Formulation of simvastatin chitosan nanoparticles for controlled delivery in bone regeneration: Optimization using Box-Behnken design, stability and in vivo study
Graphical abstract
Introduction
Simvastatin (SIM), a 3-Hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitor, is considered for the main treatment of high lipid profiles in the body (Schachter, 2005). Other than hyperlipidemia, SIM appears to have a very important role in tissue engineering and bone regeneration (Werlang et al., 2014). SIM has the ability to upregulate bone morphogenetic protein-2 (BMP-2) mRNA expression in human mesenchymal stem cells, which is related to osteoblast differentiation (Alam et al., 2009, Mundy et al., 1999). To achieve the best results as a bone regenerating agent, SIM must be accumulated in bones in appropriate concentrations (0.5–1.5 mg) with a sustainable release pattern (Bae et al., 2011, Ezirganlı et al., 2014). SIM is an anionic lipophilic drug with low oral bioavailability and is extensively cleared by the hepatic circulation. SIM systemic delivery has shown contradictory results at conventional doses, with little drug bone accumulation (Kheirallah and Almeshaly, 2016). Animal and clinical studies have suggested that high SIM oral doses to overcome the high hepatic metabolism and to target the bone tissue could be beneficial, but the concomitant drawbacks included undesirable side effects and induced liver and kidney failures (Tai et al., 2013).
Different approaches have been utilized to attain local controlled delivery of SIM for bone regeneration, including scaffold engrafted with microparticles (Gentile et al., 2016), nanostructured lipid carrier (Yue et al., 2016), collagen sponge (Papadimitriou et al., 2015) and microspheres (Tai et al., 2013).
Another approach is locally applying NPs containing the drug. NPs can be tailored to have specific properties, such as (i) small particle size (PS) and high surface charge, (ii) sustained drug release and (iii) improved drug encapsulation (Blanco et al., 2015, Petros and DeSimone, 2010).
Chitosan - tripolyphosphate (CS-TPP) NPs could be another good strategy to achieve slow and controlled release of SIM, depending mainly on the gelling properties of CS and TPP and the involved chemical cross-linking agent (Wang et al., 2011). SIM CS-TPP NPs can also improve SIM solubility and stability. As a local drug delivery system, CS-TPP NPs possess several advantages, such as (i) biocompatibility and biodegradability, (ii) controlled drug release due to diffusion and slow polymer degradation, (iii) high entrapment efficiency, especially for anionic drugs, (iv) enhanced permeability, (v) mucoadhesive property leading to higher contact between the drug and the site of action and (vi) high stability (Duceppe and Tabrizian, 2010, Elgadir et al., 2015, Wang et al., 2011).
CS is a natural polysaccharide which is a cationic copolymer of glucosamine and N-acetyl-glucosamine units linked by 1–4 glucoside bonds, and found to be the most utilized and distributed biomaterial after cellulose (Rinaudo, 2006). Properties such as in situ gelation, biodegradability, biocompatibility, good adhesive properties and nontoxicity make CS a convenient drug delivery in pharmaceutical formulations (Bao et al., 2008). CS has the capacity to be immediately transformed into hydrogel when mixed or homogenized with TPP, which is a multivalent anionic polymer, due to the formation of intra- and intermolecular cross-linkage mediated by electrostatic attraction between CS positively charged amino groups along with the negatively charged phosphates of TPP (Severino et al., 2016, Shu and Zhu, 2002). Moreover, TPP is predominantly used because of its nontoxic property and quick gelling capacity, and it can also produce a relatively high-density stable complex with CS (Shavi et al., 2011).
Box-Behnken response surface design (BBD) is a valuable statistical experimental tool for the study of the main effects and interactions of different factors over responses using only a few experimental runs and covering all possible combinations and requires only three levels of each factor (Zidan et al., 2007). BBD consists of a group of points lying at the midpoint of each edge of the multidimensional cube in addition to the replicated center point (Chopra et al., 2007). BBD can be used to determine optimum conditions for the desired formulation, where the quadratic terms are estimated by participation of the axial points, and the pure experimental uncertainty at the factor levels is estimated by the repetition of the center points (Kalam et al., 2016).
In the present study, the ionic gelation method was used to prepare SIM CS-TPP NPs to achieve a controlled and sustained delivery system that can provide the required SIM concentration in local application for bone regeneration. A three-factor, three-level BBD was used to study the effects of different variables on the studied responses to find an optimized formula. The independent variables selected were: CS percentage (A), TPP percentage (B) and homogenization time (C). The dependent variables (responses) chosen in the study included: particle size (PS) [Y1], zeta potential (ZP) [Y2], polydispersity index (PDI) [Y3] and entrapment efficiency percent (EE%) [Y4]. The optimum SIM-loaded CS-TPP NPs formula was physically characterized using Fourier transform infrared (FT-IR) spectroscopy, differential scanning calorimetry (DSC) and transmission electronic microscopy (TEM). SIM NPs were also assessed for their swelling index (SI). The in vitro SIM cumulative release percentage from the optimum formula was also determined and compared to raw SIM. The optimum SIM CS-TPP NPs formula was further investigated for its storage stability performance for three months at ambient conditions. Finally, the bone regeneration activity of the optimum formula was assessed in a bone defect model in rabbits.
Section snippets
Materials
Simvastatin was kindly supplied by (Global Napi Pharmaceuticals, Egypt). Low molecular weight CS and TPP were purchased from Sigma-Aldrich Chemical Co. (St. Louis, USA). All other chemicals were of pure analytical grade.
Experimental design
A three-factor, three-level (33) BBD was conducted to statistically optimize the formulation variables of SIM CS-TPP NPs preparation. Construction and estimation of the experimental design was performed using Design Expert® software (Version 10, Stat-Ease Inc., Suite 480
Statistical analysis of the 33 BBD
The responses of PS (Y1), ZP (Y2), PDI (Y3) and EE% (Y4) were fitted individually to linear, 2-factor interaction (2FI) and quadratic models using linear regression to obtain the model of choice with the highest adjusted and prediction r2. ANOVA testing was performed to identify the significant terms of the chosen model on the responses. The model terms with p value <0.05 were considered statistically significant. Model reduction was performed by removing the nonsignificant model terms to
Conclusion
The ionic gelation method was successfully implemented to produce SIM NPs with small and uniform PS and high ZP and EE%. The method is simple, scalable, reproducible, economical, and environmentally friendly and produces NPs of high stability. Statistical analysis of the 33 BBD for PS, ZP, and PDI indicated that the quadratic model was the one of choice, while the linear model was suggested for EE%. Model analysis revealed that CS and TPP percentages had significant effects on PS, ZP and PDI.
Future perspectives
The promising results obtained in this study encouraged us to continue work on this project. A current study is being carried out to assess the bone regeneration activity of the optimum SIM CS-TPP NPs formula by quantification of the level of bone morphogenic protein 2 in the plasma samples of the rabbits in different group using the suitable ELIZA kit.
CRediT authorship contribution statement
Wisam Khalaf Delan: Methodology, Formal analysis, Investigation, Writing - original draft. Mai Zakaria: Methodology, Investigation. Basma Elsaadany: Methodology, Investigation. Aliaa N. ElMeshad: Conceptualization, Validation, Resources, Writing - review & editing, Supervision, Funding acquisition. Wael Mamdouh: Validation, Resources, Writing - review & editing, Funding acquisition. Ahmed R. Fares: Methodology, Validation, Formal analysis, Writing - review & editing.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments and disclosures
The authors acknowledge the financial support received from the American University in Cairo (AUC), Egypt through student and Faculty Support Research Grants. The authors declare that there is no conflict of interests.
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