Artificial intelligence (AI) is a branch of computer science that allows machines to work efficiently, can analyze complex data. The research focused on AI has increased tremendously, and its role in healthcare service and research is emerging at a greater pace. This review elaborates on the opportunities and challenges of AI in healthcare and pharmaceutical research. The literature was collected from domains such as PubMed, Science Direct and Google scholar using specific keywords and phrases such as ‘Artificial intelligence’, ‘Pharmaceutical research’, ‘drug discovery’, ‘clinical trial’, ‘disease diagnosis’, etc. to select the research and review articles published within the last five years. The application of AI in disease diagnosis, digital therapy, personalized treatment, drug discovery and forecasting epidemics or pandemics was extensively reviewed in this article. Deep learning and neural networks are the most used AI technologies; Bayesian nonparametric models are the potential technologies for clinical trial design; natural language processing and wearable devices are used in patient identification and clinical trial monitoring. Deep learning and neural networks were applied in predicting the outbreak of seasonal influenza, Zika, Ebola, Tuberculosis and COVID-19. With the advancement of AI technologies, the scientific community may witness rapid and cost-effective healthcare and pharmaceutical research as well as provide improved service to the general public.

The objective of the present study was to develop, optimize, and evaluate rotigotine-loaded chitosan nanoparticles (RNPs) for nose-to-brain delivery. Rotigotine-loaded chitosan nanoparticles were prepared by the ionic gelation method and optimized for various parameters such as the effect of chitosan, sodium tripolyphosphate, rotigotine concentration on particle size, polydispersity index (PDI), zeta potential, and entrapment efficiency. The prepared nanoparticles were characterized using photon correlation spectroscopy, transmission electron microscopy, scanning electron microscopy, atomic force microscopy, fourier-transform infrared spectroscopy, and X-ray diffraction. The developed RNPs showed a small hydrodynamic particle size (75.37 ± 3.37 nm), small PDI (0.368 ± 0.02), satisfactory zeta potential (25.53 ± 0.45 mV), and very high entrapment efficiency (96.08 ± 0.01). The 24-h in vitro release and ex vivo nasal permeation of rotigotine from the nanoparticles were 49.45 ± 2.09% and 92.15 ± 4.74% while rotigotine solution showed corresponding values of 95.96 ± 1.79%and 58.22 ± 1.75%, respectively. The overall improvement ratio for flux and permeability coefficient were found to be 4.88 and 2.67 when compared with rotigotine solution. A histopathological study showed that the nanoparticulate formulation produced no toxicity or structural damage to nasal mucosa. Our results indicated that rotigotine-loaded chitosan nanoparticles provide an efficient carrier for nose-to-brain delivery.