@article{nixon_chittenden_baynes_messenger_2022, title={Pharmacokinetic/pharmacodynamic modeling of ketoprofen and flunixin at piglet castration and tail-docking}, volume={7}, ISSN={["1365-2885"]}, url={https://doi.org/10.1111/jvp.13083}, DOI={10.1111/jvp.13083}, abstractNote={Abstract}, journal={JOURNAL OF VETERINARY PHARMACOLOGY AND THERAPEUTICS}, publisher={Wiley}, author={Nixon, Emma and Chittenden, Jason T. and Baynes, Ronald E. and Messenger, Kristen M.}, year={2022}, month={Jul} }
 @article{li_cheng_chittenden_baynes_tell_davis_vickroy_riviere_lin_2019, title={Integration of Food Animal Residue Avoidance Databank (FARAD) empirical methods for drug withdrawal interval determination with a mechanistic population-based interactive physiologically based pharmacokinetic (iPBPK) modeling platform: example for flunixin meglumine administration}, volume={93}, ISSN={0340-5761 1432-0738}, url={http://dx.doi.org/10.1007/s00204-019-02464-z}, DOI={10.1007/s00204-019-02464-z}, abstractNote={Violative chemical residues in animal-derived food products affect food safety globally and have impact on the trade of international agricultural products. The Food Animal Residue Avoidance Databank program has been developing scientific tools to provide appropriate withdrawal interval (WDI) estimations after extralabel drug use in food animals for the past three decades. One of the tools is physiologically based pharmacokinetic (PBPK) modeling, which is a mechanistic-based approach that can be used to predict tissue residues and WDIs. However, PBPK models are complicated and difficult to use by non-modelers. Therefore, a user-friendly PBPK modeling framework is needed to move this field forward. Flunixin was one of the top five violative drug residues identified in the United States from 2010 to 2016. The objective of this study was to establish a web-based user-friendly framework for the development of new PBPK models for drugs administered to food animals. Specifically, a new PBPK model for both cattle and swine after administration of flunixin meglumine was developed. Population analysis using Monte Carlo simulations was incorporated into the model to predict WDIs following extralabel administration of flunixin meglumine. The population PBPK model was converted to a web-based interactive PBPK (iPBPK) framework to facilitate its application. This iPBPK framework serves as a proof-of-concept for further improvements in the future and it can be applied to develop new models for other drugs in other food animal species, thereby facilitating the application of PBPK modeling in WDI estimation and food safety assessment.}, number={7}, journal={Archives of Toxicology}, publisher={Springer Science and Business Media LLC}, author={Li, Miao and Cheng, Yi-Hsien and Chittenden, Jason T. and Baynes, Ronald E. and Tell, Lisa A. and Davis, Jennifer L. and Vickroy, Thomas W. and Riviere, Jim E. and Lin, Zhoumeng}, year={2019}, month={Apr}, pages={1865–1880} }
 @article{chittenden_riviere_2016, title={Assessment of penetrant and vehicle mixture properties on transdermal permeability using a mixed effect pharmacokinetic model of ex vivo porcine skin}, volume={37}, ISSN={0142-2782}, url={http://dx.doi.org/10.1002/bdd.2018}, DOI={10.1002/bdd.2018}, abstractNote={Abstract}, number={7}, journal={Biopharmaceutics & Drug Disposition}, publisher={Wiley}, author={Chittenden, Jason T. and Riviere, Jim E.}, year={2016}, month={Oct}, pages={387–396} }
 @article{chittenden_riviere_2015, title={Quantification of vehicle mixture effects on in vitro transdermal chemical flux using a random process diffusion model}, volume={217}, ISSN={0168-3659}, url={http://dx.doi.org/10.1016/j.jconrel.2015.08.023}, DOI={10.1016/j.jconrel.2015.08.023}, abstractNote={The effect of vehicle mixtures on transdermal permeation has been studied using transient flux profiles from porcine skin flow through diffusion cells. Such data characteristically exhibit a large amount of variability between treatments (vehicle and penetrant combinations) as well as noise within treatments. A novel mathematical model has been used that describes longitudinal variation as a time varying diffusivity. Between treatment variability was described by a mixed effects model. A quantitative structure property relationship (QSPR) was developed to describe the effects of the penetrant and vehicle mixture properties on the mean diffusivity and partition coefficient in the membrane. The relationship included terms for the logP and molecular weight of the penetrant and the refractive index of the vehicle mixture with R(2)>0.95 for K and >0.9 for partition coefficient (as K⋅D). This analysis improved on previous work, finding a more parsimonious model with higher predictability, while still identifying the mixture refractive index as a key descriptor in predicting vehicle effects. The concordance with established and expected relationships lends confidence to this new methodology for evaluating transient, finite dose, transdermal flux data collected using traditional experimental methods.}, journal={Journal of Controlled Release}, publisher={Elsevier BV}, author={Chittenden, Jason T. and Riviere, Jim E.}, year={2015}, month={Nov}, pages={74–81} }