4.7 Article

Fabrication and Modelling of a Reservoir-Based Drug Delivery System for Customizable Release

期刊

PHARMACEUTICS
卷 14, 期 4, 页码 -

出版社

MDPI
DOI: 10.3390/pharmaceutics14040777

关键词

drug delivery system; diffusion-controlled; drug reservoir; glioblastoma; computational modelling

资金

  1. German Research Foundation (DFG) [RTG2154]

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Localized therapy approaches have emerged as an alternative route to overcome the limitations of systemic therapies. To achieve effective treatment, the release kinetics of drug delivery systems (DDS) need to be controlled. This study presents a computationally supported reservoir-based DDS development for patient-specific release kinetics, allowing for precise adaptation of release profiles.
Localized therapy approaches have emerged as an alternative drug administration route to overcome the limitations of systemic therapies, such as the crossing of the blood-brain barrier in the case of brain tumor treatment. For this, implantable drug delivery systems (DDS) have been developed and extensively researched. However, to achieve an effective localized treatment, the release kinetics of DDS needs to be controlled in a defined manner, so that the concentration at the tumor site is within the therapeutic window. Thus, a DDS, with patient-specific release kinetics, is crucial for the improvement of therapy. Here, we present a computationally supported reservoir-based DDS (rDDS) development towards patient-specific release kinetics. The rDDS consists of a reservoir surrounded by a polydimethylsiloxane (PDMS) microchannel membrane. By tailoring the rDDS, in terms of membrane porosity, geometry, and drug concentration, the release profiles can be precisely adapted, with respect to the maximum concentration, release rate, and release time. The release is investigated using a model dye for varying parameters, leading to different distinct release profiles, with a maximum release of up to 60 days. Finally, a computational simulation, considering exemplary in vivo conditions (e.g., exchange of cerebrospinal fluid), is used to study the resulting drug release profiles, demonstrating the customizability of the system. The establishment of a computationally supported workflow, for development towards a patient-specific rDDS, in combination with the transfer to suitable drugs, could significantly improve the efficacy of localized therapy approaches.

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