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dc.contributor.advisorKorzekwa, Kenneth R.
dc.creatorHolt, Kimberly
dc.date.accessioned2020-10-26T19:19:25Z
dc.date.available2020-10-26T19:19:25Z
dc.date.issued2019
dc.identifier.urihttp://hdl.handle.net/20.500.12613/1455
dc.description.abstractWith the growing use of physiologically-based pharmacokinetic (PBPK) modeling to predict the pharmacokinetics of a drug, accurate prediction of the tissue: plasma water partition coefficients (Kp,m) has become increasingly important. In these predictions, drug-lipid interactions have been traditionally described using the octanol: water partition coefficient (logP) and the vegetable: oil: water partition coefficient (logPvo). However, the logP does not fully represent all of the drug interactions with phospholipids, while the logPvo is calculated from the logP and not determined experimentally. Partitioning into microsomes has been used as a potential surrogate for phospholipid partitioning in our previous steady-state volume of distribution prediction method. Microsomal partitioning is able to act as a total phospholipid partitioning term, representing both acidic and neutral phospholipid interactions. Partitioning into adipocytes potentially can provide an alternative surrogate for d
dc.format.extent161 pages
dc.language.isoeng
dc.publisherTemple University. Libraries
dc.relation.ispartofTheses and Dissertations
dc.rightsIN COPYRIGHT- This Rights Statement can be used for an Item that is in copyright. Using this statement implies that the organization making this Item available has determined that the Item is in copyright and either is the rights-holder, has obtained permission from the rights-holder(s) to make their Work(s) available, or makes the Item available under an exception or limitation to copyright (including Fair Use) that entitles it to make the Item available.
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectPharmaceutical Sciences
dc.titleEvaluation of different in vitro surrogates to represent nonspecific binding for tissue: plasma water partition coefficient predictions
dc.typeText
dc.type.genreThesis/Dissertation
dc.contributor.committeememberKorzekwa, Kenneth
dc.contributor.committeememberNagar, Swati V.
dc.contributor.committeememberChilders, Wayne E.
dc.contributor.committeememberBarrero, Carlos
dc.contributor.committeememberGibson, Christopher
dc.description.departmentPharmaceutical Sciences
dc.relation.doihttp://dx.doi.org/10.34944/dspace/1437
dc.ada.noteFor Americans with Disabilities Act (ADA) accommodation, including help with reading this content, please contact scholarshare@temple.edu
dc.description.degreePh.D.
refterms.dateFOA2020-10-26T19:19:25Z


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