Veracity of In Silico Approach for Designing Rivastigmine-Polymer Nano Complexes for Intranasal Delivery: Prediction and In Vitro Validation

Abstract

Background

Rivastigmine (RT), exhibits low oral availability (40%) and high hepatic first-pass (36%). Circumventing the blood-brain barrier-related convolutions for successful brain delivery following intranasal administration prerequisites nano-size particles with high drug loading due to restriction on the quantity administrable through this route. Also, mucoadhesion of nanoparticles (NPs) to nasal mucin is required to counter their ephemeral residence due to rapid mucociliary clearance in order to sustain drug release over a prolonged period. Therefore, the selected polymer should confer these attributes to the NPs for optimized drug delivery to the brain.

Methods

Molecular docking (Flare 4.0) followed by dynamic simulations (Material Studio 2022) comprising of LF dG score, Hildebrand solubility parameters (δ), mixing energy, Flory-Huggins parameters (χ), radius of gyration (Rg) and radial distribution function (RDF) were utilized to study binding affinity of various mucoadhesive polymers and RT. Spray-dried NPs were prepared using in silico screened and selected Eudragit RL 100, sodium hyaluronate, or carboxy methyl cellulose and subjected to in vitro characterization.

Results

Significant correlation obtained for in silico predicted values of LF dG, Rg, and RDF, respectively, with experimentally obtained drug loading and particle size of NPs. This unequivocally suggested prognostic role of molecular predictions in dosage form outcome achievement.

Conclusion

High LF dG score, low RDF and Rg values determined through in silico screening suggested, respectively, high yield, encapsulation efficiency, drug loading and small particle size of NPs. Highest ex vivo permeation of RT was observed from Eudragit RL 100 loaded NPs suggesting their promising role for intra nasal delivery.