The collaboration aims to develop new quantum algorithms that could accelerate the design of next-generation photosensitisers for photodynamic therapy, a non-invasive treatment approach targeting tumour cells.
The project combines Xanadu’s algorithms team and the University of Alberta chemistry professor Alex Brown.
They will work jointly to create a quantum computing framework that addresses the challenges involved in the discovery of novel photosensitisers.
Existing approaches to identifying effective photosensitisers rely on experimental methods or classical simulations, which the partners say are either slow, costly, or limited in their capacity to account for critical molecular interactions.
Recent results released by Xanadu have used quantum computers to simulate light-matter interactions in photosensitiser compounds, focusing on characteristics such as sensitivity to specific wavelengths and the efficiency of triggering cancer cell death.
Xanadu founder and CEO Dr Christian Weedbrook said: “Current methodologies for developing effective photosensitisers are hampered by a variety of hurdles.
“By leveraging early fault-tolerant quantum computers to model critical light-matter interactions within photosensitisers, we are positioning quantum computing as a highly competitive method for accelerating photodynamic drug discovery.”
Brown said: “Photosensitisers are challenging systems because their performance depends on excited-state processes that are difficult to capture accurately with standard computational methods.
“By combining Xanadu’s quantum algorithm expertise with our experience in modelling photodynamic therapy systems, we’re excited to explore how fault-tolerant quantum computing could provide new tools for understanding and designing more effective light-activated cancer treatments.”
The collaboration is intended to strengthen Xanadu’s quantum-based drug design workflow, with the goal of expanding its use to more complex problems in photosensitiser development.
Brown’s role will include identifying mechanisms that influence therapeutic effectiveness in photodynamic therapy.