Leveraging active learning (AL) technique for the efficient discovery of viral sensitizers

The proposed project aims to accelerate the discovery of viral sensitizers (VSEs), which are small molecules that improve the production of viral vectors like Adeno-Associated Virus or Lentivirus, crucial for gene and cell therapies. Currently, discovering VSEs involves slow and costly high-throughput screening methods. To tackle this, we will develop a new in-silico approach that combines machine learning (ML) and active learning (AL) to enhance the identification of effective VSEs more quickly and efficiently. By using these advanced technologies, the project seeks to improve the hit discovery rate, reduce costs, and explore new chemical spaces that might otherwise be overlooked. The end result will be a faster, more cost-effective process for discovering VSEs, ultimately benefiting Virica Biotech Inc. by enabling improved viral vector production for gene and cell therapies.

Faculty Supervisor:

Francesco Gentile

Student:

Partner:

Virica Biotech

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

University of Ottawa

Program: