Evaluating extended-release injectable buprenorphine in a Canadian setting

Canada is in the midst of an opioid epidemic. Although oral opioid agonist therapies (OAT) are effective for the treatment of opioid use disorder (OUD), a number of barriers pose a significant challenge to treatment initiation and retention. In 2018, Health Canada approved a new medication for OUD, a once-monthly injection, which may be able to address challenges related to medication adherence. The current project aims to support a larger observational study that assess the feasibility, efficacy, and safety of this new treatment option.

External validation and updating of prognostic models to identify hospitalized children at highest risk of in-hospital mortality in low-resource settings

Most child deaths occur in poorer countries where children who seek care at a hospital die soon after arrival. The majority of these deaths are from severe infections. Simple treatments for severe infections are available but need to be administered quickly. However, it can be difficult to identify which children are most at risk of dying from a severe infection. Risk prediction models can help frontline health workers with identifying very ill children and support decisions about treatments or referrals to higher levels of care. This can lead to faster treatment and save lives.

Oculomotor function in adults with concussion: A synthesis of evidence and clinical trial

Concussions are a frequently occurring injury with diverse clinical manifestations and an often-challenging recovery. Oculomotor deficits are commonly occurring in persons with concussion, both as an early symptoms and impairment long after the injury. Early assessment and rehabilitation of oculomotor deficits resulting from concussion have the potential to expedite recovery and improve affected individuals’ functioning. One novel and promising technology to assess and provide individualized treatment is using virtual reality technology.

Genes to affordable medicines - Stream 1-B1

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.

The importance of brand identity: Researching and developing a comprehensive design language and adaptable visual components

Today, there is an abundance of stakeholder engagement and data visualization platforms. However, they are overwhelming to use, and the data is not easy to interpret. To explore how new methods of visual design and data visualization, Veras Technologies Inc. will work with intern Divine Okonkwo to research, design, and test a comprehensive design language, adaptable visual components, and a interactive data visualization system. The intern will test the data visualization system with internally company data and publicly available population statistics.

Artificial Intelligence for Lung Scintigraphy and Pulmonary Embolism

Ventilation-perfusion (V/Q) scintigraphy has a major role to play in the diagnosis of pulmonary embolism (PE). Objective criteria exist for diagnosing PE on both V/Q planar and SPECT; however, reporting physicians ultimately incorporate their own subjective judgement into a final diagnosis. Therefore, this imaging modality is a promising candidate for standardizing and automating image interpretation with artificial intelligence (AI). Early studies from the 1990s and early 2000s with this aim report promising results but now rely on outdated machine learning techniques.

Natural products in bronchial asthma

Asthma is a chronic inflammatory disease that affects the airways in the lungs. The inner lining (epithelium) of the airways forms a protective barrier against harmful irritants. This lining is frequently injured but repairs itself quickly. In asthma, however, this barrier is dysfunctional and cannot repair itself when injured. This allows irritants into the airway tissue and initiates an inflammatory response. As the lining cannot repair itself properly, chronic inflammation develops. Natural products have been proposed as useful in treating asthma, however, they are not always safe.

Using food based AI to assess nutritional intake in adults with catabolism prone chronic diseases

There are many challenges with assessing accurate food intake data from research participants. Food image analysis is being recognized as a potential tool to make the assessment of food intake data easier for patients and dietitians who assess the data. There remain several gaps about how this data can be used in research with participants with chronic diseases. Several of these gaps will be addressed as part of this research project. First, the Intern will assess the accuracy of the food image analysis data against a gold-standard reference measure.

The effect of personal mask choices in patients with OSA: a randomized controlled trial

Apnea is a common sleep disorder in which people's breathing repeatedly stops and starts while they're asleep. This is often treated with CPAP (Continuous Positive Airway Pressure) therapy; masks that help patients breathe better. However, these masks are not always worn by patients suffering from apnea due to, among other reasons, discomfort with the mask. Studies have shown that an individualized care approach has the opportunity to improve this issue.

Understanding diverse COVID-19 outcomes at the cellular and molecular level

Approximately 40% of COVID-19 survivors experience the Post-Acute Sequelae of COVID-19 (LONG-COVID-19) or Long COVID. It is currently not possible to predict who will become long-haulers and continue to experience symptoms that last for weeks or even months. The goal of this project is to better understand the molecular underpinnings of diverse patient outcomes in COVID-19 and develop molecular diagnostics that can identify specific patient groups for targeted management, improving patient care and allocation of scarce resources to those who need them most.

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