Innovations Realized

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

13270 Completed Projects

1072
AB
2795
BC
430
MB
106
NF
348
SK
4184
ON
2671
QC
43
PE
209
NB
474
NS

Projects by Category

10%
Computer science
9%
Engineering
1%
Engineering - biomedical
4%
Engineering - chemical / biological

An efficient heuristic algorithm for laboratory analysis profile selection

In health care industry, the tests of laboratory analysis are organized and priced in the format of profiles. Each profile contains a specific group of tests. The price of a profile is usually lower than the sum of the prices of individual tests included in the profile. In this project, the intern will develop a special optimization algorithm for selecting test profiles and/or combinations of test profiles to cover the list of tests required by a patient. This is an important component to enable an online price estimation service provided by Medialpha. The service automatically calculates the price for conducting a set of lab analysis prescribed by a doctor. The service will intuitively guide patients through the price estimation process and intelligently help patients match non-standardized test abbreviations and codes in their requisition forms with the laboratory’s standard ontology. To achieve this objective, the intern will develop software interfaces which integrated the developed optimization algorithm with Medialpha’s existing Price Estimator modules. The superb user experience and time-saving benefits provided by the online price estimation system will attract more patients to obtain their laboratory analysis quotations through the online service.

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Faculty Supervisor:

Chun Wang

Student:

Xinkai Xu

Partner:

Medialpha

Discipline:

Engineering

Sector:

Health care and social assistance

University:

Concordia University

Program:

Accelerate

Examining Water Quality Parameter Testing Processes at Ontario Public Pools and Spas: Opportunities and Barriers

This research project aims to explore the experiences of public pool and spa staff in meeting the regulatory requirements for water parameter testing and understand user behaviours, needs, and attitudes towards pool and spa water testing equipment. Two groups of interest are Public Health Inspectors (PHIs) who are mandated to conduct inspections at public pools and spas and public pool and spa staff. The regulatory changes made in 2018 require pool and spa operators to test water chemistry parameters on a more frequent basis. Knowledge and user comfort when utilizing the water testing equipment are vital in maintaining the pool and spa in a sanitary manner. The research project utilizes a mixed-methods approach using surveys and focus group discussions with PHIs and pool and spa staff in southwestern Ontario.

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Faculty Supervisor:

Fatih Sekercioglu

Student:

Jessica Castellucci

Partner:

Lowry and Associates

Discipline:

Environmental sciences

Sector:

Other

University:

Ryerson University

Program:

Accelerate

Generating a COVID-19 vaccine using ministring DNA and virus-like particles

The COVID-19 pandemic is a global health crisis on an unprecedented scale, with over 1 million confirmed cases, spread over 200 countries. With the world at a virtual standstill, and no existing treatments, there is an enormous need for novel therapeutics and vaccines to combat COVID-19. Our group is working on a DNA vaccine strategy that exploits our proprietary miniaturized DNA vector technology, called ministring DNA (msDNA), to encode and deliver specially engineered copies of COVID-19 viral proteins. Once delivered into human host cells, these proteins will be designed to self-assemble into viral-like particles (VLPs). VLPs are safe, generate a strong host immune response, and have a record of commercial success as vaccine products. We are confident that our strategy will lead to the development of an effective COVID-19 DNA vaccine.

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Faculty Supervisor:

Roderick Slavcev;Marc Aucoin;Mahla Poudineh;Shawn Wettig;Andrew Doxey

Student:

Ko Currie;Shifa Javed;Gurmeet Lall;Jennifer Aguiar

Partner:

Mediphage Bioceuticals Inc

Discipline:

Biology

Sector:

University:

University of Waterloo

Program:

Accelerate

Radiation Mapping from Aerial Data

The proposed project is focused on the development of software for accurate mapping of radiation levels on the ground using aircraft or unmanned aerial vehicles (UAV) for data collection. The problem of accurate radiation mapping is crucial for handling emergency radiological incidents (e.g., on nuclear plants), monitoring national borders, operating nuclear mine sites, etc. The goal of this project is to develop a new algorithm that improves on existing methods for airborne radiation mapping with more sophisticated models and to implement the new algorithm in a software package able to build contour maps of radiation levels, possibly identify radioactive elements, and prepare the output data for use in augmented reality systems. This developed algorithm and software developed during this project will be used by the partner organization, Environmental Instruments Canada, in their UAV sensor package in order to enhance its capabilities and make it a more compelling product.

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Faculty Supervisor:

Raymond Spiteri;Andrei Smolyakov

Student:

Oleksandr Chapurin

Partner:

Environmental Instruments Canada Inc.

Discipline:

Engineering

Sector:

University:

University of Saskatchewan

Program:

Accelerate

UVPD of DMS-MS-selected SARS-CoV-2 peptides

Differential mobility spectrometry (DMS) is a technique that is used for the analysis of chemicals by separating complex gaseous mixtures under the influence of an electric field. It is a widely used technique and is successfully deployed in many areas, including drug and explosives testing at airports. In analytical laboratories, it can be used to separate peptides – the components that make up proteins and viruses. However, analysis of data from these experiments can be ambiguous and difficult to interpret. We propose to eliminate that ambiguity by simultaneously measuring those chemicals’ response to UV light after they are separated by using DMS. Their response will help us to identify peptides directly, based on their unique interaction with light.

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Faculty Supervisor:

William Scott Hopkins

Student:

Yuting Li;Arthur Lee

Partner:

Sciex

Discipline:

Chemistry

Sector:

University:

University of Waterloo

Program:

Accelerate

Using semi-supervised learning for classification of sport images

Artificial intelligence (AI) is rapidly becoming one of the most critical aspects in both business and science, and an increasing number of leading technology companies in Canada are at the forefront of AI development and innovation. The proposed research project aims at developing AI algorithms that have the ability to accurately classify the sport practiced or the sporting equipment present in an image. This project is broadly in line with the AI Strategy by the federal government to make Canada a global AI research powerhouse, and seeks to develop automated image classification models that will help increase the visibility and competitiveness of Décathlon Canada, a worldwide leading company in the sports market.

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Faculty Supervisor:

Abdessamad Ben Hamza

Student:

Hasib Zunair

Partner:

Décathlon Canada

Discipline:

Engineering

Sector:

Service industry

University:

Concordia University

Program:

Accelerate

Post discharge after surgery Virtual Care with Remote Automated Monitoring technology (PVC-RAM) Trial

Patients discharged after undergoing non-elective (i.e., semi-urgent, urgent, or emergency) surgeries are at substantial risk, in the 30 days following surgery, of hospital re-admissions and presentation to emergency departments or urgent-care centres. The use of virtual care with remote automated monitoring (RAM) technology to monitor patients from their homes after surgery has the potential to prevent hospital readmission and the need for urgent or emergent care. This is particularly important during the COVID-19 pandemic to prevent transmission and keep needed hospital beds available for individuals with COVID19.
The Post discharge after surgery Virtual Care with Remote Automated Monitoring technology (PVC-RAM) trial aims to determine the effect of virtual care provided via a shared care approach with remote automated patient monitoring on the risk of acute-hospital care after discharge, as well as on several other post-discharge outcomes including COVID-19 infection at 30 days and 6 months after randomization.

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Faculty Supervisor:

Michael McGillion;P.J. Devereaux

Student:

Carley Ouellette;Marissa Bird;Sandra Ofori

Partner:

Cloud DX

Discipline:

Nursing

Sector:

Manufacturing

University:

McMaster University

Program:

Accelerate

The Epidemiology of Fabry Disease and Metabolic Acidosis in Manitoba – Year Two

The proposed project is for the postdoctoral fellow to access healthcare data for individual adults in the province of Manitoba in order to: 1) determine the rates of metabolic acidosis in Manitoba along with associated outcomes and risk factor profiles and 2) identify patients in Manitoba who are at high risk of Fabry disease but currently undiagnosed in order to facilitate disease screening and improve patient care. The postdoctoral fellow will use their statistical and programming expertise to link various datasets of physician visits, hospitalizations, laboratory results and drug prescriptions via a scrambled patient health number that is tied to a unique patient but unidentifiable to any researcher so to protect privacy. The postdoctoral fellow will conduct statistical analyses and then will compile their results into several reports complete with text, tables and figures to be presented to our clients. They will also create manuscripts based on their reports that will be suitable for publication in an academic medical journal. This project will help the partner (CDIC) understand the epidemiology of important chronic diseases, provide synergies with ongoing clinical trials conducted at CDIC, and will help establish CDIC as a capable research partner within the pharmaceutical industry.

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Faculty Supervisor:

Paul Komenda

Student:

Mohammad Nourohammadi

Partner:

Seven Oaks Chronic Disease Innovation Centre Inc

Discipline:

Epidemiology / Public health and policy

Sector:

University:

University of Manitoba

Program:

Elevate

In-line Method Development for Vaccine Production

The safety and quality of vaccine products are an integral requirement for all vaccine manufacturing and production. Most current tests are using laboratory equipment that requires trained personnel, equipment qualification, method validation, manual sampling, and testing at various stages of product manufacturing. However, the off-line testing is slow, often requires significant volume of material for testing and requires extensive maintenance and upkeep of many different analytical instruments. This is both expensive and time consuming. On the other hand, Process Analytical Technology (PAT) provides fast turnaround time without the need for sampling, allowing manufacturing scientists opportunity to make real-time decisions to better ensure quality and consistency in product manufacturing. Furthermore, PAT provides a much faster vehicle for analytical assessment of manufacturing processes during product development, such as fermentation monitoring or protein purification.

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Faculty Supervisor:

Yi Sheng

Student:

Gabriella Gerzon

Partner:

Sanofi Pasteur

Discipline:

Biology

Sector:

University:

York University

Program:

Accelerate

Peptide-Functionalized Graphene Oxide Nanocarrier for Targeting Drug Delivery and Cancer Treatment

Carbon Upcycling Technologies Inc. is a technological research and development company in Calgary. They chemically adsorb carbon dioxide emissions into carbon-based materials, such as graphitic nanoplates and graphene oxide, and they commercialized the technology. Recently, extending graphene-based materials into drug delivery applications is attracted their attention. However, specific targeting and intracellular trafficking are the most important requirements in a well-performed drug delivery systems. Targeting molecules have to be attached to graphene-based materials. In this proposed project, graphene oxide will be combined with systematically designed peptide molecules to form a platform. The model drug doxorubicin will be loaded on the graphene surfaces by – stacking and the designed peptide in the platform is for targeting lung cancer cells. The interaction mechanism between the doxorubicin and graphene oxide with the controlled release of doxorubicin will be studied. Then the platform with doxorubicin will be tested in an in vitro and in vivo environment for potential efficient uptake and anti-tumor activity. With Carbon Upcycling Technologies Inc., there are significant opportunities to build an effective graphene-based drug delivery system for the potential of targeted cancer chemotherapy.

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Faculty Supervisor:

Pu Chen

Student:

Lei Zhang

Partner:

Carbon Upcycling Technologies

Discipline:

Engineering - chemical / biological

Sector:

University:

University of Waterloo

Program:

Elevate

Controlling the Recoil of .50 Calibre Sniper Rifle

A novel approach is taken to reduce vibration through the design of a passive smart device with the use of magnetic actuators. In the proposed device, magnets are arranged in a particular alignment, so as to attenuate the resulting vibrations from the explosion at the moment of firing. The device has shown to be effective while maintaining a low mass (expected to be approximately ~150 grams), which is a relatively lightweight device for the desired purpose.

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Faculty Supervisor:

Hadi Mohammadi

Student:

HanChuan Wang

Partner:

Steadiwear Inc

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Program:

Accelerate

A Pilot Study: Integration of the skills of New Canadian farmers to improve functional food production and secondary product development in the agriculture sector in Newfoundland and Labrador

In the first year of this 2-year research project, we propose placing former refugee farmers with the requisite secondary processing skills on a farm in Newfoundland and Labrador to conduct research in order to diversify their production, as well as to increase their secondary product output. The second part of this project involves research of value-added food products that will be tested for the Association for New Canadians’ (ANC) on-site in their test kitchen which provides former refugees including former refugee farmers, with an outlet to prepare and sell traditional foods for the local market. We propose achieving this by placing a post-doctoral fellow with secondary production and food analysis expertise to work with former refugee farmers to improve the quality of the products that are being produced for the traditional and functional foods market

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Faculty Supervisor:

Raymond Thomas;Mumtaz Cheema

Student:

Ibrahim M Abu-Reidah

Partner:

Association for New Canadians

Discipline:

Environmental sciences

Sector:

Other services (except public administration)

University:

Memorial University of Newfoundland

Program:

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