Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.681173
Title: Micro-injection moulded microneedles for drug delivery
Author: Nair, Karthik Jayan
ISNI:       0000 0004 5919 1649
Awarding Body: University of Bradford
Current Institution: University of Bradford
Date of Award: 2014
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Abstract:
The emergence of microneedle (MN) technologies offers a route for a pain free, straightforward and efficient way of transdermal drug delivery, but technological barriers still exist which pose significant challenges for manufacture of MN systems with high volume outputs at low cost. The main aim of this research was to develop new ways for MN manufacture primarily using micro-injection moulding processes with high performance engineering thermoplastics. During the moulding process these polymeric melts will be subjected to extreme stress and temperature gradients and detailed material characterisation combined with in-line monitoring is desirable to optimise the moulding parameters and will help in achieving sharp microneedles with acceptable quality. Hence high shear rheology of these selected materials was performed at wall shear rates carried out in excess of 107 s-1 over a range of temperatures to predict the flow behaviour of polymer melts at such high shear strain rates. This information was fed into injection moulding simulation software tools (Moldflow) to assist the MN production process design. The optimal design was then used to produce a full 3D solid model of the injection mould and mould insert. Furthermore various design of experiments were conducted considering input parameters such as injection pressure, injection speed, melt temperature, filling time and mould cavity temperature. Response variables including product quality and data acquired from the cavity pressure and temperature transducers were used to optimise the manufacturing process. The moulded MNs were geometrically assessed using a range of characterisation techniques such as atomic force microscopy, confocal microscopy and scanning electron microscopy. An attempt to make hollow MNs was performed and encountered many challenges like partial cavity filling and part ejection during processing. Studies were carried out to understand the problem and identified the major problem was in tool design and improvements to the moulding tool design were recommended. Plasma treatment and mechanical abrasion were employed to increase the surface energy of the moulded polymer surfaces with the aim of enhancing protein adsorption. Sample surface structures before and after treatment were studied using AFM and surface energies have been obtained using contact angle measurement and calculated using Owens-Wendt theory. Adsorption performance of bovine serum albumin and release kinetics for each sample set was assessed using a Franz diffusion cell. Results indicate that plasma treatment significantly increases the surface energy and roughness resulting in better adsorption and release of BSA. To assist design-optimisation and to assess performance, a greater understanding of MN penetration behaviour is required. Contact stiffness, failure strength and creep behaviour were measured during compression tests of MN against a steel surface, and in-vitro penetration of MNs into porcine skin. The MN penetration process into porcine skin was imaged using optical coherence tomography. Finally, a finite element model of skin was established to understand the effect of tip geometry on penetration. The output of findings from this research will provide proof of concept level development and understanding of mechanisms of MN penetration and failure, facilitating design improvements for micro-injection moulded polymeric MNs.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.681173  DOI: Not available
Keywords: Micro-injection moulding ; Microneedles ; Bovine serum albumin ; Plasma treatment ; Surface energy ; Optical coherence tomography ; Drug delivery
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