Amalgamation of Artificial Intelligence with Nanoscience for Biomedical Applications

Nanoscience in healthcare offers significant advancement in the areas of diagnostic and therapeutic for imaging, biosensing, targeted drug delivery systems, etc. To extend the applications in biomedical engineering, artificial intelligence (AI) technology holds the power to analyze and interpret biological data, accelerate drug discovery and identify selective small molecules or unique compounds with predictive behavior. Implementation of such database systems for rapid data analysis, treatment strategies, novel hypotheses development, and determination of disease progression remarkably improves the treatment outcomes with the potential to accelerate the high-throughput development and systematic design of highly effective smart materials and nanoformulations with pre-defined functionality. Specifically, optimizing physicochemical parameters, compatibility, and drug-dose parameters with higher prediction efficiency (above 90%) is the area where AI holds the potential to actionably cognize the full nanotechnology potential. This review article discusses the research findings to accelerate the clinical translation of nanoscience, bestow the potential development of high throughput experimentation-based, AI-assisted design, and data-driven production of nanosynthesized systems.{GRAPHIACAL ABSTRACT}

Automated summary

Nanoscience in healthcare has made significant advancements in diagnostic and therapeutic applications, such as imaging, biosensing, and targeted drug delivery systems. Artificial intelligence technology has the potential to analyze biological data, accelerate drug discovery, and identify predictive small molecules or unique compounds.