Quantum Computing for Photon-Drug Interactions in Cancer Treatment

Quantum computing is at the threshold of transforming molecular simulation, offering solutions to some of the most intractable challenges in computational chemistry. One of the areas where this transformation is most urgently needed is photodynamic therapy (PDT) drug discovery, a highly promising yet computationally demanding approach to targeted cancer treatment. PDT drugs must be carefully designed to optimize light absorption, reactive oxygen species generation, and excited-state stability. However, classical methods have failed to provide accurate predictive modeling for PDT drug candidates, leaving experimental screening as the primary discovery method—an inefficient and costly approach that has significantly slowed innovation.

In this talk, I will outline our project, currently a part of the Wellcome Leap Quantum4Bio Global Challenge that is designed to address these challenges by building the first scalable quantum

simulation pipeline for PDT drug discovery, allowing for the rational design of next-generation photosensitizers. In particular, I will discuss a series of groundbreaking advancements, enabling large-scale quantum chemistry simulations that were previously infeasible. These results provide a clear path toward executing hardware-based quantum simulations at a scale where classical multiconfigurational quantum-chemistry methods break down, setting the stage for the first credible demonstration of quantum advantage in molecular modelling, currently ongoing in our laboratories in joint collaboration with our clinical partner at Cleveland Clinic and our hardware partner at IBM Quantum.

With these innovations at hand, we present an end-to-end procedure —from defining a molecular structure to computing error-mitigated ground- and excited-state energies and molecular properties using real quantum hardware at at 50+ qubit scale. This marks a significant step toward practical, hardware-compatible quantum chemistry simulations.