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Status: Bibliographieeintrag

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Verfasst von:Farnoud, Ali [VerfasserIn]   i
 Tofighian, Hesam [VerfasserIn]   i
 Baumann, Ingo [VerfasserIn]   i
 Ahookhosh, Kaveh [VerfasserIn]   i
 Pourmehran, Oveis [VerfasserIn]   i
 Cui, Xinguang [VerfasserIn]   i
 Heuveline, Vincent [VerfasserIn]   i
 Song, Chen [VerfasserIn]   i
 Vreugde, Sarah [VerfasserIn]   i
 Wormald, Peter-John [VerfasserIn]   i
 Menden, Michael [VerfasserIn]   i
 Schmid, Otmar [VerfasserIn]   i
Titel:Numerical and machine learning analysis of the parameters affecting the regionally delivered nasal dose of nano- and micro-sized aerosolized drugs
Verf.angabe:Ali Farnoud, Hesam Tofighian, Ingo Baumann, Kaveh Ahookhosh, Oveis Pourmehran, Xinguang Cui, Vincent Heuveline, Chen Song, Sarah Vreugde, Peter-John Wormald, Michael P. Menden and Otmar Schmid
Jahr:6 january 2023
Umfang:14 S.
Fussnoten:Gesehen am 05.06.2023
Titel Quelle:Enthalten in: Pharmaceuticals
Ort Quelle:Basel : MDPI, 2004
Jahr Quelle:2023
Band/Heft Quelle:16(2023), 1 vom: Jan., Artikel-ID 81, Seite 1-15
ISSN Quelle:1424-8247
Abstract:The nasal epithelium is an important target for drug delivery to the nose and secondary organs such as the brain via the olfactory bulb. For both topical and brain delivery, the targeting of specific nasal regions such as the olfactory epithelium (brain) is essential, yet challenging. In this study, a numerical model was developed to predict the regional dose as mass per surface area (for an inhaled mass of 2.5 mg), which is the biologically most relevant dose metric for drug delivery in the respiratory system. The role of aerosol diameter (particle diameter: 1 nm to 30 µm) and inhalation flow rate (4, 15 and 30 L/min) in optimal drug delivery to the vestibule, nasal valve, olfactory and nasopharynx is assessed. To obtain the highest doses in the olfactory region, we suggest aerosols with a diameter of 20 µm and a medium inlet air flow rate of 15 L/min. High deposition on the olfactory epithelium was also observed for nanoparticles below 1 nm, as was high residence time (slow flow rate of 4 L/min), but the very low mass of 1 nm nanoparticles is prohibitive for most therapeutic applications. Moreover, high flow rates (30 L/min) and larger micro-aerosols lead to highest doses in the vestibule and nasal valve regions. On the other hand, the highest drug doses in the nasopharynx are observed for nano-aerosol (1 nm) and fine microparticles (1-20 µm) with a relatively weak dependence on flow rate. Furthermore, using the 45 different inhalation scenarios generated by numerical models, different machine learning models with five-fold cross-validation are trained to predict the delivered dose and avoid partial differential equation solvers for future predictions. Random forest and gradient boosting models resulted in R2 scores of 0.89 and 0.96, respectively. The aerosol diameter and region of interest are the most important features affecting delivered dose, with an approximate importance of 42% and 47%, respectively.
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Sach-SW:machine learning
 nanodrug delivery
 nasal drug delivery
 numerical modelling
 targeted drug delivery
Verknüpfungen:→ Zeitschrift

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