirobot based on elastic and biocompatible polymers that can generate voltage as it moves. By using this proposed millirobot, locomotion efficiency can be increased with a decrease in resistance under challenging and harsh conditions in stomachs and digestion systems. In addition, it can serve as a carrier for a drug-loaded sponge, LED, or sensor since it is capable of carrying different objects. Providing less risky treatment for both patients and physicians is the main goal of this project.

Development in the fabrication of oxide nanowires used in biosensors

Detection and quantification of biological species are critical to many areas of healthcare and life science, either intending to diagnose diseases or discover and screen new medicine molecules. Central to detection are the biosensors that generate a signal associated with the selective recognition of a species of interest. Nanostructures, such as oxide nanowires with large surface-to-volume ratios, offer new and unique opportunities to develop novel biosensors. However, some challenges are associated with the fabrication of oxide nanowires, including poor quality of produced nanowires and high production costs. Such fabrication issues have limited the industrial development of nanowire-based biosensors. This proposed research targets a simple, scalable, and cost-effective approach for fabricating oxide nanowires used in biosensors. The proposed approach can potentially be a promising method for fabricating high-quality nanowires as it has demonstrated success in producing high-quality titanium dioxide nanowires. This approach also reduces the cost of mass manufacturing by eliminating the high-cost equipment.

Constraint Satisfaction Reconfiguration

The constraint satisfaction problem (CSP) is one of the classical problems studied in Theoretical Computer Science and asks for an assignment of values to variables such that given constraints are satisfied. The CSP includes as special cases for example graph coloring and Boolean satisfiability. Besides its theoretical importance, it has applications in many different domains, such as Scheduling, Operations Research, and Artificial Intelligence. We are interested in the structure of the solutions of CSP instances and approach this topic from the point-of-view of Combinatorial Reconfiguration. Based on our previous work, our goal is to make progress by pushing the limits of a recent topological approach to the problem.