Les syndromes d’hypercroissance sont un groupe de maladies rares caractérisées par une croissance excessive généralisée ou d’un membre. Dans la plupart des cas, ils sont liés à des anomalies génétiques affectant des gènes contrôlant le signal de croissance au sein des cellules (la voie de signalisation PI3K-AKT-mTOR). L’Alpelisib (autrement appelé Piqray®) est un médicament émergent. […]

Giardiasis is a foodborne and waterborne disease that affects people worldwide, and it causes enteric diseases with outbreaks of diarrhea in adults and children. There are a few drugs available for treating Giardia spp. infections and they are associated with low efficacy, adverse effects, and drug resistance is spreading. Hence, there is an urgent need […]

The lymphatic system serves an integral role in fluid homeostasis, lipid metabolism and immune control of the human body. Lipid based nano-carriers employing lymphatic voyage offer multitude of advantages like enhanced bioavailability, selective targeting to localized as well as metastatic conditions, controlled delivery and others. Lipid-based nano-carriers have been tested on various experimental various in-vivo, […]

Depression affects up to 20% of pregnancy. If left untreated, antenatal depression increases the risk of complicated pregnancy and abnormal fetal development. The selective serotonin reuptake inhibitors (SSRIs) are the most commonly used treatment method for perinatal depression, while the risk of the drug on the placental function and fetal development remains controversial. Iron deficiency […]

As the third documented emergence of an animal-to-human coronavirus during the past two decades (Severe Acute Respiratory Syndrome in 2002, Middle East Respiratory Syndrome in 2012), the current pandemic and near-certainty of future epidemics demands intensified surveillance and proactive screening. Definitive therapy for novel Coronavirus Disease 2019 (COVID-19) is likely at least half a year […]

Retinal diseases are the leading causes of blindness in Canada. Retinal diseases are currently treated by monthly or bimonthly intraocular injections of biologics. At the Sheardown lab, we are developing a new injectable hydrogel that can provide prolonged treatment for retinal diseases. Upon injection, the new treatment forms a transparent solid depot inside the eye […]

In this project, the interns will develop a new set of tools and techniques to provide new scientific insights into the detailed interactions that occur between drug and target molecules in the human body. Understanding of these interactions is critical to design better, more effective, and more precisely targeted drugs. The problem is that current […]

In response to the COVID-19 pandemic, hundreds of clinical trials are currently ongoing to evaluate the effectiveness of convalescent plasma derived from individuals who have recovered from COVID-19. As a licensed plasma collector for transfusible plasma and the National blood operator (outside Quebec), Canadian Blood Services has consequently taken on a unique role in several […]

The proposed project aims to assess the impact of Diclofenac on freshwater fauna. Current research work in this area will be beneficial to characterize potential risks from long term low-level exposure to pharmaceuticals like Diclofenac, particularly for sensitive aquatic organisms and hence, this project will attempt to evolve various measures for sustaining and safeguarding the […]

Using simplified language understandable to a layperson; provide a general, one-paragraph description of the proposed research project to be undertaken by the intern(s) as well as the expected benefit to the partner organization. {100 – 150 words) The project aims to develop a molecular compounds database to accelerate drug discovery. Compounds shared by chemical providers […]

Unsupervised machine learning has recently been introduced into the field of quantum many-body physics. A strategy based on generative models has been particularly successful in the data-driven learning of quantum states. In this proposal, we aim to adapt this technology to applications in quantum chemistry. The primary focus of this research will be on the […]

Unsupervised machine learning has recently been introduced into the field of quantum many-body physics. A strategy based on generative models has been particularly successful in the data-driven learning of quantum states. In this proposal, we aim to adapt this technology to applications in quantum chemistry. The primary focus of this research will be on the […]