Epigenetic Regulators of Anticancer Drug Response

The effectiveness of cancer drugs depends on several factors which are governed by the genetic and ‘epigenetic’ code of cancer cells. The epigenetic code comprises those heritable modifications that bookmark DNA and DNA-associated proteins to guide the expression of genetic attributes without changing the DNA sequence. This epigenetic code is written, read, and erased by a group of proteins known as epigenetic regulators.

Development of microneedle array patch for COVID-19 vaccine delivery

COVID-19 is a global pandemic with no effective therapeutic and preventive agents. Given the high infectivity of the SARS-CoV-2 and severity of the disease, vaccines are urgently needed to tackle the infection of this novel coronavirus. Thus far, various types of vaccine candidates, in different stages of preclinical testing and clinical trials, are being explored, including RNA- and DNA-based, vectored and attenuated virus, and recombinant proteins. However, possible adverse effects and limitations exist.

Perioperative Opioid Usage Quality Improvement [CDTS-PDF2]

Our aim is to use machine-learning to improve treatment of post-surgical pain in children and adults. Most people addicted to opioids were initially exposed through the treatment of pain from trauma and/or surgery. The opioid crisis is reaching the pediatric population, in whom effective post-surgical pain management, with less reliance on prescription of opioids, is more important than ever. Recent advances in machine-learning, combined with approaches to patient-oriented research, provide significant prospects for a learning health system.

Perioperative Opioid Usage Quality Improvement [CDTS-PDF1]

Our aim is to use machine-learning to improve treatment of post-surgical pain in children and adults. Most people addicted to opioids were initially exposed through the treatment of pain from trauma and/or surgery. The opioid crisis is reaching the pediatric population, in whom effective post-surgical pain management, with less reliance on prescription of opioids, is more important than ever. Recent advances in machine-learning, combined with approaches to patient-oriented research, provide significant prospects for a learning health system.

Next-Generation Precision Medicine Solutions – Diagnostics

As personalized medicine approaches aim to tailor treatments to individuals, improvements are needed in the detection of existing biomarkers and genomic, epigenomic, and proteomic changes that occur during disease development. This would have potential impact on medication selection and targeted therapy, reduce adverse effects, improve cost effectiveness, and shift the goal of medicine from reactive to preventative clinical decision making1.

Application of multi-omics and pharmacological studies to discover potential new therapeutics for COVID-19

COVID-19 is the largest pandemic of the 21st century, affecting over 6.6 million individuals and claiming over 391,000 lives worldwide as of June 4, 2020. It is caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV2), which uses a receptor to gain entry into the host and cause active infection. This project involves the expertise of PROOF Centre and Professors Don Sin and Pascal Bernatchez.

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.

Development of a Product to Prevent Binding of SARS-COV-2 within the Respiratory Airway and Cardiovascular System

The SARS beta coronaviruses, SARS-CoV, which caused the SARS (Severe Acute Respiratory Syndrome) outbreak in 2003 and the new SARS-CoV-2, which causes COVID-19, bind to angiotensin converting enzyme 2 (ACE2) receptors in the lower respiratory tracts of infected patients to gain entry into the lungs. Viral pneumonia and potentially fatal respiratory failure may result in susceptible persons after 10-14 days. Our proposed product will bind to SARS-COV-2 and reduce the opportunity for it to enter the body.

Develop a web based geospatial artificial intelligence framework to track, visualize, analyze, model, and predict infectious disease spread in real-time.

As location is an integral part of both population and individual health, there is an emerging role for geospatial artificial intelligence (GeoAI) technology in health and healthcare. Novel infectious diseases such as COVID-19 are associated with population density, environmental factors, and interactions between humans and wildlife. GeoAI technology can be used to collect and analyze large amounts of spatial data, such as individual-level epidemiological data, social media, human mobility, transportation, mobile phone data, and vulnerable populations.

Hybrid bacteriophage platforms for the production of non-invasive, self-adjuvanted, and targeted DNA vaccines against SARS-CoV-2

Our project aims to design and develop COVID19 vaccines engineered from viruses that infect bacterial cells only. SARS-CoV2 pathogenic components have been identified and modified to develop the vaccine. Although these components are pathogenic in nature, they are modified to pose no harm. The vaccine is designed to be administered intranasally, where it relocates to the lower respiratory tract. Upon reaching respiratory cells, the vaccine binds to respiratory cells and delivers the carried component. The delivered component will self-assemble into a SARS-CoV2 shape mimic.

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