Harnessing Technological Advances to Re-engineer Polymer Particles for Drug Delivery

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The COVID-19 pandemic has challenged the operations of scientific laboratories around the globe. Ironically, at the same time it is science and medicine that are leading us out of this pandemic. In fact, advanced pharmaceutical formulation is amongst the key areas that have played a critical role in the fight against COVID-19. The two clinically approved mRNA vaccines are reliant on formulation in lipid-based nanoparticles. This success has brought renewed interest in lipid and polymer particle-based formulation strategies. Pharmaceutical formulation involves combining drugs with inactive materials to produce products with desirable properties. Through formulation, pharmaceutical scientists can engineer important properties of new medicines, such as reduced side effects and improved therapeutic efficacy. Polymers are materials that can be used for drug formulation. Polymers bring unparalleled diversity owing to the ability to synthesize innovative materials. Yet, to date the potential of polymer-based nano and microparticles for applications in drug formulation has not been fully exploited. This is in part due to the fact that there are a wide range of polymer properties and manufacturing parameters that must be considered in the development of nano or microparticle-based drug formulations. Further, the design - build - test loop associated with nano and microparticle development is largely reliant on hands on experimentation. Thus, full consideration of the impact of each polymer property or manufacturing parameter, and their combinations, on the characteristics and performance of drug formulations has been near to impossible to fully explore. The goal of the proposed research program is to capitalize on recent technological advancements in artificial intelligence, machine learning, microfluidics and experimental automation to pursue data driven development pathways for polymeric nano and microparticle-based drug formulations. Over the past decade AI has enabled ground-breaking advances in the pharmaceutical and healthcare sectors, including improvements in drug discovery and cancer diagnosis. Machine learning is a branch of artificial intelligence, that enables computers to learn tasks without the need to be explicitly programmed. The proposed research aims to harness this technology to enable faster and cheaper design of more effective medicines for the treatment of chronic diseases with a high prevalence in women, including ovarian and breast cancer, osteoarthritis, and dementia. This research builds on areas of research strength and recent economic investment in Canada, namely, artificial intelligence and machine learning, manufacturing, and the biotech/pharmaceutical industry. As a result, this program will provide trainees with the knowledge and interdisciplinary skills necessary to secure leadership positions at the intersection between these growing industry sectors.