Quantum Computing for Photosensitizer Design in Photodynamic Therapy
Year: 2025
Type: review
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.
Authors: Hope Zehr, Alberto Baiardi, Francesco Tacchino, Anthony Gandon, Laurin E. Fischer, Yue Xu, Frank P. DiFilippo, Leonardo Guidoni, Pi A.B. Haase, Walter N. Talarico, Martina Stella, Fabio Tarocco, Anton Nykänen, Aaron Fitzpatrick, Aaron Miller, Leander Thiessen, Stefan Knecht, Elsi-Mari Borrelli, Sabrina Maniscalco, Fabijan Pavošević, Ivano Tavernelli, Edward Maytin, Vijay Krishna
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4409997166