Predicting passive and active tissue:Plasma partition coefficients: Interindividual and interspecies variability

Journal of Pharmaceutical Sciences

Volumn 103, Issue 7, 2014, Pages 2189-2198

  Ruark, Christopher D ^a,b   Hack, C Eric ^a   Robinson, Peter J ^a   Mahle, Deirdre A ^c   Gearhart, Jeffery M ^a  

^a AIR FORCE RESEARCH LABORATORY   (United States)

^b WRIGHT STATE UNIVERSITY   (United States)

^c USAF   (United States)

Author keywords

active transport; computational ADME; computational biology; drug transport; in silico modeling; Monte Carlo; physicochemical properties; population pharmacokinetic pharmacodynamic models; QSPR; tissue partition

Indexed keywords

ADENOSINE TRIPHOSPHATE; FAT; MULTIDRUG RESISTANCE PROTEIN; ORGANIC COMPOUND; PHOSPHOLIPID; PROTEIN; WATER; XENOBIOTIC AGENT; DRUG;

ACTIVE TRANSPORT; ANIMAL EXPERIMENT; ANIMAL TISSUE; ARTICLE; BEAGLE; BRAIN; CALCULATION; COMPUTER MODEL; DRUG TRANSPORT; ERYTHROCYTE; EXPERIMENTAL ANIMAL; EXPERIMENTAL DOG; EXPERIMENTAL GUINEA PIG; EXPERIMENTAL MONKEY; EXPERIMENTAL PIG; EXPERIMENTAL RABBIT; HEART; HUMAN; KIDNEY; LIVER; LUNG; MAMMAL; MEMBRANE PERMEABILITY; MEMBRANE TRANSPORT; MODEL; MONTE CARLO METHOD; MOUSE; MUSCLE; NONHUMAN; PARTITION COEFFICIENT; PASSIVE TRANSPORT; PH; PHOSPHOLIPID MEMBRANE; PLASMA; PREDICTION; QUANTITATIVE STRUCTURE PROPERTY RELATION; RAT; SKIN; SPECIES DIFFERENCE; SPLEEN; TISSUE SPECIFICITY; XENOBIOTIC METABOLISM; ANIMAL; ANTIBODY SPECIFICITY; BIOLOGICAL MODEL; BLOOD; DOG; FORECASTING; GUINEA PIG; HAPLORHINI; METABOLISM; RABBIT; SWINE; TISSUE DISTRIBUTION;

ANIMALS; BIOLOGICAL TRANSPORT, ACTIVE; DOGS; FORECASTING; GUINEA PIGS; HAPLORHINI; MICE; MODELS, BIOLOGICAL; MONTE CARLO METHOD; ORGAN SPECIFICITY; PHARMACEUTICAL PREPARATIONS; RABBITS; RATS; SPECIES SPECIFICITY; SWINE; TISSUE DISTRIBUTION;

EID: 84903142184     PISSN: 00223549     EISSN: 15206017     Source Type: Journal    
DOI: 10.1002/jps.24011     Document Type: Article

References (28)

1. Schmitt W,. 2008. General approach for the calculation of tissue to plasma partition coefficients. Toxicol In Vitro 22: 457-467. (Pubitemid 351163539)
2. Rodgers T, Leahy D, Rowland M,. 2005. Physiologically based pharmacokinetic modeling 1: Predicting the tissue distribution of moderate-to-strong bases. J Pharm Sci 94: 1259-1276. (Pubitemid 40904190)
3. Krishnan K, Andersen ME,. 2001. Physiologically based pharmacokinetic modeling in toxicology. In Principles and methods of toxicology;, Hayes AW, Ed. Philadelphia, Pennsylvania: Taylor and Francis Ch. 5, pp 193-241.
4. Rodgers T, Jones HM, Rowland M,. 2012. Pharmacokinetics, pharmacodynamics and drug metabolism tissue lipids and drug distribution: Dog versus rat. J Pharm Sci 101: 4615-4626.
5. Syvanen S, Lindhe O, Palner M, Kornum BR, Rahman O, Langstrom B, Knudsen GM, Hammarlund-Udenaes M,. 2009. Species differences in blood-brain barrier transport of three positron emission tomography radioligands with emphasis on p-glycoprotein transport. Drug Metab Dispos 37: 635-643.
6. Dallas CE, Chen XM, Muralidhara S, Varkonyi P, Tackett RL, Bruchner JV,. 1994. Use of tissue disposition data from rats and dogs to determine species differences in input parameters for a physiological model for perchloroethylene. Environ Res 67: 54-67. (Pubitemid 24322334)
7. Gargas ML, Burgess RJ, Voisard DE, Cason GH, Andersen ME,. 1989. Partition coefficients of low-molecular-weight volatile chemicals in various liquids and tissues. Toxicol Appl Pharmacol 98: 87-99. (Pubitemid 19094137)
8. Terasaki T, Iga T, Sugiyama Y, Hanano M,. 1984. Pharmacokinetic study on the mechanism of tissue distribution of doxorubicin: Interorgan and interspecies variation of tissue-to-plasma partition coefficients in rats, rabbits, and guinea pigs. J Pharm Sci 73: 1359-1363. (Pubitemid 14021881)
9. Chignell CF, Starkweather DK,. 1971. Species differences in the binding of phenylbutazone to plasma albumin. Pharmacology 5: 235-244.
10. Jepson GW, Hoover DK, Black RK, McCafferty JD, Mahle DA, Gearhart JM,. 1994. A partition coefficient determination method for nonvolatile chemicals in biological tissues. Fund Appl Toxicol 22: 519-524. (Pubitemid 24194715)
11. Poulin P, Theil FP,. 2000. A priori prediction of tissue:plasma partition coefficients of drugs to facilitate the use of physiologically-based pharmacokinetic models in drug discovery. J Pharm Sci 89: 16-35. (Pubitemid 30080151)
12. Poulin P, Krishnan K,. 1995a. A biologically-based algorithm for predicting human tissue:blood partition coefficients of organic chemicals. Human Exp Toxicol 14: 273-280.
13. Poulin P, Krishnan K,. 1995b. An algorithm for predicting tissue:blood partition coefficients of organic chemicals from n-octanol:water partition coefficient data. J Toxicol Environ Health 46: 117-129.
14. Poulin P, Krishnan K,. 1996a. A tissue composition-based algorithm for predicting tissue:air partition coefficients of organic chemicals. Toxicol Appl Pharmacol 136: 126-130. (Pubitemid 26049718)
15. Poulin P, Krishnan K,. 1996b. Molecular structure-based prediction of the partition coefficients of organic chemicals for physiological pharmacokinetic models. Toxicol Methods 6: 117-137.
16. Poulin P, Krishnan K,. 1996c. A mechanistic algorithm for predicting blood air partition coefficients of organic chemicals with the consideration of reversible binding in hemoglobin. Toxicol Appl Pharmacol 136: 131-137. (Pubitemid 26049719)
17. Poulin P, Theil FP,. 2002. Prediction of pharmacokinetics prior to in vivo studies. II. Generic physiologically based pharmacokinetic models of drug disposition. J Pharm Sci 91: 1358-1370. (Pubitemid 34651198)
18. Poulin P, Schoenlein K, Theil FP,. 2001. Prediction of adipose tissue:plasma partition coefficients for structurally unrelated drugs. J Pharm Sci 90: 436-447.
19. Poulin P, Hop CE, Salphati L, Liederer BM,. 2013. Correlation of tissue-plasma partition coefficients between normal tissues and subcutaneous xenografts of human tumor cell lines in mouse as a prediction tool of drug penetration in tumors. J Pharm Sci 102: 1355-1369.
20. Rodgers T, Rowland M,. 2006. Physiologically based pharmacokinetic modelling 2: Predicting the tissue distribution of acids, very weak bases, neutrals and zwitterions. J Pharm Sci 95: 1238-1257. (Pubitemid 43874439)
21. Yun YE, Edginton AN,. 2013. Correlation-based prediction of tissue-to-plasma partition coefficients using readily available input parameters. Xenobiotica 43: 839-852.
22. Zhang H,. 2004. A new nonlinear equation for the tissue/blood partition coefficients of neutral compounds. J Pharm Sci 93: 1595-1604. (Pubitemid 38725030)
23. Zhang H, Zhang Y,. 2006. Convenient nonlinear model for predicting the tissue/blood partition coefficients of seven human tissues of neutral, acidic, and basic structurally diverse compounds. J Med Chem 49: 5815-5829. (Pubitemid 44423718)
24. Reifenrath W, Kemppainen BW, Palmer WG,. 1996. An in vitro pig skin model for predicting human skin penetration and irritation potential. In Advances in swine in biomedical research. Vol. 2, Springer Science+Business Media, New York, pp 459-474.
25. Dobson PD, Kell DB,. 2008. Carrier-mediated cellular uptake of pharmaceutical drugs: An exception or the rule. Nat Rev Drug Discov 7: 205-220. (Pubitemid 351321232)
26. Loo TW, Clarke DM,. 1999. Molecular dissection of the human multidrug resistance P-glycoprotein. Biochem Cell Biol 77: 11-23. (Pubitemid 29342829)
27. Shirasaka Y, Nakamura T, Sakaeda T, Okumura K, Langguth P, Yamashita S,. 2006. Induction of human P-glycoprotein in Caco-2 cells: Development of a highly sensitive assay system for P-glycoprotein-mediated drug transport. Drug Metab Pharmacokinet 21: 414-423.
28. Shirasaka Y, Masaoka Y, Kataoka M, Sakuma S, Yamashita S,. 2008. Scaling of in vitro membrane permeability to predict p-glycoprotein-mediated drug absorption in vivo. Drug Metab Dispos 36: 916-922. (Pubitemid 351574890)