Electricity-assisted cancer therapies: nanotechnology, electrochemotherapy, and machine learning

Abstract

Electricity-assisted cancer therapies, including nanotechnology and electrochemotherapy (ECT), have emerged as promising approaches in oncology. Nanotechnology delivers anticancer drugs to tumor sites precisely, improving efficacy and reducing side effects. ECT uses electric pulses to increase cancer cell drug uptake, making them more treatable. Electricity-assisted cancer therapies increasingly employ machine learning algorithms to analyze complex data, optimize treatment protocols, and predict patient outcomes. Nanotechnology has shown promise in improving therapy efficacy and targeting. Researchers can precisely deliver drugs to cancerous cells using nanoparticles, minimizing tissue damage. Nanoparticles' unique properties enable customization to meet treatment needs, improving patient outcomes and treatment success. With fewer side effects, ECT kills cancer cells more effectively. It uses electric pulses to increase cancer cell uptake of chemotherapy drugs, improving treatment outcomes. More research is necessary to optimize electric pulses and chemotherapy drugs to maximize the therapeutic potential of ECT. Machine learning algorithms for electricity-assisted cancer therapies have the potential to revolutionize cancer treatment. Researchers can improve existing therapies and develop patient-specific approaches by using artificial intelligence to analyze massive amounts of data and optimize treatment protocols.