Grants and Contributions

Designing a drug for a specific disease type is highly challenging due to tremendous molecular search space and limited understanding about the disease of interest. Successful discovery of a medicine for a target (gene/protein/pathway) usually last for many years and costs a private pharmaceutical organization billions of dollars, which in turn determines the unaffordable price of medicines in the Canadian and global markets. The emerging of massive biochemical and high-throughput genomic data acquisition techniques and the rise of advanced artificial intelligence paradigms provide an unprecedented opportunity for automatic design of new drugs with much faster pace and much lower cost, igniting hopes to discovery drugs for diseases where no medicines have been found yet. A develop a data- and AI-driven drug design platform/pipeline will be developed for precise and effective treatment of cancers and complex diseases. The project will take advantage of NRC’s unique multidisciplinary expertise in AI, data science, and human health therapeutics, as well as external collaborators’ knowledge and facilities, to tackle challenges in every step of drug design. Project technologies and outcomes will be disruptive and beneficial to all Canadians.
This project will focus on the development and testing of AI methods and molecule parameterization.

Reaching Home aims to prevent and reduce homelessness across Canada. This is accomplished by mobilizing partners at the federal, provincial/territorial and community levels, as well as the private and voluntary sectors, and other stakeholders, to address barriers to well-being faced by those who are homeless or at imminent risk of homelessness.

This will be accomplished in the following ways:
• Through partnership and joint management of distinctions based investments that will enhance and expand Indigenous ELCC, and support the transfer of ELCC to Indigenous organizations;
• Strengthening foundational supports for Indigenous ELCC through, for example, Indigenous led quality improvement projects; and
• Adapting and improving existing federal programs to be more flexible, adaptable and horizontal across federal departments as a first step prior to transferring control, so that programs cohesively support the goals of the Framework including supporting self determination.

A contribution to support the implementation of enhanced stormwater management controls that would improve water quality of downstream water bodies and mitigate flooding concerns.

It is well-known that asphalt pavements in cold regions such as Canada are exposed to number of environmental stresses such as thermal fatigue cycles and low-temperatures which result in different modes of distresses most commonly cracking. In addition, repeated application of traffic loads on flexible pavement induces structural cracking known as bottom-up fatigue distress. Considering that cracked pavements are more susceptible to water seepage and frost action, it is crucial to reverse the cracking process through use of self-healing bituminous materials in order to extend the service life of the infrastructure, reduce the amount of Greenhouse Gas emissions and decrease the energy usage. Improving the self-healing properties of asphalt binder and Hot Mix Asphalt (HMA) through innovative techniques and novel applications is still at emerging stage. This project will investigate the rheological properties and healing characterization of nano-clay modified asphalt binder and performance testing of HMA specimens containing nano-clay modified asphalt binder.

Silicon nitride is becoming established as an important nanophotonic platform because of its compatibility with CMOS fabrication and its substantially broader spectral transparency range compared to silicon. Silicon nitride allows CMOS integrated photonics to break into new application areas, in particular sensing in the visible and mid-IR spectral ranges, quantum photonics and nonlinear optics. However, silicon nitride poses some fundamental challenges. The high index contrast, which allows device miniaturization, causes significant optical scattering losses, mode size disparity between optical fiber and on-chip waveguides results in high coupling losses, and fabrication tolerances are tight, making manufacturing yield a major concern. Subwavelength engineering was successfully used to overcome similar challenges in silicon waveguides and the team believes that this strategy can also be advantageously implemented in the silicon nitride platform, which has not yet been done. In this proposed New Beginnings project, the benefits of subwavelength metamaterial engineering for the emerging nitride nanophotonic platform will be demonstrated. This can result in major advances in state-of-the-art silicon nitride integrated devices, including new photonic sensors, next generation quantum communications chips and on-chip optical amplifiers for telecom applications.

Many antibiotics are derived from natural products, small molecules made by organisms in the environment. In this project, high-throughput screening and chemical analysis will be used to isolate and identify novel natural products with unique activities against drug-resistant strains of E. coli. Using this approach, it is anticipated that a new classes of bioactive compounds will be identified that could form the foundation for future drug development.

Terahertz (THz) radiation is a form of electromagnetic energy that occupies a broad frequency band between 0.1 and 10 THz, and is non-ionizing. These frequencies coincide with natural dynamics of biological systems, including low-frequency vibrational modes of large molecules (e.g., all proteins, DNA) and the stretching/twisting modes of hydrogen bond networks that are ubiquitous in biological systems. This interaction mechanism is the basis behind existing novel THz diagnostic imaging technologies for which the high sensitivity to molecular/chemical structure provides excellent contrast between diseased and healthy tissue. However, exposure to higher levels of THz radiation can also affect the structure and function of target biomolecules. This project investigates these effects of intense terahertz radiation in proteins, cells, and skin tissue.

The Ultrafast Nanotools lab, houses the source of terahertz radiation and sample chambers that will be used to perform biological exposure studies. This is central to the proposed research, as sufficient radiation sources of the type required for these investigations are not commercially available. The state-of-the-art sources of intense terahertz pulses constructed for research purposes are known to be capable of generating peak electric fields and intensity distributions sufficient to induce significant non-thermal biological effect in target samples, as reported in several academic publications.

The project will examine the impact of solid state and submerged fermentation, and enzymatic modification on the functional and nutritional properties of commercial pulse (e.g., yellow pea, faba bean and lentil) protein concentrates or isolates. Fermentation of pulse fractions will be done using traditional GRAS strains, Aspergillus niger, A. oryzae, and Lactobacillus plantarum, under different fermentation conditions (pH, temperature and time) to obtain different levels of hydrolysis (5, 10, 15 and 20%). Similarly, proteases (Trypsin and Savinase) will be added to modify protein isolates under different conditions (enzyme: substrate ratios, temperatures, pH and times) to obtain similar levels of hydrolysis. Changes to the protein’s surface properties will be measured, along with their functionality (e.g., solubility, emulsifying, water/oil holding and foaming). Changes to levels of anti-nutritional compounds and protein quality (PDCAAS and digestibility) will also be examined as the result of processing.

Modern technological materials are typically multi-component compounds with complex structures that determine their opto/electronic/chemical properties. The design of new functional materials has been greatly assisted by developments in efficient and accurate electronic-structure methodologies, most notably Density Functional Theory (DFT). But DFT is too expensive to perform the rapid screening of thousands of candidates required for the design of new high-performance materials. This project aims to harness the power of modern Artificial Intelligence to build on the success of DFT and ferret out optimal design parameters. This project is of prime socioeconomic importance, aiming to reduce the environmental footprint of the Alberta oil sands by designing new nanocatalysts for the chemical reactions involved in in-the-reservoir upgrading.