Quantum Computing for Photosensitizer Design in Photodynamic Therapy.

Area of Science:

• Biomedical optics
• Photochemistry
• Computational chemistry

Background:

• Photodynamic therapy (PDT) is an evolving cancer treatment using light-activated photosensitizers (PSs) to generate reactive oxygen species (ROSs), inducing tumor cell death.
• Current PDT limitations include the need for PSs activated by deep-penetrating near-infrared light, with low dark toxicity and efficient ROS production.

Purpose of the Study:

• To review current photosensitizer (PS) categories in clinical and preclinical trials.
• To highlight the role of computational methods in understanding PS activation mechanisms.
• To propose quantum computing as a novel approach for optimizing PS design.

Main Methods:

• Review of existing literature on photosensitizers (PSs) and their applications in photodynamic therapy (PDT).
• Discussion of advanced computational chemistry methods, including density functional theory (DFT) and wave function-based quantum chemistry.
• Exploration of quantum computing for simulating excited-state dynamics of PSs.

Main Results:

• Various categories of PSs are currently in clinical or preclinical development for PDT.
• Classical computational methods aid in understanding PS molecular mechanisms but face challenges with complex systems.
• Quantum computing offers a promising avenue for accurate modeling of PS excited-state properties.

Conclusions:

• Optimizing PS design is crucial for advancing PDT applications.
• Quantum computing has the potential to revolutionize PS development by enabling precise modeling of their photophysical properties.
• This approach could lead to more effective and broadly applicable PDT cancer treatments.