Improved quality control of blood products using high throughput mass spectrometry coupled to machine learning approaches.

We will assess the quality and suitability of blood and blood-derived products using a fast and economical approach that combines measurements of molecules in the blood product identified by their weight and computational approaches to make sense of all the data generated. Normal blood products have thousands of small molecules in common. By monitoring a large spectrum of these molecules, we will be in a position to determine the normal state and the quality of the products. Having determined the profile of molecules that are present in the normal conditions therefore any deviations should be considered abnormal and the product discarded or tested for degradation or infection by microbes. The process will increase the safety of blood and blood products in Canada and therefore will benefit all Canadians. The process will save money and time and provide new expertise for blood banks across our country. Moreover, the project will open new markets for our sponsor Phytronix

Faculty Supervisor:

Jacques Corbeil

Student:

Pierre-Luc Plante

Partner:

Phytronix Technologies

Discipline:

Microbiology / Immunology

Sector:

Life sciences

University:

Université Laval