Artificial Intelligence
Artificial intelligence (AI) and machine learning are transforming stem cell research and regenerative medicine, offering unprecedented capabilities to analyze complex biological data, predict cell behavior, and accelerate therapeutic development. From identifying optimal conditions for cell differentiation to analyzing medical imaging and predicting patient outcomes, AI tools are helping researchers work faster and more precisely than ever before.
In Canada, researchers are at the forefront of integrating AI into stem cell science, developing innovative computational approaches that complement traditional laboratory methods. These technologies are enabling breakthroughs in cell manufacturing, quality control, disease modeling, and personalized treatment strategies. As the field advances, AI is becoming an essential tool for translating stem cell discoveries from the laboratory to the clinic, helping to make regenerative therapies safer, more effective, and more accessible to patients across the country.
Dr. Nika Shakiba, University of British Columbia, British Columbia
Human pluripotent stem cells (hPSCs) are extraordinary: they can make unlimited copies of themselves and transform into any cell type in the body. That’s why they’re the foundation of many regenerative therapies now entering clinical trials—including stem cell-derived beta cells for people with diabetes. But while these cells hold immense promise, growing them in large numbers is not without risk.
As hPSCs multiply, some pick up dangerous genetic changes. These “rogue” cells behave more like cancer than cure: they grow faster than their healthy counterparts and can take over an entire cell batch. Once that happens, the product becomes unusable for therapy—and millions of dollars in manufacturing costs may be lost.
Dr. Nika Shakiba is working to stop these variant cells in their tracks. Using a suite of powerful genetic and engineering tools, her team is developing a high-resolution system to track individual hPSCs, identify unwanted variants early, and understand how they gain an edge. By applying machine learning to analyze these data, her lab aims to uncover the signals that predict variant takeover before it occurs.
This work will support the safe, large-scale production of stem cells needed for regenerative therapies—helping Canada’s biotech sector scale up cell manufacturing and deliver high-quality treatments to patients.
“We’re building tools to detect dangerous cells before they compromise a therapy. It’s about protecting the promise of regenerative medicine—so it’s not just effective, but safe and scalable too.”
Dr. Peter Zandstra, University of British Columbia, British Columbia
Stem cells have the potential to transform treatment for many diseases, but turning them into specific, therapeutic cell types is a slow and expensive process. Today’s methods rely heavily on trial and error, specialized expertise, and complex lab work—barriers that limit progress in regenerative medicine.
Dr. Peter Zandstra’s project, IQCELL 2.0, aims to change that. This next-generation platform uses artificial intelligence and systems biology to decode how cells decide their fate. By combining experimental data with advanced machine learning tools, IQCELL 2.0 can predict and design the best protocols for turning stem cells into specific types—faster, cheaper, and more accurately than current methods.
Initially, the platform will be tested and refined using human T-cell data, then expanded to model the creation of other cell types like B-cells and liver cells. Collaborations with leading research and industry partners, including Apiary Therapeutics, Aspect Biosystems, and CCRM, will ensure real-world impact in areas like immunotherapy and regenerative medicine. Ultimately, IQCELL 2.0 will offer a powerful, scalable tool to speed up the development of new cell-based treatments.
“By combining AI with biology, IQCELL 2.0 will make it faster and easier to turn stem cells into the therapies patients need.”
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