Predictions of hepatic disposition properties using a mechanistically realistic, physiologically based model.

Predictions of hepatic disposition properties using a mechanistically realistic, physiologically based model. Research Abstract Details 

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Predictions of hepatic disposition properties using a mechanistically realistic, physiologically based model. Abstract Text:

Li Yan,Shahab Sheihk-Bahaei,Sunwoo Park,Glen E P Ropella,C Anthony Hunt,

Quantitative mappings were established between drug physicochemical properties (PCPs) and parameter values of a physiologically based, mechanistically realistic, in silico liver (ISL). The ISL plugs together autonomous software objects that represent hepatic components at different scales and levels of detail. Microarchitectural features are represented separately from the mechanisms that influence drug metabolism. The same ISL has been validated against liver perfusion data for sucrose and four cationic drugs: antipyrine, atenolol, labetalol, and diltiazem. Parameters sensitive to drug-specific PCPs were tuned so that ISL outflow profiles from a single ISL matched in situ perfused rat liver outflow profiles of all five compounds. Quantitative relationships were then established between the four sets of drug PCPs and the corresponding four sets of PCP-sensitive, ISL parameter values; those relationships were used to predict PCP-sensitive, ISL parameter values for prazosin and propranolol given only their PCPs. Relationships were established using three different methods: 1) a simple linear correlation method, 2) the fuzzy c-means algorithm, and 3) a simple artificial neural network. Each relationship was used separately to predict ISL parameter values for prazosin and propranolol, given their PCPs. Those values were applied in the ISL used earlier to predict the hepatic disposition details for each drug. Although we had only sparse data available, all predicted disposition profiles were judged reasonable (within a factor of 2 of referent profile data). The order of precision, based on a similarity measure, was 3 > 2 > 1.

Predictions of hepatic disposition properties using a mechanistically realistic, physiologically based model. Publishing Authors By Initials

L Yan,S Sheihk-Bahaei,S Park,GE Ropella,CA Hunt,

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Predictions of hepatic disposition properties using a mechanistically realistic, physiologically based model. Journal Published:

PUBLICATION TYPE: Research Support, Non-U.S. Gov

Journal: Drug metabolism and disposition: the biological fa

VOLUME: 36

Page Numbers: 759-68

Journal Abbreviation: Drug Metab. Dispos.

ISSN: 1521-009X

DAY: 28

MONTH: 01

YEAR: 2008

Predictions of hepatic disposition properties using a mechanistically realistic, physiologically based model. Information

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LANGUAGE: eng

NlmUniqueID: 9421550

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Grant and Affiliation Information for Predictions of hepatic disposition properties using a mechanistically realistic, physiologically based model.

AFFILIATION: The UCSF/UCB Joint Graduate Group in Bioengineering, University of California, Berkeley and San Francisco, California, USA.

Country: United States

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MEDLINETA: Drug Metab Dispos

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