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As one of today鈥檚 recipients of a Natural Sciences and Engineering Research Council of Canada (NSERC) grant worth $1.65 million over six years, 91亚色鈥檚 Distinguished Research Professor will lead a team of researchers and industrial leaders in training the next generation of technologically advanced graduates.

Master鈥檚 and PhD students will graduate from 91亚色 with the technical and managerial skills to take on leading positions in new entities to capitalize on disruptive technologies that could impact Canada鈥檚 research and development in the pharmaceutical industry.

鈥淭his grant will help train our students to become highly qualified personnel ready to meet difficult scientific and engineering challenges, while also helping to drive and support pharmaceutical drug discovery and vaccine development in Canada,鈥� says 91亚色 Vice-President Research and Innovation Amir Asif. 鈥淭his NSERC CREATE program taps into 91亚色鈥檚 expertise in bioanalytical methods and instrumentation and the University鈥檚 commitment to purposeful research. I congratulate Sergey Krylov on his successful application and collaboration.鈥�

NSERC announced the winners of the CREATE program earlier today designed to give Canada鈥檚 researchers of tomorrow, not only improved mentoring, but a better training environment.

The NSERC-funded industrial stream Technology-Enhance Pharmaceutical Discovery (TEPD) program at 91亚色, designed with industry input, will bring together some of Canada鈥檚 leading academics working on technological aspects of pharmaceutical discovery along with major companies driving or supporting this country鈥檚 pharmaceutical research and development.

鈥淏ig pharma is continually shifting tremendous costs and risks associated with pharmaceutical discovery to small-venture players, changing the landscape of pharmaceutical discovery in Canada,鈥� says Krylov of the Faculty of Science. 鈥淭he pressing needs of Canadian pharmaceutical research and development were what motivated our academic and industrial team members to come together to create a comprehensive training ecosystem capable of making a difference in this industry at the national level.鈥�

The goal of this program is to enhance Canada鈥檚 global economic competitiveness by fueling innovation in the pharmaceutical industry, a sector of the economy which creates more research and development jobs in Canada than any other industry.

Trainees will conduct collaborative research in one of the seven pharmaceutical-discovery research themes, like the stages involved in pharmaceutical discovery used by developers of drugs, biologicals and vaccines. They will work with leading-edge technologies that could lead to potential drug discovery and vaccine development through the design and synthesis of DNA-encoded libraries (DELs), the selection of hits from DELs and their validation.

The program is comprised of collaborative research, joint seminars, summer school with hands-on and in-classroom workshops run by instructors from academia and industry to advance soft and professional skills of the trainees, summer research conferences and industrial internships in the research and development labs of the four industrial partners in Canada or the United States.

Students will graduate with superior industrial and academic research expertise, ready to meet the scientific and engineering challenges of Canada's new research landscape.

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Throughout the COVID-19 pandemic, Faculty of Science mathematics and statistics Professor Jianhong Wu has been working non-stop with both federal and provincial agencies and a National Modelling Task Force to project the spread of the disease and its variants throughout the country 鈥� a testament to both his expertise and 91亚色鈥檚 leadership in mathematical modelling.

Wu, a Distinguished Research Professor at 91亚色, is one of Canada鈥檚 most prolific researchers for publications in COVID-19 and mathematical modelling and joins several other 91亚色 faculty members who helped lead the way with research in the area (SciVal, 2021).

It鈥檚 nothing new to Wu, who is . He was tasked in 2003 with leading a national network of mathematicians and researchers to model the path of SARS-1. In 2020, the Fields Institute asked him to organize a national modelling Task Force for COVID-19, and he responded to the call by simply reactivating and expanding the network.

鈥淥ver the last two decades, my research time has been spent on establishing and leading national teams from one pandemic to another,鈥� says Wu, whose work focused on big data and neural networks prior to the SARS outbreak.

Sitting on multiple provincial, national and international panels, Wu is also a member of the Ontario Modelling Consensus Table that builds consensus 鈥� using research results of multiple modelling teams from across Ontario universities 鈥� about the projected COVID-19 cases and the disease burden on the health system under a range of intervention scenarios. This consensus has been providing critical data to inform the government鈥檚 policy about closures and re-openings: how to do so and how quickly to do so. By integrating mathematical modelling and stochastic optimization, Wu鈥檚 group suggested optimal pathways and likely scenarios for escalating or de-escalating social distancing, and estimated the costs and benefits of each 鈥� factoring in economics and mental health.

鈥淔rom SARS-1 onward, we鈥檝e been working with a variety of stakeholders on collecting data of population contacts, drug resistance, vaccine efficacies, waning and vaccination priorities, and health-care system,鈥� Wu says. 鈥淭he data quality and accessibility has been much improved in Ontario this time, as well as the co-ordination of efforts from different research groups. Each of these modelling teams has a different collection of expertise and that helps cross-validation, which is important when the disease moves so fast and our knowledge about the disease advances fast.鈥�

Wu鈥檚 group has also incorporated artificial intelligence into its work, facilitating the real-time processing of 鈥渢he huge amount of data to identify vulnerable populations and hot spots.鈥�

鈥淎I and Mathematics don鈥檛 have emotion, and they allow us to think several steps ahead,鈥� says Wu, 鈥渂ut with the disease moving so fast, it has been a challenge to convince the decision makers to take a proactive approach rather than being reactive, and, unfortunately, sometimes with a delay.鈥�

Being at the forefront of pandemic modelling isn鈥檛 something Wu anticipated when he arrived at 91亚色. Born in China, he came to Canada to pursue post-doctoral research in Alberta with an international expert in mathematical biology. He joined 91亚色鈥檚 Department of Mathematics and Statistics in 1990 and became the nation鈥檚 youngest Senior Canada Research Chair in 2001. Some of his ongoing research concerns the impact of Lyme disease. He is working to predict the tick-borne infection risk worldwide and looking at how its trajectory is being affected by global warming. In 2017, he was awarded the , and has been leading a large 91亚色-Sanofi collaboration to evaluate the cost and benefits of various immunization programs.

His research interest includes big data and informational analytics, and he is the funding co-chair for a major global conference on this topic.

鈥淒uring peaceful times, it鈥檚 my hobby,鈥� he says.

However, these aren鈥檛 peaceful times and COVID-19 is currently a priority. Wu鈥檚 stellar work serves to demonstrate 91亚色鈥檚 impact on COVID modelling, which will continue to support efforts for future outbreaks and pandemics, COVID-19 related or otherwise.

鈥淒uring a pandemic like this, our theories confront reality,鈥� Wu says 鈥� and big data analytics is a part of his tool kit.

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