Nanomaterials have been extensively investigated to be used in clinical and
pharmaceutical applications due to their unique features, such as shape, size, surface
properties, reactive oxygen species (ROS) scavenging, targeted drug delivery,
improved cell imaging due to excellent fluorescence property, precise personalized
diagnosis, reduced side effects, and excellent sensing property. Despite all advantages,
nanomaterials are signified as a potential generator of ROS, a symbol of toxicity.
Although some clinical practices utilize ROS to prevent cancer, bacterial infection, etc.,
non-customized morphology can yield excessive ROS that may cause harm to normal
cells. Another disadvantage is the infant research stages; more modulation in design is
needed, and evaluation, as well as validation in nanotoxicity, is required. Although
there exist a few stories of nano-medicine-mediated theranostic applications, the
emerging challenges are increasingly prompting researchers to explore the optimal use
of artificial intelligence (AI) in designing personalized drug delivery systems,
potentially offering a more effective alternative to traditional nano-theranostic
approaches. Accordingly, an elaborate governance framework is needed to develop and
implement innovative AI systems successfully in the healthcare sector. The present
work provides a comprehensive overview of the role of AI technologies in drug
delivery, along with its ethical and regulatory concerns. Additionally, it illuminates the
numerous challenges met in the employment of AI systems in clinical practice.
Keywords: Artificial intelligence in drug delivery, AI bot, Drug discovery, Drug delivery, NLP, Toxicity profile.
