間眅埶AV

Prof. Caroline Colijn from 間眅埶AV's Department of Mathematics is one of the researchers leading the study. She also holds the Canada 150 Research Chair in Mathematics for Evolution, Infection and Public Health. Some graphical descriptions of the genomic data and mathematical models used in her research can be seen in the background. Photo: Dale Northey (間眅埶AV)

Research

Pioneering 間眅埶AV research customizes vaccines to reduce bacterial disease

February 03, 2020
Facebook
Twitter
LinkedIn
Reddit
SMS
Email
Copy

By Shradhha Sharma

The invention of vaccines for disease prevention is often cited as one of the miracles of modern medicine. New research from 間眅埶AV suggests that tailoring vaccines based on geography and other factors could substantially reduce overall rates of bacterial disease.

Professor Caroline Colijn, who holds a Canada 150 Research Chair in Mathematics for Evolution, Infection and Public Health, is among lead researchers on the study published today in .

Colijn collaborated with of the University of Oslo and  from the MRC Centre for Global Infectious Disease Analysis at Imperial College London.

The trio proposes new methods for choosing the best vaccine to fight and eliminate certain bacterial strains, which could help minimize rates of pneumococcal disease, an infection that can cause serious illnesses, such as pneumonia, sepsis and bacterial meningitis.

Designing the best vaccine is important because when we vaccinate against some strains, other strains can come in and replace those strains, says Colijn. If new strains are as bad as the ones we have replaced through vaccinations, that can undermine our vaccination efforts.

Citing existing concerns in the medical community around the replacement of bacterial strains in vaccines, Colijn says her latest research goes a step further. Researchers propose using genomic data and mathematical modelling to design vaccines for the specific geographic location where they will be used.

The study simulated the performance of vaccines over time to assess the risk of vaccine-targeted strains being replaced by other potentially dangerous strains. Through this predictive modelling approach, the researchers identified new vaccine designs that could help reduce overall rates of disease.

Its only recently that we have been able to do bacterial genomics on the scale that we require for this work, says Colijn. This was made possible by our ability to combine sequencing technologies with computational modelling in a new way.

These data modelling methods, when applied to pneumococcus, also help identify which options are best for minimizing disease in different age groups, or reducing the frequency of antibiotic resistant-infections.

Researchers are already considering whether these findings could be applied to other bacterial pathogens such as E. coli.

Both Corander and Croucher are also associate faculty at the , which could play a pivotal role in accelerating future vaccine discovery and design using these techniques.

WHY IT MATTERS:

According to , vaccines have saved more lives in Canada than any other medical intervention in the past 50 years.

The estimates that vaccines prevented at least 10 million deaths between 2010 and 2015, and protected many millions more lives.