Development of pH-Dependent Nanospheres for Nebulisation- In vitro Diffusion, Aerodynamic and Cytotoxicity Studies.

The aim of this work was to evaluate the in vitro performance of nebulized nanosuspension formulation when nebulized using ultrasonic nebulizer. The present investigation deals with successful formulation of Beclomethasone dipropionate loaded HPMCP nanospheres prepared by solvent evaporation technique using PEG 400 as a stabilizer. Beclomethasone dipropionate is a water insoluble drug molecule was encapsulated in HPMCP nanospheres to have pH dependent solubility at basic pH for targeted drug delivery in lung and studied for in vitro cytotoxicity and immediate release capability. The synthesized nanospheres were characterized through drug excipient compatibility, surface topography; mean particle size , zeta potential, PDI, entrapment efficiency and drug loading, in vitro diffusion, aerodynamic, in vitro cytotoxicity and stability studies. The mean particle size and PDI of the optimized batch (F1) had 197.6±0.40 nm and 0.324 ±0.35, respectively. The % entrapment efficiency and % drug loading was found to be 86.56±1.32 and 8.30±0.27, respectively. The optimized batch F1 showed % cumulative drug release 94.77±0.24 at 1 h. The formulation showed cell viability up to 91.28%. It can be concluded that, Beclomethasone dipropionate loaded HPMCP nanospheres was found to be safe, stable with significant increase in solubility and bypass the liver.

Applying quality by design (QbD) concept for fabrication of chitosan coated nanoliposomes.

In the present investigation, a quality by design (QbD) strategy was successfully applied to the fabrication of chitosan-coated nanoliposomes (CH-NLPs) encapsulating a hydrophilic drug. The effects of the processing variables on the particle size, encapsulation efficiency (%EE) and coating efficiency (%CE) of CH-NLPs (prepared using a modified ethanol injection method) were investigated. The concentrations of lipid, cholesterol, drug and chitosan; stirring speed, sonication time; organic:aqueous phase ratio; and temperature were identified as the key factors after risk analysis for conducting a screening design study. A separate study was designed to investigate the robustness of the predicted design space. The particle size, %EE and %CE of the optimized CH-NLPs were 111.3 nm, 33.4% and 35.2%, respectively. The observed responses were in accordance with the predicted response, which confirms the suitability and robustness of the design space for CH-NLP formulation. In conclusion, optimization of the selected key variables will help minimize the problems related to size, %EE and %CE that are generally encountered when scaling up processes for NLP formulations. The robustness of the design space will help minimize both intra-batch and inter-batch variations, which are quite common in the pharmaceutical industry.