Genes to affordable medicines - Stream 1-A2

The Structural Genomics Consortium (SGC) is a not-for-profit public-private partnership research organization that aims to accelerate the discovery of new medicines through open science. This Mitacs cluster will bring together SGC’s industry and academic collaborators to work together towards new and affordable medicines for challenging diseases. Sixty-three post-doctoral fellows will spend 2-3 years developing open source tools and knowledge for previously understudied proteins, thereby unlocking new areas of biology and identifying new opportunities for drug discovery.

New electrolyte design for Li-ion batteries based on metal-based anodes

Lithium-ion batteries (LIBs), as a promising method for energy storage, have been widely used in our daily lives, and the boosting development of electric vehicles and electronic devices requires LIBs with a higher operation voltage. However, their safety problems are always a threat because of the unstable Li salt and flammable organic solvents in the commercialized electrolytes.

Development of a Quantitative and Inexpensive Opioid Detector for Clinical Use

The opioid epidemic is a serious health crisis and opioid treatment strategies are at the forefront of efforts to tackle this crisis. Replacement therapy is the current approach taken using medications such as methadone. To be more effective, the dosage needs to be tailored to individual tolerance which requires a point-of-care type analytical measurement of the patient's existing opioid level.

Development of new methods for screening bioilogics by means of Capillary Electrophoresis (CE) coupled with Mass-Spectrometer (MS) via novel Open Port Probe Sampling Interface (OPP)

The methods for screening complex biological samples found wide application in pharmaceutics, forensic science and medical science. The majority of these methods involve several analytical techniques coupled together in order to maximize the efficiency of the analysis. For example, the combination of Capillary Electrophoresis (CE) with Mass Spectrometry (MS) creates a new analytical platform (CE-MS) that utilizes the separation power of CE and superior detection abilities of MS.

Bio-based Latexes using Switchable Hydrophilicity Solvent (SHS)

The proposal focuses on the design and synthesis of novel bio-based, biodegradable materials to be used in packaging and protective coatings (varnishes), and targeted at replacing the nonrenewable, non- biodegradable materials currently used to manufacture these products. Our new process allows us to obtain a desired combination of material properties, and also eliminates the need for using VOCs (Volatile Organic Compounds). We achieve this using a new type of solvent whose properties can be “switched” simply by introducing or removing CO2 into or from the mixture.

Next-Generation Coating Materials for Architectural Lighting

Architectural and decorative lighting have significant impacts on our daily lives, especially our moods and mental health. We propose to combine supramolecular chemistry and cellulose nanocrystal gels, two intriguing research field in chemistry and material sciences, in order to develop the next-generation coating materials for architectural lighting. Such gel materials have the ability to change color and pattern spontaneously over time, which can be programmed or customized.

Thin-film photocatalyst development for Solar-Driven GHG Conversion to Fuels

Solar-driven dry-reforming is an ideal solution for recycling greenhouse gasses (GHGs) while producing valuable chemical feedstock. These anthropogenic emissions of the GHGs are the leading cause of global climate change. Furthermore, these emissions are related to the manufacture of fuels and carbon-based products. Solar fuels technology addresses both of these issues. Solistra is developing photocatalyst technology in partnership with NRC, through the Materials for Clean Fuels Challenge program, and the University of Toronto’s Solar Fuels group.

Accelerating discovery through high-throughput experimentation and machine learning - Year two

Canonical methods of molecular discovery and reaction optimization rely on “trial-and-error” approaches and slow experimentation with low discovery rates. By harnessing high-throughput experimentation (HTE) with machine learning (ML) methods, artificial intelligence (AI) and robotics, we have the potential to dramatically accelerate the discovery and preparation of next generation molecules and materials. We will extract, unify, and transform data from literature into actionable intelligence, and generate a robust workflow for the automated synthesis of catalysts and resins at NOVA Chemicals.

Development of Pharmacological Probes for Road-Mapping WD40 Domain Proteins

Since the dawn of the human genome sequencing in 2003, great hopes have been put into the development of new therapeutics and personalized medicine tailored on individual DNA profiles. Nonetheless, progress in these fields has been slow, mainly due to the focus of the research community on only a small number of genes and proteins involved in diseases. As a result, there remains a plethora of unexplored proteins and genes responsible for diseases such as Alzheimer's, cancer, or rare/orphan diseases, that have yet to be understood.

Investigating the influence of metallic impurities on the properties of Cu coatings intended for used nuclear fuel containers

Canada’s use of nuclear power has led to an inventory of used fuel, which requires a strategy for safe, permanent containment. The current long-term disposal plan uses both natural and engineered barriers in a deep geological repository. A key engineered barrier in this concept is the used fuel container (UFC), made of copper-coated carbon steel. The Cu coating will be applied by two additive manufacturing techniques, electrodeposition (ED) and cold spray (CS) deposition.