Physiologically based pharmacokinetic modelling 2: predicting the tissue distribution of acids, very weak bases, neutrals and zwitterions. 2006

Trudy Rodgers, and Malcolm Rowland
Centre for Applied Pharmacokinetic Research, School of Pharmacy and Pharmaceutical Sciences, The University of Manchester, England. trudy.rogers@manchester.ac.uk

A key component of whole body physiologically based pharmacokinetic (WBPBPK) models is the tissue-to-plasma water partition coefficients (Kpu's). The predictability of Kpu values using mechanistically derived equations has been investigated for 7 very weak bases, 20 acids, 4 neutral drugs and 8 zwitterions in rat adipose, bone, brain, gut, heart, kidney, liver, lung, muscle, pancreas, skin, spleen and thymus. These equations incorporate expressions for dissolution in tissue water and, partitioning into neutral lipids and neutral phospholipids. Additionally, associations with acidic phospholipids were incorporated for zwitterions with a highly basic functionality, or extracellular proteins for the other compound classes. The affinity for these cellular constituents was determined from blood cell data or plasma protein binding, respectively. These equations assume drugs are passively distributed and that processes are nonsaturating. Resultant Kpu predictions were more accurate when compared to published equations, with 84% as opposed to 61% of the predicted values agreeing with experimental values to within a factor of 3. This improvement was largely due to the incorporation of distribution processes related to drug ionisation, an issue that is not addressed in earlier equations. Such advancements in parameter prediction will assist WBPBPK modelling, where time, cost and labour requirements greatly deter its application.

UI MeSH Term Description Entries
D008954 Models, Biological Theoretical representations that simulate the behavior or activity of biological processes or diseases. For disease models in living animals, DISEASE MODELS, ANIMAL is available. Biological models include the use of mathematical equations, computers, and other electronic equipment. Biological Model,Biological Models,Model, Biological,Models, Biologic,Biologic Model,Biologic Models,Model, Biologic
D010599 Pharmacokinetics Dynamic and kinetic mechanisms of exogenous chemical DRUG LIBERATION; ABSORPTION; BIOLOGICAL TRANSPORT; TISSUE DISTRIBUTION; BIOTRANSFORMATION; elimination; and DRUG TOXICITY as a function of dosage, and rate of METABOLISM. LADMER, ADME and ADMET are abbreviations for liberation, absorption, distribution, metabolism, elimination, and toxicology. ADME,ADME-Tox,ADMET,Absorption, Distribution, Metabolism, Elimination, and Toxicology,Absorption, Distribution, Metabolism, and Elimination,Drug Kinetics,Kinetics, Drug,LADMER,Liberation, Absorption, Distribution, Metabolism, Elimination, and Response
D010743 Phospholipids Lipids containing one or more phosphate groups, particularly those derived from either glycerol (phosphoglycerides see GLYCEROPHOSPHOLIPIDS) or sphingosine (SPHINGOLIPIDS). They are polar lipids that are of great importance for the structure and function of cell membranes and are the most abundant of membrane lipids, although not stored in large amounts in the system. Phosphatides,Phospholipid
D011237 Predictive Value of Tests In screening and diagnostic tests, the probability that a person with a positive test is a true positive (i.e., has the disease), is referred to as the predictive value of a positive test; whereas, the predictive value of a negative test is the probability that the person with a negative test does not have the disease. Predictive value is related to the sensitivity and specificity of the test. Negative Predictive Value,Positive Predictive Value,Predictive Value Of Test,Predictive Values Of Tests,Negative Predictive Values,Positive Predictive Values,Predictive Value, Negative,Predictive Value, Positive
D001798 Blood Proteins Proteins that are present in blood serum, including SERUM ALBUMIN; BLOOD COAGULATION FACTORS; and many other types of proteins. Blood Protein,Plasma Protein,Plasma Proteins,Serum Protein,Serum Proteins,Protein, Blood,Protein, Plasma,Protein, Serum,Proteins, Blood,Proteins, Plasma,Proteins, Serum
D001825 Body Fluid Compartments The two types of spaces between which water and other body fluids are distributed: extracellular and intracellular. Body Fluid Compartment,Compartment, Body Fluid,Compartments, Body Fluid,Fluid Compartment, Body,Fluid Compartments, Body
D003198 Computer Simulation Computer-based representation of physical systems and phenomena such as chemical processes. Computational Modeling,Computational Modelling,Computer Models,In silico Modeling,In silico Models,In silico Simulation,Models, Computer,Computerized Models,Computer Model,Computer Simulations,Computerized Model,In silico Model,Model, Computer,Model, Computerized,Model, In silico,Modeling, Computational,Modeling, In silico,Modelling, Computational,Simulation, Computer,Simulation, In silico,Simulations, Computer
D004912 Erythrocytes Red blood cells. Mature erythrocytes are non-nucleated, biconcave disks containing HEMOGLOBIN whose function is to transport OXYGEN. Blood Cells, Red,Blood Corpuscles, Red,Red Blood Cells,Red Blood Corpuscles,Blood Cell, Red,Blood Corpuscle, Red,Erythrocyte,Red Blood Cell,Red Blood Corpuscle
D000442 Octanols Isomeric forms and derivatives of octanol (C8H17OH). Alcohols, Octyl,Heptylcarbinols,Hydroxyoctanes,Octylic Alcohols,Alcohols, Octylic,Octyl Alcohols
D000818 Animals Unicellular or multicellular, heterotrophic organisms, that have sensation and the power of voluntary movement. Under the older five kingdom paradigm, Animalia was one of the kingdoms. Under the modern three domain model, Animalia represents one of the many groups in the domain EUKARYOTA. Animal,Metazoa,Animalia

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