Quantum Computing for Photosensitizer Design in Photodynamic Therapy

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Abstract
Use of light in healthcare is evolving with increasing applications of photodynamic therapy (PDT) for treating various cancers. PDT utilizes light-activated molecules called photosensitizers (PSs) that generate reactive oxygen species (ROSs) to induce tumor cell apoptosis and necrosis. However, the use of PDT is limited by the availability of PSs that can be activated by deep tissue–penetrating near-infrared light, exhibit low dark toxicity, and produce ROSs efficiently. Here we review the different categories of PS currently used in clinical or preclinical trials and highlight the significance of advanced computational methods, including density functional and wave function–based quantum chemistry, for understanding the molecular mechanisms involved in PS activation. Despite advancements in classical computational techniques, the complexities of excited state dynamics in highly correlated molecular systems demand innovative simulation approaches such as quantum computing. We propose that quantum computing holds promise for accurately modeling the excited-state properties of PSs to optimize their design and broaden clinical applications.

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