Supplementary materials for machine learning-driven multifunctional peptide engineering for sustained ocular drug delivery

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dc.contributor.advisorCummings, Michael P.
dc.contributor.advisorEnsign, Laura M.
dc.contributor.authorChou, Renee Ti
dc.contributor.authorHsueh, Henry T.
dc.contributor.authorRai, Usha
dc.contributor.authorLiyanage, Wathsala
dc.contributor.authorKim, Yoo Chun
dc.contributor.authorAppell, Matthew B.
dc.contributor.authorPejavar, Jahnavi
dc.contributor.authorLeo, Kirby T.
dc.contributor.authorDavison, Charlotte
dc.contributor.authorKolodziejski, Patricia
dc.contributor.authorMozzer, Ann
dc.contributor.authorKwon, HyeYoung
dc.contributor.authorSista, Maanasa
dc.contributor.authorAnders, Nicole M.
dc.contributor.authorHemingway, Avelina
dc.contributor.authorRompicharla, Sri Vishnu Kiran
dc.contributor.authorEdwards, Malia
dc.contributor.authorPitha, Ian
dc.contributor.authorHanes, Justin
dc.contributor.authorCummings, Michael P.
dc.contributor.authorEnsign, Laura M.
dc.date.accessioned2023-01-27T22:09:47Z
dc.date.available2023-01-27T22:09:47Z
dc.date.issued2023
dc.descriptionThe research notebook contains the code of the machine learning pipeline developed in the project, which involves a super learner-based methodology for multifunctional peptide engineering. The main pipeline consists of variable reduction and model training. The code functionality details can be found in the Methods section of the paper "Machine learning-driven multifunctional peptide engineering for sustained ocular drug delivery."en_US
dc.description.abstractSustained drug delivery strategies have many potential benefits for treating a range of diseases, particularly chronic diseases that require treatment for years. For many chronic ocular diseases, patient adherence to eye drop dosing regimens and the need for frequent intraocular injections are significant barriers to effective disease management. Here, we utilize peptide engineering to impart melanin binding properties to peptide-drug conjugates to act as a sustained-release depot in the eye. We developed a super learning-based methodology to engineer multifunctional peptides that efficiently enter cells, bind to melanin, and have low cytotoxicity. When the lead multifunctional peptide (HR97) was conjugated to brimonidine, an intraocular pressure (IOP)-lowering drug that is prescribed for three times per day topical dosing, IOP reduction was observed for up to 18 days after a single intracameral HR97-brimonidine injection in rabbits. Further, the cumulative IOP-lowering effect was increased ~17-fold compared to free brimonidine injection. Engineered multifunctional peptide-drug conjugates are a promising approach for providing sustained therapeutic delivery in the eye and beyond.en_US
dc.description.sponsorshipNational Institutes of Health (NIH) (grant nos. R01EY026578 and R01EY031041; National Eye Institute Training Grant (T32EY007143); National Science Foundation Award (DGE-1632976)en_US
dc.identifierhttps://doi.org/10.13016/0jck-hnnv
dc.identifier.urihttp://hdl.handle.net/1903/29529
dc.language.isoen_USen_US
dc.relation.isAvailableAtLibrary Research & Innovative Practice Forum
dc.relation.isAvailableAtDigital Repository at the University of Maryland
dc.relation.isAvailableAtUniversity of Maryland (College Park, Md)
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/us/*
dc.subjectmachine learningen_US
dc.subjectdrug deliveryen_US
dc.titleSupplementary materials for machine learning-driven multifunctional peptide engineering for sustained ocular drug deliveryen_US
dc.typeSoftwareen_US

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