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Customizable 3D Printed Implants Containing Triamcinolone Acetonide: Development, Analysis, Modification, and Modeling of Drug Release

Three-dimensional-printed customizable drug-loaded implants provide promising opportunities to improve the current therapy options. In this study, we present a modular implant in which shape, dosage, and drug release can be individualized independently of each other to patient characteristics to imp...

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Detalles Bibliográficos
Autores principales: Ponsar, Hanna, Quodbach, Julian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10459585/
https://www.ncbi.nlm.nih.gov/pubmed/37631311
http://dx.doi.org/10.3390/pharmaceutics15082097
Descripción
Sumario:Three-dimensional-printed customizable drug-loaded implants provide promising opportunities to improve the current therapy options. In this study, we present a modular implant in which shape, dosage, and drug release can be individualized independently of each other to patient characteristics to improve parenteral therapy with triamcinolone acetonide (TA) over three months. This study focused on the examination of release modification via fused deposition modeling and subsequent prediction. The filaments for printing consisted of TA, ethyl cellulose, hypromellose, and triethyl citrate. Two-compartment implants were successfully developed, consisting of a shape-adaptable shell and an embedded drug-loaded network. For the network, different strand widths and pore size combinations were printed and analyzed in long-term dissolution studies to evaluate their impact on the release performance. TA release varied between 8.58 ± 1.38 mg and 21.93 mg ± 1.31 mg over three months depending on the network structure and the resulting specific surface area. Two different approaches were employed to predict the TA release over time. Because of the varying release characteristics, applicability was limited, but successful in several cases. Using a simple Higuchi-based approach, good release predictions could be made for a release time of 90 days from the release data of the initial 15 days (RMSEP ≤ 3.15%), reducing the analytical effort and simplifying quality control. These findings are important to establish customizable implants and to optimize the therapy with TA for specific intra-articular diseases.