Optimization of nano delivery systems of an anticancer drug

Abstract

Sesamol is a sesame seed constituent possessing a reported activity against many types of cancer. In this work, two types of nanocarriers, Solid Lipid Nanoparticles (SLN) and Polymeric Nanoparticles (PNs), were exploited through the intranasal route to improve sesamol efficiency against glioma cancers. Also, an attempt to catch up with and share in the vigorously expanding era of the pharmaceutical industry is presented. The major theme here is an examination of the feasibility of the newly emerging notion of Computer-Assissted Drug Formulation Design (CADFD) in predicting Drug Loading (DL) in different nano-delivery systems. This idea has been tested on sesamol using different lipids and polymers as carrier materials to predict carriers possessing the highest sesamol payload in order to achieve an efficient deposition of this phytochemical compound inside the brain. Accordingly, different lipid and polymer systems commonly used for SLN and PNs preparation were virtually simulated using Molecular Dynamics (MD). Sesamol was docked on the built systems using two popular molecular docking programs, AutoDock Vina and Molecular Operating Environment (MOE). The obtained binding energy values along with their underlying SF were used to assess sesamol relative affinity, and hence probable DL pattern, inside these systems. Experimental validation of the obtained in-silico results has been accomplished in the form of successfully prepared sesamol-loaded SLN and sesamol-loaded PNs. After preparing different sesamol-loaded nanoparticles followed by DL measurements and full characterization, a rank order agreement between experimental loading results and in-silico prediction results was recorded. According to this complementarity, Glyceryl Monostearate (GMS)-SLN and Polycaprolactone (PCL)-PNs scored the highest DL both experimentally and computationally. The DL results were 9.58±0.1 µmole/100 mg carrier and 67.04±0.5 µmole/100 mg carrier corresponding to the binding energy of -8.85±0.16 kcal/mol in MOE and -5.04±0.11 kcal/mol in Vina, respectively. Moreover, these systems formed small particles in the nano-range suitable for nose-to-brain delivery with 215.1±7.2 nm and 414.25±1.6 nm, respectively. In silico selected members with the highest drug payload, i.e. GMS-SLN and PCL-PNs were exploited in-vitro to improve the sesamol efficiency against glioma cancer cell line, and in-vivo for its efficient brain targeting via the intranasal route. A cytotoxicity test was conducted on GL261 cell line using 3-(4,5-dimethylthiazole-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay, and in-vivo Pharmacokinetics (PK) experiments were conducted using intranasal administration for male albino rats. The outcomes from both formulations were compared to those from drug solution. The results confirmed the efficient cytotoxic effect and brain targeting ability of the optimized formulations compared to the drug solution. This was evidenced by low IC50 values, 38.50±10.37 µM for GMS-SLN and 27.81±2.76 µM for PCL-PNs, compared to 71.2±9.69 µM for the sesamol solution. Also, high Drug Targeting Efficiency (DTE) values (7.64±1.89 fold and 13.72±4.1 fold) and Direct Transport Percentage (DTP) (86.12±3.89 and 92.198±2.09) for GMS-SLN and PCL-PNs; respectively, were obtained. The current work have shown that the difference in composition and characteristics of different formulations could affect their cytotoxic and targeting ability.