Innovative Projects Realized

Explore thousands of successful projects resulting from collaboration between organizations and post-secondary talent.

29670 Completed Projects

2811
AB
4990
BC
801
MB
663
NL
825
SK
8841
ON
9197
QC
95
PE
568
NB
1088
NS

Projects by Category

Developing rAAV-mediated retinal gene therapy to improve vision for ZellwegerSpectrum Disorder – Year Two

Peroxisome Biogenesis Disorders of the Zellweger Spectrum (PBD-ZSD) are a group of inherited genetic disorders caused by mutations in any one of 13 PEX genes. Individuals with the common PEX1-G843D mutation consistently develop a retinopathy that progresses to blindness. To test whether we could slow visual loss in these patients, we performed a proof-of-concept trial for PEX1 retinal gene augmentation therapy using our mouse model homozygous for the equivalent PEX1-G844D mutation. We found that expression of functional PEX1 in the retina of this mouse model resulted in twofold improvement of retinal function over 6-7 months, and was effective at both earlier and later disease stages. In partnership with AmorChem Therapeutics, we will advance the preclinical, and eventually clinical, development of this therapy. Dr. Argyriou will lead the maturation plan over the 2-year Postdoctoral fellowship. The project includes experiments to establish the optimal design of the clinical gene delivery vector, dose, and efficacy, as well as establishing a business plan towards commercialization. These experiments will lead to safety and toxicology studies in nonhuman primates and an ultimate transition to the clinic.

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Faculty Supervisor:

Nancy Elise Braverman

Student:

Partner:

Amorchem Therapeutics Inc

Discipline:

Life Sciences

Sector:

Finance and Insurance; Professional, scientific and technical services

University:

Research Institute of the McGill University Health Centre

Program:

Elevate

Developing rAAV-mediated retinal gene therapy to improve vision for ZellwegerSpectrum Disorder

Peroxisome Biogenesis Disorders of the Zellweger Spectrum (PBD-ZSD) are a group of inherited genetic disorders caused by mutations in any one of 13 PEX genes. Individuals with the common PEX1-G843D mutation consistently develop a retinopathy that progresses to blindness. To test whether we could slow visual loss in these patients, we performed a proof-of-concept trial for PEX1 retinal gene augmentation therapy using our mouse model homozygous for the equivalent PEX1-G844D mutation. We found that expression of functional PEX1 in the retina of this mouse model resulted in twofold improvement of retinal function over 6-7 months, and was effective at both earlier and later disease stages. In partnership with AmorChem Therapeutics, we will advance the preclinical, and eventually clinical, development of this therapy. Dr. Argyriou will lead the maturation plan over the 2-year Postdoctoral fellowship. The project includes experiments to establish the optimal design of the clinical gene delivery vector, dose, and efficacy, as well as establishing a business plan towards commercialization. These experiments will lead to safety and toxicology studies in nonhuman primates and an ultimate transition to the clinic.

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Faculty Supervisor:

Nancy Elise Braverman

Student:

Partner:

Amorchem Therapeutics Inc

Discipline:

Life Sciences

Sector:

Finance and Insurance; Professional, scientific and technical services

University:

Research Institute of the McGill University Health Centre

Program:

Elevate

Perioperative Opioid Usage Quality Improvement [CDTS-PDF1]

Our aim is to use machine-learning to improve treatment of post-surgical pain in children and adults. Most people addicted to opioids were initially exposed through the treatment of pain from trauma and/or surgery. The opioid crisis is reaching the pediatric population, in whom effective post-surgical pain management, with less reliance on prescription of opioids, is more important than ever. Recent advances in machine-learning, combined with approaches to patient-oriented research, provide significant prospects for a learning health system. Such a system could risk-stratify children and adults before surgery, so that pre-habilitation and optimized analgesic combinations can be employed to reduce persistent post-procedural pain. Artificial intelligence-augmented systems will also give clinicians actionable feedback on their practice, so they can learn how to improve their care, reduce their patients’ risk further, and
help them to recover more quickly from their procedure.
Postdoctoral fellows will lead day-to-day project activities and spend significant time working with both our clinical sites (St. Paul’s Hospital and BC Children’s Hospital) as well as industry partners (Careteam and Xerus) who will benefit from their methods expertise, ability to collaborate with clinicians and academic researchers, design, implementation, and evaluation skills.

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Faculty Supervisor:

Matthias Görges

Student:

Partner:

Careteam Technologies Inc

Discipline:

Engineering

Sector:

Health and Related Sciences & Technology; Information and cultural industries; Professional, scientific and technical services

University:

The University of British Columbia

Program:

Elevate

Étude préliminaire de la situation d’envahissement du nerprun: Revue de littérature et mise en place d’un dispositif expérimental pour une gestion efficace du nerprun dans les bois de Laval

Depuis des milliers d’années, les déplacements des humains ont introduit des espèces exotiques dans des milieux où elles ne se retrouvaient pas naturellement. Une de ces espèces, le nerprun, a été introduite en Amérique du nord vers la fin des années 1800. Elle prend aujourd’hui de plus en plus de place dans nos environnements forestiers, menaçant les l’équilibre des écosystèmes forestiers. Le présent projet vise à faire l’inventaire de la dispersion des colonies de nerprun dans 3 bois de Laval afin de proposer des méthodes pour leur éradication, en prenant en compte les risques pour la faune, la flore indigène et les milieux avoisinants. Il s’agit donc de répertorier l’information pour élaborer un dispositif expérimental dans le but de créer un outil d’aide à la décision. Cet outil permettra de comprendre les différentes méthodes d’éradication du nerprun, facilitant ainsi les choix des gestionnaires des bois urbains à Laval.

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Faculty Supervisor:

Daniel Kneeshaw;Ira Tanya Handa

Student:

Partner:

CANOPÉE

Discipline:

Earth science

Sector:

Professional, scientific and technical services

University:

Université du Québec à Montréal

Program:

Accelerate

Modelling glacial overdeepenings and future lake locations for the western Canadian Cordillera

The Canadian Western Cordillera is a glaciated region within Canada which has seen significant glacial retreat due to recent climatic warming – estimated glacial volume reduction by 70% by 2100. As a result of this glacier retreat, depressions beneath are exposed (known as glacial overdeepenings) and lakes begin to form, dammed by the bedrock or deposited moraines. These can have important consequences both in terms of hazards and the possibility of economic benefits, including hydroelectric dams and a water resource. This research aims to predict where these glacial overdeepenings may occur under the present-day glacial ice in the British Columbia and Alberta glaciers. We will estimate the depth and volume of the potential lakes and understand how they will develop by using modern-day analogues, currently transitioning from a glaciated to deglaciated environment. This will aid future decision making of the local governments into water availability in an unpredictable climate.

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Faculty Supervisor:

Dan Shugar

Student:

Partner:

Newcastle University

Discipline:

Earth science

Sector:

Sustainability & the Environment; Water; Environmental Science and Technology

University:

University of Calgary

Program:

Globalink Research Award

Few-shot Generative Adversarial Networks

The most successful computer vision approaches are based on deep learning architectures, which typically require a large amount of labeled data. This can be impractical or expensive to acquire. Therefore, few-shot learning techniques were proposed to learn new concepts with just one or few annotated examples. However, unsupervised methods such as generative adversarial networks (GANs) still require a huge amount of data to be trained. As such, this project will focus on few-shot learning for GANs. This means that at inference time, the user can input a few images of a class never seen before by the model and the model can generate new images from that class. The proposed project will use a standard

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Faculty Supervisor:

Christopher Pal;Derek Nowrouzezahrai

Student:

Partner:

ServiceNow Canada

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

McGill University; Polytechnique Montréal

Program:

Accelerate

Biomarkers for detection of breast cancer and multiple myeloma using liquid biopsy – Year Two

Blood tests are highly sought after to enable earlier cancer detection. We previously developed a blood test for breast cancer that is in prospective clinical study in Alberta, Manchester (UK), Oklahoma (USA) and South Korea. The proposed project will investigate some clinical samples collected through this work to support the primarily focus of identifying biomarkers for a new cancer, multiple myeloma (MM). MM has a need for new monitoring approaches as it accounts for 10% of hematologic malignancies and is hard to cure, with a low five-year survival rate. MM is characterized by cancerous plasma cells in the bone marrow (BM). Invasive BM aspirates are the primary method of diagnosing the disease and following response to therapy. In this study, we will evaluate patient samples (BM and blood) to identify potential MM biomarkers, test a new cell culture model, and validate results in patient samples. These studies will allow partners to participate in publishing research study results, as well as potentially develop a new clinical laboratory tests for MM. This could enable earlier detection and provide a method to determine response to therapy, resulting in increased survival, as well as enhanced quality of life through optimizing treatment and monitoring recurrence.

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Faculty Supervisor:

Ernesta Paola Neri

Student:

Partner:

Syantra

Discipline:

Life Sciences

Sector:

Health and Related Sciences & Technology; Biotechnology; Other

University:

University of Calgary

Program:

Elevate

Biomarkers for detection of breast cancer and multiple myeloma using liquid biopsy

Blood tests are highly sought after to enable earlier cancer detection. We previously developed a blood test for breast cancer that is in prospective clinical study in Alberta, Manchester (UK), Oklahoma (USA) and South Korea. The proposed project will investigate some clinical samples collected through this work to support the primarily focus of identifying biomarkers for a new cancer, multiple myeloma (MM). MM has a need for new monitoring approaches as it accounts for 10% of hematologic malignancies and is hard to cure, with a low five-year survival rate. MM is characterized by cancerous plasma cells in the bone marrow (BM). Invasive BM aspirates are the primary method of diagnosing the disease and following response to therapy. In this study, we will evaluate patient samples (BM and blood) to identify potential MM biomarkers, test a new cell culture model, and validate results in patient samples. These studies will allow partners to participate in publishing research study results, as well as potentially develop a new clinical laboratory tests for MM. This could enable earlier detection and provide a method to determine response to therapy, resulting in increased survival, as well as enhanced quality of life through optimizing treatment and monitoring recurrence.

View Full Project Description
Faculty Supervisor:

Ernesta Paola Neri

Student:

Partner:

Syantra;University of Calgary

Discipline:

Life Sciences

Sector:

Health and Related Sciences & Technology; Biotechnology; Other

University:

University of Calgary

Program:

Elevate

Development of whole-heart model-based cardiac shape and motion analysis using parallel computing multi-core CPUs and GPUs technology

According to Statistics Canada, cardiovascular disease is the leading cause of death in Canada,
accounting for 72,338 or 32% of all Canadian deaths in 2004. To further reduce the mortality and
morbidity rate of heart disease, significant improvements in the extraction of the clinical heart
parameters, such as the change in shape and motion patterns have to be made, which are believed to
be useful for the early and reliable diagnosis of regional ischemia and dysfunctional contraction. The
accurate calculation of these parameters depends on an effective generating of 3D heart model,
which however, is a very computation demanding process. This project is designed to develop an
efficient implementation of spherical harmonic modeling algorithm by incorporating the combined,
parallel computing power of multi-core central processing units and graphics processing units, leading
to massive reductions in processing time and furthermore, to provide highly informative and accurate
parameters for clinical use.

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Faculty Supervisor:

Hung-Yu Lin

Student:

Partner:

MedVoxel

Discipline:

Life Sciences

Sector:

University:

University of Manitoba

Program:

Accelerate

Machine Learning-Assisted History Matching for Light and Tight Oil Reservoirs

The use of ionic liquids (ILs) in enhanced oil recovery is considered a new and promising technology as it has never been tested in any pilot plant or reservoir field. ILs are very similar to surfactants as they help reduce the interfacial tension, change the wettability of the reservoir, and some have strong viscous effect, all essential factors in recovering more heavy oil. The technology can also be used for medium and light oil recoveries with other kinds of ionic liquids. After an initial screening ILs will be selected taking into account stability in a basic environment, biodegradability and toxicity. The best ionic liquid will be used in a chemical enhanced oil recovery application where a weak alkali and a polymer are added to increase the recovery factor. ILs have the potential to be the most promising Chemical enhanced oil recovery (EOR) technology in the history of heavy oil production. The economic benefits to Saskatchewan and Canada could be extraordinary.

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Faculty Supervisor:

Mohamed Eldarieby;Ezeddin Shirif

Student:

Partner:

Petroleum Technology Research Centre

Discipline:

Engineering

Sector:

Mining; Professional, scientific and technical services

University:

University of Regina

Program:

Accelerate

Développement d’un indice de potentiel pour une localisation optimale des centres d’appels dans un contexte canadien

L’industrie des centres d’appels est en pleine mutation et, depuis les dernières années, ceux-ci se sont multipliés au Canada, tout comme dans le reste du monde. Alors qu’ils sont souvent vus comme des emplois routiniers et précaires, les emplois de centres d’appels sont, dans certains cas, devenus des emplois qualifiés. Ainsi, pour optimiser l’établissement d’un centre d’appels dans une ville, une entreprise doit désormais maîtriser la composition de la main-d’œuvre de cette même ville. Dans cette recherche, nous tenterons de saisir la localisation optimale d’un centre d’appels pour une compagnie d’assurance. Pour ce faire, nous proposerons un « indice de potentiel » basé sur des variables socioéconomiques dans une cinquantaine de villes canadiennes. Entre cinq et dix de ces villes seront sélectionnées selon leur potentialité. L’avantage pour l’organisme partenaire sera notamment de bénéficier des résultats de la recherche et de les intégrer dans la mise en place d’un centre d’appels.

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Faculty Supervisor:

Cédric Brunelle

Student:

Partner:

Co-operators (General Insurance)

Discipline:

Business

Sector:

Finance and Insurance; Commercial Services; Sustainability & the Environment

University:

Université du Québec : Institut national de la recherche scientifique

Program:

Accelerate

The correlation and validation of functional markers and biomarkers for m/sTBIpopulations during simple and complex tasks – Year 1

This project aims to develop and validate markers for adaptive neurological performance therapies for persons with moderate-to severe traumatic brain injury (m/sTBI), with the purpose to further develop clinical paradigms for at-risk populations. In order to accomplish this, we have formed a collaboration between two Universities (Université Laval and McGill University) and two industrial partners (BeamMeUp Inc. (BMU) and Saccade Analytics). This collaboration allows us to combine whole-body movement analysis with BMU’s brain activity measurements (EEG) and Saccade Analytics’ eye-tracking technologies. We will design a protocol in virtual reality and compare the above techniques in healthy and m/sTBI populations. To further elucidate differences between the two populations we will have a series of increasingly complex tasks: joystick navigation and over ground walking in an empty virtual environment, and avoiding virtual pedestrians with different emotional states. Such a task could be very difficult for m/sTBI populations, which have known difficulties in both navigation and recognizing emotions. The project will increase the capacity to deploy BMU’s and Saccade Analytics’ technologies in realistic free movement tasks while adapting to different stages of cognitive impairment. The combined collaboration will help elucidate emotion recognition deficits and validate diagnostic tools with improved bio- and functional markers.

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Faculty Supervisor:

Anouk Lamontagne;Bradford McFadyen

Student:

Partner:

Saccade Analytics;BeamMeUp Inc. - to merge

Discipline:

Life Sciences

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

McGill University

Program:

Elevate

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