Artificial Intelligence-Nanomedicine Interface: Today’s Theory Tomorrow's Technology

Author(s): Sarah I Mazi, Abdulahi M Hassen, Fahad A Alrashed, Fatiha M. Benslimane, Nura A Mohamed

Substantial strides were made in the nano-therapeutic and nanodiagnostic fields. The clinical deployment of the investigational nanomedicine improved treatment outcomes significantly. Currently, there is an urge to develop a single nanoparticle that can serve as both detection and treatment tools, in addition to the possibility of tailoring it to integrate more than one therapeutic agent. Furthermore, scientists are interested in developing functionalized-nanoparticles that can be activated only at the desired tissues and organs or be taken up by specific cells. Finding nanoparticles with these unique properties is insufficient as concerns about nailing the appropriate doses and accumulation, tolerance, timedependent, and patient-dependent issues persist. Such concerns necessitate establishing better data mining tools as available data is scattered. By integrating artificial intelligence (AI) with nanomedicine, information platforms for this very promising field can be created. Furthermore, through the use of AI-nanomedicine-interface, combinatorial-nanotherapy can be optimized and made more sustainable, moving it one step closer to clinical application. This article, to this end, will focus on implementing AI to improve the sustainability of nanotherapeutics and nanodiagnostics as well as highlighting the possible concerns that AI can address to ensure a smooth translation of the developed nanotherapeutics and nanodiagnostics from bench to clinical use.