Hejjaji, Ezzeddin M. A. (2018) Tuneable Chitosan Particles with Potential Forensic and Pharmaceutical Applications. Doctoral thesis, University of Huddersfield.

Chitosan(CS), a natural cationic polymer obtained by the partial N-deacetylation of chitin, has been investigated widely for its potential in the development of food and drug delivery systems and pharmaceutical applications, however it has not generally been considered in forensic applications for example fingerprints (fingermarks). The purpose of this study was to prepare chitosan micro/nanoparticles through cross-linking with tripolyphosphate (TPP) utilising the ionotropic interaction between positively charged amino groups (CS) and negatively charged counter ions (TPP). The investigation into the potential of these particles was divided into two parts: forensic and pharmaceutical applications. Firstly, these formulations were characterized (relative viscosity, zeta potential, particle size, FT-IR, XRD, SEM) and evaluated for forensic applications (fingermark visualisation). This can be controlled by the charge density of CS and TPP, which depends on the pH and ionic strength of the solution. Secondly, the combined effects of three independent variables (pH, ionic strength and CS: TPP ratio) on three important physico-chemical properties (viscosity, zeta potential andparticle size) during the preparation of microparticles were investigated. CS: TPP microparticles (CSMPs) were prepared using experimental design and equations were generated and used to predict relative viscosity, zeta potential and particle size under different conditions. This gives us the ability to design tuneable CS: TPP microparticles with desired size for specific pharmaceutical or forensic applications e.g. latent fingerprint visualisation. Fingerprints are a very common form of physical evidence. The most commonly used procedure for revealing the ridge pattern is powder dusting, which relies on the mechanical adherence of fingerprint formulation to the fatty components of the skin deposit that are secreted by sweat pores that exist on friction ridges. The development of latent fingermarks using IICSMPs was analysed by using a 23 factorial design, which considered simultaneously three main factors: pH, ionic strength and CS: TPP (v/v) ratio. CS: TPP ratio has the strongest effect on fingerprint quality. The best conditions for fingerprint visualisation were microparticles prepared using a buffer of pH 4.8, 0.2 M ionic strength at a CS: TPP of 2:1. Although we have demonstrated that CSMPs can be used to develop latent fingermarks there are limitationsin that they are only applicable as a powder and are only sensitive up to the third depletion level for a fingermark aged for one day.

In the final sections of this thesis, chitosan nanoparticles were prepared and characterized for potential applications in drug delivery (using ibuprofen as a model drug) and in terms of their interactions with mucin (mucoadhesion). It has been demonstrated that chitosan nanoparticles can incorporate appreciable quantities of ibuprofen into nanoparticles (CS-IBU-TPP), although the order addition of the individual components is important. The carboxylate ions of the ibuprofen (negative charge) and could bind strongly to the ammonium group (positive charge) of chitosan, thereby allowing greater drug-loading capacity in the chitosan nanoparticles. In addition, the interaction between different ratios chitosan nanoparticles (CS: TPP) and mucin were evaluated based on relative viscosity, zeta potential and particle size. It has been suggested that chitosan nanoparticle-mucin interactions are driven by electrostatic forces. The results conclude that interactions between CS: TPP nanoparticles and mucin occur, with a CS: TPP ratio of 4:1 displaying the strongest interaction with mucin. This is observed through differences in relative viscosity, zeta potential and particle size.

Hejjaji THESIS.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (12MB) | Preview


Downloads per month over past year

Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email