{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T23:24:52Z","timestamp":1788909892636,"version":"build-2803163510"},"reference-count":64,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T00:00:00Z","timestamp":1765497600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2339001"],"award-info":[{"award-number":["2339001"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Drug Deliv."],"abstract":"\n Introduction<\/jats:title>\n Improving the efficacy of nasal sprays by enhancing targeted drug delivery to intra-airway tissue sites prone to infection onset is hypothesized to be achievable through an optimization of key device and formulation parameters, such as the sprayed droplet sizes, the spray cone angle, and the formulation density. This study focuses on the nasopharynx, a primary locus of early viral entry, as the optimal target for intranasal drug delivery.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n \n Two full-scale three-dimensional anatomical upper airway geometries reconstructed from high-resolution computed tomography scans were used to numerically evaluate a cone injection approach, with inert particles mimicking the motion of sprayed droplets within an underlying inhaled airflow field of 15\u00a0L\/min, commensurate with relaxed breathing conditions. Therein we have considered monodisperse sprayed particles sized between 10\u201350\n \n \n \n \u03bc<\/mml:mi>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n m, six material densities ranging from 1.0\u20131.5\u00a0g\/mL for the constituent formulation, and twelve plume angles spanning 15\n \n \n \n \n \u00a0<\/mml:mo>\n \u00b0<\/mml:mo>\n <\/mml:msup>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n \u2013 70\n \n \n \n \n \u00a0<\/mml:mo>\n \u00b0<\/mml:mo>\n <\/mml:msup>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n subtended by the spray jet at the nozzle position. Large Eddy Simulation-based modeling of the inhaled airflow physics within the anatomical domains was coupled with a Lagrangian particle-tracking framework to derive the drug deposition trend at the nasopharynx.\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n The resulting three-dimensional deposition contour map, obtained by interpolating the outcomes for the discrete test parameters, revealed that the mean nasopharyngeal deposition rate peaked for particle sizes\n \n \n \n d<\/mml:mi>\n \u2208<\/mml:mo>\n \u2009<\/mml:mtext>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n [25, 45]\n \n \n \n \u03bc<\/mml:mi>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n m and plume angles\n \n \n \n \u03b8<\/mml:mi>\n \u2272<\/mml:mo>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n 30\n \n \n \n \n \u00a0<\/mml:mo>\n \u00b0<\/mml:mo>\n <\/mml:msup>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n , with the deposition rates averaged over the test airway geometries and formulation densities. That mean deposition rate at the nasopharynx was approximately 11.4% within the specified\n \n \n \n {<\/mml:mo>\n \n d<\/mml:mi>\n ,<\/mml:mo>\n \u03b8<\/mml:mi>\n <\/mml:mrow>\n }<\/mml:mo>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n parametric bounds. In addition, the formulation density of 1.0\u00a0g\/mL yielded the highest mean deposition rate, over the comprehensive tested range of sprayed particle sizes and plume angles. A subset of the simulated nasopharyngeal deposition trends was experimentally validated through representative physical spray tests conducted in a 3D-printed replica of one of the test geometries.\n <\/jats:p>\n <\/jats:sec>\n \n Discussion<\/jats:title>\n The overall findings, while implicitly tied to the two test subjects (i.e., for spray administration through four representative nasal pathways), do collectively demonstrate that rational optimization of the intranasal sprays for targeted nasopharyngeal deposition is attainable with actionable design modifications on the sprayed droplet sizes and device plume angles.<\/jats:p>\n <\/jats:sec>","DOI":"10.3389\/fddev.2025.1721960","type":"journal-article","created":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T11:26:08Z","timestamp":1765538768000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Mechanics-guided parametric modeling of intranasal spray devices and formulations for targeted drug delivery to the nasopharynx"],"prefix":"10.3389","volume":"5","author":[{"given":"Md Tariqul","family":"Hossain","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abir","family":"Malakar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammad","family":"Yeasin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"William","family":"O\u2019Connell","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammad Mehedi Hasan","family":"Akash","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Azadeh A. 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