Optimizing microfluidic preparation parameters of nanosuspension to evaluate stability in nanoprecipitation of stable-iodine (127I)

Abstract

The aim of the current study was the development of nanosuspension stability in nanoprecipitation using microfluidic devices. Also, it is desirable to understand how the microfluidic preparation parameters influenced the stability of the stable-iodine ( 127 I) nanosuspension. In optimization process through artificial neural networks (ANNs), the relations between input and output variables were investigated for 37 samples obtained by microfluidic nanoprecipitation process. Solvent temperature, antisolvent flow rate, and solvent flow rate were used as input variables, and the sedimentation time and polydispersity index (PDI) were considered as output parameters. Sedimentation time as an indicator of physical stability of nanosuspension was evaluated by observation of a densely packed sediment. Also, size and PDI of different samples were determined by dynamic light scattering. The size of the optimized sample was confirmed by transmission electron microscopy. The result obtained from modeling showed that increasing solvent temperature and antisolvent flow rate led to a decrease in PDI and an increase in the sedimentation time. The antisolvent flow rate was determined as the most important factor that affected the sedimentation time and PDI. Increasing the solvent flow rate was identified as an adverse factor which increased PDI or decreased formulation's sedimentation time. Optimization using ANN showed that microfluidic preparation parameters of nanosuspension as input variables had potential impacts on output parameters.

Bioactivity and safety evaluations of Cupressus sempervirens essential oil, its nanoemulsion and main terpenes against Culex quinquefasciatus Say

“…The nanoemulsion developed herein exhibited good stability for up to 4 weeks under extreme storage conditions (centrifugation, thermodynamics, viscosity, cooling-freezing and heating-cooling cycles). It is known that nonequilibrium emulsions tend to reduce their interfacial free energy and break down by creaming, flocculation, sedimentation, Ostwald ripening and coalescence (Taylor 2003;KianvashRad et al 2019). The pH can affect nanoemulsion stability, as variations in pH values cause a change in the surface charge of the globules and disturb their stability during storage.…”

A Comprehensive Review of One Decade of Microfluidic Platforms Applications in Synthesis of Enhanced Carriers Utilized in Controlled Drug Delivery

“…Also, it features more surface area, which is an advantage of the process. [142,143] Compared with other nanosuspension preparation methods, the MF techniques can improve reproducibility and stability by utilizing an artificial neural network (ANN), [144] minimizing waste and residuals, and lowering costs. [145] The following studies elucidate the advantages of the MFs technique for the preparation of nanosuspensions:…”

“…Compared with other nanosuspension preparation methods, the MF techniques can improve reproducibility and stability by utilizing an artificial neural network (ANN), [ 144 ] minimizing waste and residuals, and lowering costs. [ 145 ]…”

“…In addition, another article investigated the influence of MFs parameters on nanosuspensions’ stability. [ 150 ] The relationship between input and output variables was assessed via ANNs for 37 MFs prepared nanosuspension in the optimization process. It was illustrated that the input synthesis parameters (i.e., solvent temperature, the flow rate of solvent, and antisolvent) influence output parameters (including sedimentation time and PDI).…”