Quantum Algorithms for Photoreactivity in Cancer-Targeted Photosensitizers

TL;DR

This paper demonstrates how fault-tolerant quantum algorithms can predict the performance of photosensitizers for photodynamic therapy, potentially accelerating the discovery of effective cancer treatments by overcoming classical computational limitations.

Contribution

It introduces quantum algorithms for evaluating key properties of photosensitizers, enabling simulations of complex molecules beyond classical capabilities, with resource estimates indicating near-term feasibility.

Findings

Quantum algorithms can assess photosensitizer properties with high accuracy.

Simulations of complex BODIPY derivatives are within reach of future quantum devices.

Resource estimates suggest practical implementation with 180-350 qubits and high gate depths.

Abstract

Photodynamic therapy (PDT) is a targeted cancer treatment that uses light-activated photosensitizers to generate reactive oxygen species that selectively destroy tumor cells, generally causing less collateral damage than conventional treatments. However, its clinical success hinges on the availability of photosensitizers with strong optical sensitivity and high efficiency in generating reactive oxygen species. While classical computational methods have provided useful insights into photosensitizer design, they struggle to scale and often lack the accuracy needed for these simulations. In this work, we show how fault-tolerant quantum algorithms can be used to identify promising photosensitizer candidates for PDT. To predict photosensitizer performance, we assess two computational properties. First, we quantify light sensitivity by calculating the cumulative absorption in the therapeutic window with a threshold projection algorithm. Second, we determine the efficiency of reactive oxygen generation by estimating intersystem crossing (ISC) rates using the evolution-proxy approach, complemented by a vibronic dynamic treatment where appropriate. We apply these algorithms to a clinically relevant and actively pursued class of photosensitizers, BODIPY derivatives, including heavy-atom and transition-metal-substituted systems that are challenging for classical methods. Our resource estimates, obtained with PennyLane, suggest that systems with active spaces ranging from 11 to 45 spatial orbitals can be simulated using $180$-$350$ logical qubits and Toffoli gate depths between $10^7$ and $10^9$, placing our algorithms within reach of realistic fault-tolerant quantum devices. This paves the way to an efficient quantum-based workflow for designing photosensitizers that can accelerate the discovery of new PDT agents.