Fabrication of Ciprofloxacin-Loaded Sodium Alginate Nanobeads Coated with Thiol-Anchored Chitosan Using B-390 Encapsulator Following Optimization by DoE

Abstract

Most infectious diseases of the gastrointestinal tract can easily be treated by exploiting the already available antibiotics with the change in administration approach and delivery system. Ciprofloxacin (CIP) is used as a drug of choice for many bacterial infections; however, long-term therapy and off-site drug accumulation lead to an increased risk of tendinitis and peripheral neuropathy. To overcome this issue, nanotechnology is being exploited to encapsulate antibiotics within polymeric structures, which not only facilitates dose maintenance at the infection site but also limits off-site side effects. Here, sodium alginate (SA) and thiol-anchored chitosan (TC) were used to encapsulate CIP via a calcium chloride (CaCl₂) cross-linker. For this purpose, the B-390 encapsulator was employed in the preparation of nanobeads using a simple technique. The hydrogel-like sample was then freeze-dried, using trehalose or mannitol as a lyoprotectant, to obtain a fine dry powder. Design of Experiment (DoE) was utilized to optimize the nanobead production, in which the influence of different independent variables was studied for their outcome on the polydispersity index (PDI), particle size, zeta potential, and percentage encapsulation efficiency (% EE). In vitro dissolution studies were performed in simulated saliva fluid, simulated gastric fluid, and simulated intestinal fluid. Antibacterial and anti-inflammatory studies were also performed along with cytotoxicity profiling. By and large, the study presented positive outcomes, proving the advantage of using nanotechnology in fabricating new delivery approaches using already available antibiotics.

Keywords: B-390 encapsulator; anti-inflammatory; ionic gelation; nanobeads; sodium alginate; thiolated chitosan.

Figure 1

Pareto charts of the effect of the examined independent variables on the outcomes (PDI, particle size, zeta potential, and % EE) of dry powders (a–d). Bars that exceed the vertical line indicate that the terms are significant (p ˂ 0.05).

Figure 2

Surface plots obtained by STATISTICA^® 12 software presenting the relation between the most influential independent variables on the outcomes (PDI, particle size, zeta potential, and % EE) of dry powders (a–d).

Figure 3

SEM micrographs of dry powder with mannitol (a) and dry powder with trehalose (b).

Figure 4

DSC curves of the polymer, excipients, drug, and dry powder samples, exo ↑ (a), and XRPD patterns of the polymer, excipients, drug, and dry powder samples (b).

Figure 5

% Release of CIP from dry powders in simulated saliva fluid (SSF), simulated gastric fluid (SGF), and simulated intestinal fluid (SIF).

Figure 6

Cell viability MTT assay on Caco-2 cells, with samples concentrations of 0.125, 0.25, and 0.5 mg/mL. Untreated cells served as a control, with 100% viability.

Figure 7

Relative expression of IL-6 on Caco-2 cells; untreated cells served as control. Results are expressed as mean ± SD (n = 3 independent measurements). Level of significance: (* p < 0.05), (** p < 0.01).

Figure 8

Relative expression of HBD-2 on Caco-2 cells; untreated cells served as control. Results are expressed as mean ± SD (n = 3 independent measurements). Level of significance: (* p < 0.05), (** p < 0.01).

Figure 9

MBC values of the samples in µg/mL for Pseudomonas aeruginosa (ATCC^® 27853) (a) and Escherichia coli (ATCC^® 25922) (b). Results are expressed as mean ± SD (n = 3 independent measurements). Level of significance: (* p < 0.05), (** p < 0.01).