Central Composite Design for Optimization of Mitomycin C-Loaded Quantum Dots/Chitosan Nanoparticles as Drug Nanocarrier Vectors.

Cancer is one of the most devastating diseases that leads to a high degree of mortality worldwide. Hence, extensive efforts have been devoted to the development of drug nanocarrier vectors as a potential new cancer treatment option. The main goal of this treatment is to deliver an anticancer medicine successfully and effectively to the patient's cells using non-toxic nanocarriers. Here, we present a drug delivery system to emphasize the optimization of an anticancer drug-loaded formulation using Mitomycin C (MMC) encapsulated in chitosan nanocarrier conjugated with a bioimaging fluorescence probe of Mn:ZnS quantum dots (MMC@CS-Mn:ZnS). Additionally, the Response Surface Methodology (RSM), which uses a quadratic model to forecast the behaviour of the nano-drug delivery system, was used to assess the optimization of encapsulation efficiency. In this investigation, the core points of the Central Composite Design (CCD) model were used with 20 runs and 6 replications. The encapsulation efficiency (EE%) was measured using UV-Vis spectroscopy at 362 nm. The highest EE% is 55.31 ± 3.09 under the optimum parameters of incubation time (105 min), concentration of MMC (0.875 mg/mL), and concentration of nanocarriers (5.0 mg/mL). Physicochemical characterizations for the nanocarriers were accessed using a nanosizer and field-emission scanning electron microscopy (FESEM). Three independent variables for the evaluation of the encapsulation efficiency were used, in which the incubation time, concentration of MMC, concentration of nanocarriers, and correlation for each variable were studied. Furthermore, the MMC drug release efficiency was carried out in four different solution pHs of 5.5, 6.0, 6.5, 7.0, and pH 7.5, and the highest cumulative drug release of 81.44% was obtained in a pH 5.5 release medium, followed by cumulative releases of 68.55%, 50.91%, 41.57%, and 32.45% in release mediums with pH 6.0, pH 6.5, pH 7.0, and pH 7.5. Subsequently, five distinct mathematical models-pseudo-first-order, pseudo-second-order, Hixson-Crowell, Korsmeyer-Peppas, and Higuchi kinetic models-were used to fit all of the drug release data. The Korsmeyers-Peppas model was found to fit it well, highlighting its importance for the log of cumulative drug release proportional to the log of time at the equilibrium state. The correlation coefficient value (R