The genesis of cancer is a precisely organized process in which normal cells undergo genetic alterations that cause the cells to multiply abnormally, colonize, and metastasize to other organs such as the liver, lungs, colon, and brain. Potential drugs that could modify these carcinogenic pathways are the ones that will be used in clinical trials as anti-cancer drugs. Resveratrol (RES) is a polyphenolic natural antitoxin that has been utilized for the treatment of several diseases, owing to its ability to scavenge free radicals, control the expression and activity of antioxidant enzymes, and have effects on inflammation, cancer, aging, diabetes, and cardioprotection. Although RES has a variety of pharmacological uses and shows promising applications in natural medicine, its unpredictable pharmacokinetics compromise its therapeutic efficacy and prevent its use in clinical settings. RES has been encapsulated into various nanocarriers, such as liposomes, polymeric nanoparticles, lipidic nanocarriers, and inorganic nanoparticles, to address these issues. These nanocarriers can modulate drug release, increase bioavailability, and reach therapeutically relevant plasma concentrations. Studies on resveratrol-rich nano-formulations in various cancer types are compiled in the current article. Studies relating to enhanced drug stability, increased therapeutic potential in terms of pharmacokinetics and pharmacodynamics, and reduced toxicity to cells and tissues are the main topics of this research. To keep the readers informed about the current state of resveratrol nano-formulations from an industrial perspective, some recent and significant patent literature has also been provided. Here, the prospects for nano-formulations are briefly discussed, along with machine learning and pharmacometrics methods for resolving resveratrol's pharmacokinetic concerns.
Keywords: machine learning; nanotechnology; polyphenol; resveratrol; stability; targeted therapy; toxicity.