Nano-enhanced photodynamic therapy and machine learning: Advancements, challenges, and future directions
Alexander Chota1, Heidi Abrahamse1, Blassan P George1
1Laser Research Centre, Faculty of Health Sciences, University of Johannesburg, P.O. Box 17011, Doornfontein 2028, South Africa.
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Cancer remains a leading cause of death globally for both men and women, characterized by the uncontrolled growth of cells. Common risk factors for cancer include exposure to carcinogens such as alcohol, tobacco, toxins, gamma rays, and alpha particles. Over the past decade, significant efforts have been directed towards the synthesis of eco-friendly green metallic nanoparticles and their medical applications. Metallic NPs offer considerable advantages over traditional therapies and can be functionalized with various drug delivery systems and targeting agents, including liposomes, antibodies, folic acid, transferrin, and carbohydrates. This review highlights and provides an overview of recent advances on nano-based therapies to enhanced cancer photodynamic therapy (PDT). Review also discusses the benefits of green hybridized metallic NPs over conventional photosensitizers (PSs) and explores future perspectives in nanotechnology using artificial intelligence (AI) models, and clustered regularly interspaced short palindromic repeats (CRISPR) in combination with PDT in cancer research and therapy. The insights provided aim to inspire the design and development of green nano-formulations for improved image-guided cancer PDT.
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