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Coupled Diffusion-Binding-Deformation Modelling for Phase-Transition Microneedles-Based Drug Delivery.
Yadav, Prateek Ranjan; Das, Diganta Bhusan; Pattanayek, Sudip K.
Afiliación
  • Yadav PR; Department of Chemical Engineering, Indian Institute of Technology, Delhi 110016, India.
  • Das DB; Chemical Engineering Department, Loughborough University, Loughborough LE11 3TU, Leicestershire, United Kingdom.
  • Pattanayek SK; Department of Chemical Engineering, Indian Institute of Technology, Delhi 110016, India. Electronic address: sudip@chemical.iitd.ac.in.
J Pharm Sci ; 112(4): 1108-1118, 2023 04.
Article en En | MEDLINE | ID: mdl-36528111
ABSTRACT
Phase-transition microneedles (PTMNs)-based transdermal drug delivery (TDD) is gaining popularity due to its non-invasiveness and ability to deliver a wide range of drugs. PTMNs absorb interstitial skin fluid (ISF) and transport drugs from microneedle (MNs) domain to the skin without polymer dissolution. To establish PTMNs for practical use, one needs to understand and optimise the key parameters governing drug transport mechanisms to achieve controlled drug delivery. In addressing this point, we have developed a coupled diffusion-binding-deformation model to understand the effect of physicochemical parameters (e.g., swelling capacity, drug binding) of MN and skin mechanical properties on overall drug transport behaviour. The contact mechanics at the MN and skin interface is introduced to account for the resistive force exerted by the deformed skin to MN swelling. The model is validated with the reported data of in vitro insulin delivery using polyvinyl alcohol (PVA) MN. The drug binding parameters are estimated from the fitting of the cumulative release of insulin within 6 hours of MN insertion. To predict the in vivo data of insulin delivery using the PVA MN, one-compartment model of drug pharmacokinetics is incorporated. It is shown in the paper that the model is able to predict the final insulin concentration in blood and in good agreement with the reported experimental data. The proposed model is concluded to be a tool for the predictive design and development of PTMNs-based TDD systems.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Piel / Sistemas de Liberación de Medicamentos Tipo de estudio: Prognostic_studies Idioma: En Revista: J Pharm Sci Año: 2023 Tipo del documento: Article País de afiliación: India

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Piel / Sistemas de Liberación de Medicamentos Tipo de estudio: Prognostic_studies Idioma: En Revista: J Pharm Sci Año: 2023 Tipo del documento: Article País de afiliación: India