Real-time AI-Powered Cells Segmentation

Sanofi, a leading pharmaceutical and healthcare company, continues to seek highly qualified personnel to achieve the goals of incorporating machine learning into various processes, which will allow for optimal development of its vaccines. Sanofi has a critical goal of combining smart data, such as those obtained through image analysis and flow cytometric assessments with artificial intelligence to have a digital twin of every process in manufacturing. Appropriate cell segmentation practices are critical to performing optimal analysis of images and in performing flow cytometry. One key challenge is the need to collect and process inline and offline data to obtain target cell/cellular entities trends either directly or via inference for appropriate cell segmentation. This process can be resource intensive, inefficient, and prone to generating images that are difficult to interpret. Interpretation of the images using machine learning will foster better understanding of the data to reveal information on cell diameter, cell circularity, light phase and cell count. Overall, they will be incorporated into knowledge database as per harbingers of productivity or root cause of possible ailments in the process. This approach could be implemented across multiple business units of Sanofi, such as Speciality Care, General Medicines and Vaccines.

Faculty Supervisor:

Arash Mohammadi

Student:

Partner:

Sanofi

Discipline:

Engineering

Sector:

Health and Related Sciences & Technology; Manufacturing; Other services (except public administration); Professional, scientific and technical services; Wholesale trade

University:

Concordia University

Program:

Accelerate