Grant: DRA: Canada Impact+ Research Training Awards - Doctoral

"Drug discovery relies on biological models to evaluate whether new treatments are safe and effective before they are tested in patients. Traditional models based on 2D cell culture, where cells grow as flat layers, often poorly predict drug efficacy, contributing to high failure rates in drug development. Three-dimensional (3D) cell culture offers a more realistic alternative by growing cells in small multi-cellular clusters, such as spheroids, organoids, or “mini-tumors”, that better replicate the complex cell interactions and chemical environments found in real tissues. Despite these advantages, 3D models are difficult to produce consistently. They require careful manual handling, are difficult to standardize, and challenging to scale-up for drug screening. This project aims to develop automated platforms to make 3D cell culture reliable, reproducible, and scalable. By integrating improved cell culture substrates, robotic liquid handling, high-throughput microscopy, and AI-powered data analysis, we aim to dramatically increase the speed and consistency of 3D drug screening workflows. This work will lay the foundation for personalized “patient avatars”, where cells extract from patient tumor biopsies are grown into thousands of mini-tumors. Using robotic systems, these mini-tumors are rapidly tested against many drug options, to identify the most effective and least toxic treatment combination prior to therapy."