LAUSR

PurposeA common approach to “Quality-by-Design” is to employ quality software(s) to characterize the impacts of input parameters on output-critical quality attributes. In this study, paclitaxel (PTX), a common chemotherapeutic agent, was loaded into poly-lactic-co-glycolic acid (PLGA) nanoparticles (NPs), and the coating process of chitosan (CS) onto PLGA NPs was focused for optimization.MethodExperiments were designed using Modde 8.0 to set up a D-optimal design for inputs (CS/PLGA ratios, temperature, and pH), and particle size (Z), zeta potential (Zeta), polydispersity index (PDI), encapsulation efficiency (EE), and loading capacity (LC) were the selected outputs. Data analysis was performed using Modde 8.0 concurrently with artificial neural networks such as INform 3.1 and FormRules 2.0. Furthermore, enhancement of cytotoxicity, cellular uptake, and apoptosis by CS coating were also determined.ResultsThe results confirmed the influence of inputs on output ones (R2 > 90%). The optimized formulation showed Z of 161.53 ± 0.97 nm, PDI of 0.270 ± 0.007, Zeta of 41.87 ± 1.42 mV, and EE of 98.59 ± 0.22%; the results were close to the predicted calculations. The optimal formulation, CS-PLGA NPs, showed higher cytotoxicity than PLGA NPs in Hela and SK-LU-1 cell-lines (cell viability assay). Furthermore, apoptosis and intracellular uptake studies confirmed enhancement of the CS layer.ConclusionThe data reveal the validity of optimization models and their potential in anti-cancer therapy, especially for lung and cervical cancer treatment.