{"title":"Drug Delivery from A Ring Implant Attached to Intraocular Lens: An In-Silico Investigation.","authors":"Pawan Kumar Pandey, Manish Jain, Prateek K Jha","doi":"10.1016/j.xphs.2024.09.001","DOIUrl":null,"url":null,"abstract":"<p><p>Multiple iterations required to design ocular implants, which will last for the desired operational period of months or even years, necessitate the use of in-silico models for ocular drug delivery. In this study, we developed an in-silico model to simulate the flow of Aqueous Humor (AH) and drug delivery from an implant to the Trabecular Meshwork (TM). The implant, attached to the side of the intraocular lens (IOL), and the TM are treated as porous media, with their effects on AH flow accounted for using the Darcy equation. This model accurately predicts the physiological values of Intraocular Pressure (IOP) for both healthy individuals and glaucoma patients, as reported in the literature. Results reveal that the effective diffusivity of the drug within the implant is the critical parameter that can alter the bioavailability time period (BTP) from a few days to months. Intuitively, BTP should increase as effective diffusivity decreases. However, we discovered that with lower levels of initial drug loading, BTP declines when effective diffusivity falls below a specific threshold. Our findings further reveal that, while AH flow has a minimal effect on the drug release profile at the implant site, it significantly impacts drug availability at the TM.</p>","PeriodicalId":16741,"journal":{"name":"Journal of pharmaceutical sciences","volume":null,"pages":null},"PeriodicalIF":3.7000,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of pharmaceutical sciences","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.xphs.2024.09.001","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, MEDICINAL","Score":null,"Total":0}
引用次数: 0
Abstract
Multiple iterations required to design ocular implants, which will last for the desired operational period of months or even years, necessitate the use of in-silico models for ocular drug delivery. In this study, we developed an in-silico model to simulate the flow of Aqueous Humor (AH) and drug delivery from an implant to the Trabecular Meshwork (TM). The implant, attached to the side of the intraocular lens (IOL), and the TM are treated as porous media, with their effects on AH flow accounted for using the Darcy equation. This model accurately predicts the physiological values of Intraocular Pressure (IOP) for both healthy individuals and glaucoma patients, as reported in the literature. Results reveal that the effective diffusivity of the drug within the implant is the critical parameter that can alter the bioavailability time period (BTP) from a few days to months. Intuitively, BTP should increase as effective diffusivity decreases. However, we discovered that with lower levels of initial drug loading, BTP declines when effective diffusivity falls below a specific threshold. Our findings further reveal that, while AH flow has a minimal effect on the drug release profile at the implant site, it significantly impacts drug availability at the TM.
期刊介绍:
The Journal of Pharmaceutical Sciences will publish original research papers, original research notes, invited topical reviews (including Minireviews), and editorial commentary and news. The area of focus shall be concepts in basic pharmaceutical science and such topics as chemical processing of pharmaceuticals, including crystallization, lyophilization, chemical stability of drugs, pharmacokinetics, biopharmaceutics, pharmacodynamics, pro-drug developments, metabolic disposition of bioactive agents, dosage form design, protein-peptide chemistry and biotechnology specifically as these relate to pharmaceutical technology, and targeted drug delivery.