We are developing a library/biobank of in vitro 3D bioprinted living tumor models to accelerate cancer drug development and bridge the translational gap. By incorporating human cells into organ-specific proprietary 3D bioprintable hydrogels we replicate the biochemical and physical properties of the tumor microenvironment with a high degree of complexity using only bio-derived materials. By […]

Nextdriv is a user-friendly platform that helps fleet operators plan and manage the switch to electric vehicles. By using smart tools and data analysis, it makes it easier to choose the right vehicles, optimise daily operations, and even take advantage of energy market opportunities. For our partner organisation, this means a smoother, more cost-effective transition […]

Nature is experiencing an ever-changing world where dramatic environmental changes require species to adapt rapidly to new conditions. As a result, understanding when species can rapidly adapt and persist has become crucial to ensuring the preservation of vulnerable populations such as freshwater ecosystems. The current project addresses our limited understanding of the parallelism of adaptation […]

This MITACS Globalink Award research proposal aims to engineer and characterize biomimetic dense collagenous gels as in vitro models for studying breast cancer metastasis to bone. At McGill, we have advanced the Gel Aspiration-Ejection (GAE) technique, a robust and simple method to create 3D anisotropic, cellular dense collagen (DC) gels. By applying negative pressure, collagen […]

The wind energy industry is good for the environment, but one aspect is not: lack of recycling of fiberglass from end-of-life wind turbine blades. This projects develops an important step in the recycling process being promoted by FibeCycle. Sorted of recycled fiberglass from the blades is a difficult process that must be performed carefully in […]

The objective of this project is to develop a proof-of-concept of a formable polymer in the shape of a customizable inset for an earphone. The material should be relatively inexpensive, take shape rapidly (within a few seconds optimally) and ultimately provide consumers with a customized earphone that will fit the vast majority of the population. […]

The proposed project will help in the development of a new revolutionary product. Its focus will be the design and development of a customizable in-ear earphone sleeve (ear bud/body of earphone). The designed sleeve will be initially flexible and adapt to the human ear contour once plugged into the ear. Later, the sleeve will take […]

Metallic parts are used in combination with oil or grease in many applicaitons, for example in car engines or hinges. To re-use them, the surface of the metal needs to be cleaned. Current technology makes use of solvents to remove the contamination. Although very effective, this method is polluting. Our industry partner (Walter Surface Technologies) […]

Modern synthetic chemistry, and in effect the production of pharmaceuticals and agrochemicals, still relies heavily on molecular transformations that inherently generate metal waste. In the CJ Li lab at McGill, we developed a “hydrazone” strategy that does the same transformation while generating only benign by-products (nitrogen and water). To expand the utility of this technology, […]

Saltmarshes, meadows flooded by marine waters, are recognized as one of the world’s most effective ecosystems for sequestering carbon dioxide from the atmosphere and storing it in the soil, thus helping to mitigate climate warming. These marshes also are negligible sources or even sinks for the potent greenhouse gases, methane and nitrous oxide. Through our […]

There is a growing awareness of the role of microbes in the functioning of higher organisms. The human microbiome has now been shown to play key roles in health and physiology. Similarly, plants have had microbes, mycorrhizal fungi for example, associated with their roots since they colonized the land. It is becoming clear that there […]

This project uses machine learning algorithms to better understand back movement and low back pain. We apply supervised learning time series algorithms to data collected from Backtracks’ wearable de-vice — which consists of a malleable think curve that reads data collected from the participants’ spine movements. At each time step, such movements are represented as […]