Cancer is one of the major causes of death worldwide and chemotherapy is a major therapeutic approach for the treatment which may be used alone or combined with other forms of therapy. However, conventional chemotherapy suffers lack of aqueous solubility, lack of selectivity and multidrug resistance. Nanotherapeutics is rapidly progressing aimed to solve several limitations of conventional drug delivery systems. Nonspecific target of cancer chemotherapy leads to damage rapidly proliferating normal cells and can be significantly reduced through folate and transferrin mediated nanotherapeutics which are aimed to target cancerous cells. Multidrug resistance is challenge in cancer chemotherapy which can be significantly reversed by solid lipid nanoparticles, polymeric nanoparticles, mesoporous silica nanoparticles, nanoparticulated chemosensitizer, nanoparticluated poloxamer and magnetic nanoparticles. Hydrophobic nature of chemotherapeutics leads to poor aqueous solubility and low bioavailability which can be overcome by nanocrystals, albumin based nanoparticles, liposomal formulation, polymeric micelles, cyclodextrin and chitosan based nanoparticles. This review focuses the role of nanotherapeutics to overcome lack of selectivity, multidrug resistance and lack of aqueous solubility of conventional cancer chemotherapy.

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Cu-Pi nanoparticles coated with PEG containing copolymer produced by Fessi method had a minimum average particle size, excellent polydispersity index and optimal zeta potential which fall within the acceptable limits of the study. This dual nanoparticulate drug delivery system appears to be promising to overcome oral bioavailability and cancer cell targeting limitations in the treatment of cancer.

Statistical experimental design and Derringer's desirability function were applied to develop an improved RP-HPLC method for the simultaneous analysis of amlodipine and atorvastatin in pharmaceutical formulations. Four independent factors were considered: acetonitrile content in the mobile phase; buffer pH; buffer concentration; and flow rate. The preliminary screening step was carried out, according to a 2(4-1) fractional factorial design, to identify the significant factors affecting the analysis time response. Then central composite design was applied for a response surface study, in order to examine in depth the effects of the most important factors. Subsequently, Derringer's desirability function was employed to simultaneously optimize the six responses: retention factor of first peak; two resolutions; and three retention times, each having a different target. This procedure allowed deduction of two separate optimum conditions, intended for the analysis of quality control and plasma samples, within the experimental domain. The predicted optimum for the quality control samples was: methanol-acetonitrile-15 mM K(2)HPO(4) buffer (pH 5.33) (10:42.08:47.92, v/v/v) as the mobile phase and 1.12 mL/min as the flow rate. The method using this optimized condition showed higher sensitivity and shorter analysis time than the previously published reports. The optimized assay condition was validated according to International Conference on Harmonization guidelines.