کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
10162468 1114330 2014 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Predicting Passive and Active Tissue:Plasma Partition Coefficients: Interindividual and Interspecies Variability
ترجمه فارسی عنوان
پیش بینی شیوه های غیرفعال و فعال: ضرایب پراکندگی پلاسما: متغیر بین فردی و بین گونه ای
موضوعات مرتبط
علوم پزشکی و سلامت داروسازی، سم شناسی و علوم دارویی اکتشاف دارویی
چکیده انگلیسی
A mechanistic tissue composition Model incorporating passive and active transport for the prediction of steady-state tissue:plasma partition coefficients (Kt:pl) of chemicals in multiple mammalian species was used to assess interindividual and interspecies variability. This approach predicts Kt:pl using chemical lipophilicity, pKa, phospholipid membrane binding, and the unbound plasma fraction, together with tissue fractions of water, neutral lipids, neutral and acidic phospholipids, proteins, and pH. Active transport Kt:pl is predicted using Michaelis-Menten transport parameters. Species-specific biological properties were identified from 126 peer reviewed journal articles, listed in the Supporting Information, for Mouse, rat, guinea pig, rabbit, beagle dog, pig, Monkey, and human species. Means and coefficients of variation for biological properties were used in a Monte Carlo analysis to assess variability. The results show Kt:pl interspecies variability for the brain, fat, heart, kidney, liver, lung, muscle, red blood cell, skin, and spleen, but uncertainty in the estimates obscured some differences. Compounds undergoing active transport are shown to have concentration-dependent Kt:pl. This tissue composition-based mechanistic Model can be used to predict Kt:pl for organic chemicals across eight species and 10 tissues, and can be an important component in drug development when scaling Kt:pl from animal Models to humans.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Pharmaceutical Sciences - Volume 103, Issue 7, July 2014, Pages 2189-2198
نویسندگان
, , , , ,