Exploring artificial intelligence-driven photodynamic therapy to advance cancer treatment

Due to its multifaceted nature, cancer remains a formidable disease that continues to cause substantial mortality globally. Conventional treatments, such as surgery, chemotherapy, and radiation therapy, often fail to adequately control this aggressive disease, thereby reducing the quality of life of affected individuals. Photodynamic therapy (PDT) has emerged as a promising treatment modality that utilizes lasers to destroy cancer cells. While PDT has shown promise as a safer and more targeted treatment with fewer side effects compared to some conventional therapies, it faces certain limitations, such as limited light penetration for deep tumors and the need for tissue oxygenation in hypoxic regions. The emergence and potential use of artificial intelligence (AI)-driven technologies in PDT may offer favorable outcomes for cancer treatment by addressing some of the limitations of conventional PDT. AI uses machine learning (ML) and deep learning (DL) algorithms to continuously learn, adapt to changes, recognize abnormalities in a dataset, and make accurate predictions. In this review, we propose integrating AI tools, such as ML and DL, with PDT to combat cancer and address some of the limitations of conventional PDT. The combination of AI and PDT could improve the precision and effectiveness of PDT for cancer treatment by monitoring the effects of PDT during treatment, advancing imaging techniques for better diagnosis of specific tumor types, enabling monitoring of light in real time, and overcoming light-delivery limitations associated with deep, internal tumors, with the potential to improve overall clinical outcomes in cancer patients.