Evaluating the Co-Translational Framework for systematic translation of scientific knowledge towards implementation

The University of Toronto’s Translational Research Program (TRP) is a graduate program that developed the Co-Translational Framework (CTF) to systematically mobilize research towards innovations to improve health outcomes.
The Translational Research for Innovation initiative is the research mechanism to help validate the CTF to facilitate meaningful collaboration between industry and academia.

Optimization of Angiotensin II Receptor type 1 Blockers (ARBs) in chronic obstructive pulmonary disease (COPD)

Chronic Obstructive Pulmonary Diseases (COPD) is a lung disease that cause a lot of suffering to the Canadian population. To accelerate the drug discovery process, an old blood pressure lowering medication was tested to block the progression of COPD. A patient study showed that the old medication did provide some protective effect to the lung airways of COPD patients. However, we have found that this old medication does not slow down COPD by lowering blood pressure, but rather by acting on a new, unknown target.

Improving the properties of active pharmaceutical ingredients by polymorph, salt and cocrystal screening

Solids exist as crystals, amorphous or subcooled liquids. The degree of crystallinity determines the long range order in a solid phase. Molecules when transferred from the solution to the solid phase may take many different crystal forms (polymorphs, solvates/hydrates, salts, co-crystals). Theoretically, there are 230 space groups describing the diversity of a crystalline material. About two thirds of pharmaceutical small molecules exist in more than one polymorphic solid form. Crystallization of polymorphs still has a touch of art.

A comparative analysis of glycan variation and its effects on therapeutic protein function

There are many exciting therapeutic applications for proteins. Many diseases are caused by faulty enzymes, which can sometimes be replaced. Antibodies and antibody-like molecules are being developed to specifically target cancers and other diseases. However, in order to administer these products, they must be made in a way that has minimal effect on the patient’s immune system. To make them viable commercially, they also have to be made in a robust, cost-effective process.

Advanced differential mobility mass spectrometry with electron capture dissociation for the characterization of therapeutic proteins - Year two

Many new pharmaceuticals are based on large biomolecules like proteins. Even small differences in the protein structure can cause significant changes in the efficacy and safety of these drugs. Furthermore, these large molecules are difficult to characterize without advanced instrumentation and methods. Current technologies still struggle with robustness and reproducibility. This study aims to introduce new technology to improve the reliability of protein pharmaceutical characterization.

Development of new classes of bio-relevant linkers for PROTACs and other conjugates using new technologies - Year two

Les PROTACs sont de nouvelles molécules thérapeutiques ayant pour but de soigner certaines maladies grave comme les cancers. Ces composés sont des molécules linéaires constitués de trois composants principaux : une extrémité permettant de repérer la cible, une autre extrémité permettant de causer la dégradation de cette cible, et enfin un linker reliant les deux. Cette dernière partie est la moins étudié, bien qu’il ait récemment été prouvé qu’elle joue grandement sur les propriétés de la molécule finale.

Investigating the Paradoxical Adoption of Blockchain in Healthcare Data Sharing: The Patterns, Consequences and Mediating Mechanisms of Challenging yet Succumbing to Incumbents

In this Mitacs project, we examine how nascent technology advocators can successfully implement the technology in highly institutionalized settings. Using the implementation of Blockchain in healthcare data sharing as an example, we compare and contrast the implementation strategies of 6-8 start-ups or divisions of established companies, and examine how the different types of implementation strategies lead to different implementation outcomes. Based on this research, BI will learn about the key advocators of Blockchain for healthcare data sharing, their strategies and performance.

Full characterization of Drug-Drug interactions using deep learning methods

Better understanding Drug-Drug interactions (DDIs) is crucial for planning therapies and drugs co-administration. While, considerable efforts are spent in labor-intensive in vivo experiments and time-consuming clinical trials, understanding the pharmacological implications and adverse side-effects for some drug combinations is challenging. The majority of interactions remains undetected until therapies are prescribed to patients. We propose to use computational tools for predicting interactions in order to reduce experimental costs and improve safety.

In Vitro Screening and Validation of Phyto-Cannabinoids in Glaucoma

Glaucoma is the second leading cause of blindness in the world, mainly induced by increased pressure in the eye. Marijuana has been shown to reduce such pressure, thus benefit glaucoma patients. In this project, we test several components from marijuana extracts that are unlikely to cause psychoactive symptoms, for their therapeutic effects on glaucoma. This project is likely to be the solid base of a future drug that could help lots of glaucoma patients and meet the need of the market.

Splicing alterations: from pathogenic variant discovery to next generation therapeutics development

Many human genetic diseases are associated with defects in post-transcriptional gene regulation and alternative splicing. Despite rapid technological advancements, successful diagnostic rates for rare genetic disorders are still low and clinical interventions and treatments unavailable for most patients. This project aims to address this challenge by developing novel antisense RNA therapies based on the splice-switching oligonucleotide (SSO) technology. SSOs allow correcting aberrant transcript splicing by targeting disease mutations at the transcript level.

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