Evaluation and calibration of high-throughput predictions of chemical distribution to tissues

Journal of Pharmacokinetics and Pharmacodynamics

Volumn 44, Issue 6, 2017, Pages 549-565

  Pearce, Robert G ^a,b   Setzer, R Woodrow ^a   Davis, Jimena L ^a,c   Wambaugh, John F ^a  

^a U S ENVIRONMENTAL PROTECTION AGENCY   (United States)

^b OAK RIDGE INSTITUTE FOR SCIENCE AND EDUCATION   (United States)

^c SYNGENTA BIOTECHNOLOGY INC   (United States)

Author keywords

Distribution; High throughput toxicokinetics; httk; Partition coefficients; PBPK; PBTK; Physiologically based toxicokinetics; Statistical analysis; Volume of distribution

Indexed keywords

ANIMAL EXPERIMENT; ANIMAL MODEL; ANIMAL TISSUE; ARTICLE; DATA BASE; HUMAN; HUMAN CELL; MEMBRANE BIOLOGY; MODEL; NONHUMAN; PARTITION COEFFICIENT; PHYSICAL CHEMISTRY; PRIORITY JOURNAL; RAT; SOFTWARE; TISSUE DISTRIBUTION; TOXICOKINETICS; ADVERSE DRUG REACTION; ANIMAL; BIOLOGICAL MODEL; CALIBRATION; COMPUTER SIMULATION; DRUG EFFECT; HIGH THROUGHPUT SCREENING; METABOLISM; PHYSIOLOGY; PRECLINICAL STUDY; PROCEDURES; STANDARDS; STATISTICS AND NUMERICAL DATA; TOXICITY TESTING;

DRUG;

ANIMALS; CALIBRATION; COMPUTER SIMULATION; DRUG EVALUATION, PRECLINICAL; DRUG-RELATED SIDE EFFECTS AND ADVERSE REACTIONS; HIGH-THROUGHPUT SCREENING ASSAYS; HUMANS; MODELS, BIOLOGICAL; PHARMACEUTICAL PREPARATIONS; RATS; TISSUE DISTRIBUTION; TOXICITY TESTS;

EID: 85031421199     PISSN: 1567567X     EISSN: 15738744     Source Type: Journal    
DOI: 10.1007/s10928-017-9548-7     Document Type: Article

References (79)

1. Park YH, Lee K, Soltow QA, Strobel FH, Brigham KL, Parker RE, Wilson ME, Sutliff RL, Mansfield KG, Wachtman LM, Ziegler TR, Jones DP (2012) High-performance metabolic profiling of plasma from seven mammalian species for simultaneous environmental chemical surveillance and bioeffect monitoring. Toxicology 295(1–3):47–55. doi:10.1016/j.tox.2012.02.007
2. Rager JE, Strynar MJ, Liang S, McMahen RL, Richard AM, Grulke CM, Wambaugh JF, Isaacs KK, Judson R, Williams AJ, Sobus JR (2016) Linking high resolution mass spectrometry data with exposure and toxicity forecasts to advance high-throughput environmental monitoring. Environ Int 88:269–280. doi:10.1016/j.envint.2015.12.008
3. Judson R, Richard A, Dix D, Houck K, Elloumi F, Martin M, Cathey T, Transue TR, Spencer R, Wolf M (2008) ACToR—aggregated computational toxicology resource. Toxicol Appl Pharmacol 233(1):7–13
4. National Research Council (1983) Risk assessment in the federal government: managing the process. National Academies Press, Washington, DC. doi:10.17226/317
5. Thomas RS, Philbert MA, Auerbach SS, Wetmore BA, Devito MJ, Cote I, Rowlands JC, Whelan MP, Hays SM, Andersen ME (2013) Incorporating new technologies into toxicity testing and risk assessment: moving from 21st century vision to a data-driven framework. Toxicol Sci 136(1):4–18
6. Wetmore BA, Wambaugh JF, Allen B, Ferguson SS, Sochaski MA, Setzer RW, Houck KA, Strope CL, Cantwell K, Judson RS, LeCluyse E, Clewell HJ, Thomas RS, Andersen ME (2015) Incorporating high-throughput exposure predictions with dosimetry-adjusted in vitro bioactivity to inform chemical toxicity testing. Toxicol Sci 148(1):121–136. doi:10.1093/toxsci/kfv171
7. Rovida C, Hartung T (2009) Re-evaluation of animal numbers and costs for in vivo tests to accomplish REACH legislation requirements for chemicals—a report by the transatlantic think tank for toxicology (t (4)). Altex 26(3):187–208
8. Pellegatti M (2014) The debate on animal ADME studies in drug development: an update. Exp Opin Drug Metab Toxicol 10(12):1615–1620
9. Tolonen A, Pelkonen O (2013) Analytical challenges for conducting rapid metabolism characterization for QIVIVE. Toxicology. doi:10.1016/j.tox.2013.08.010
10. Wambaugh JF, Wetmore BA, Pearce R, Strope C, Goldsmith R, Sluka JP, Sedykh A, Tropsha A, Bosgra S, Shah I, Judson R, Thomas RS, Setzer RW (2015) Toxicokinetic triage for environmental chemicals. Toxicol Sci 147(1):55–67. doi:10.1093/toxsci/kfv118
11. Waters NJ, Jones R, Williams G, Sohal B (2008) Validation of a rapid equilibrium dialysis approach for the measurement of plasma protein binding. J Pharm Sci 97(10):4586–4595
12. Shibata Y, Takahashi H, Chiba M, Ishii Y (2002) Prediction of hepatic clearance and availability by cryopreserved human hepatocytes: an application of serum incubation method. Drug Metab Dispos 30(8):892–896
13. ® population-based ADME simulator. Exp Opin Drug Metab Toxicol 5(2):211–223
14. Lukacova V, Woltosz WS, Bolger MB (2009) Prediction of modified release pharmacokinetics and pharmacodynamics from in vitro, immediate release, and intravenous data. AAPS J 11(2):323–334
15. Wang Y-H (2010) Confidence assessment of the Simcyp time-based approach and a static mathematical model in predicting clinical drug-drug interactions for mechanism-based CYP3A inhibitors. Drug Metab Dispos 38(7):1094–1104. doi:10.1124/dmd.110.032177
16. O’Flaherty EJ (1981) Toxicants and drugs: kinetics and dynamics. Wiley, New York
17. Andersen ME (1995) Development of physiologically based pharmacokinetic and physiologically based pharmacodymamic models for applications in toxicology and risk assessment. Toxicol Lett 79(1):35–44
18. Campbell JL, Clewell RA, Gentry PR, Andersen ME, Clewell HJ (2012) Physiologically based pharmacokinetic/toxicokinetic modeling. Comput Toxicol I:439–499
19. Clewell HJ, Andersen ME (1985) Risk assessment extrapolations and physiological modeling. Toxicol Ind Health 1(4):111–134
20. Loizou GD, Hogg A (2011) MEGen: a physiologically based pharmacokinetic model generator. Front Pharmacol 2:56
21. Shiran M, Proctor N, Howgate E, Rowland-Yeo K, Tucker G, Rostami-Hodjegan A (2006) Prediction of metabolic drug clearance in humans: in vitro–in vivo extrapolation vs allometric scaling. Xenobiotica 36(7):567–580
22. Schmitt W (2008) General approach for the calculation of tissue to plasma partition coefficients. Toxicol In Vitro 22(2):457–467
23. 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(1):16–35
24. Payne MP, Kenny LC (2002) Comparison of models for the estimation of biological partition coefficients. J Toxicol Environ Health Part A 65(13):897–931
25. 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(6):1238–1257
26. Peyret T, Poulin P, Krishnan K (2010) A unified algorithm for predicting partition coefficients for PBPK modeling of drugs and environmental chemicals. Toxicol Appl Pharmacol 249(3):197–207
27. Ruark CD, Hack CE, Robinson PJ, Mahle DA, Gearhart JM (2014) Predicting passive and active tissue: plasma partition coefficients: interindividual and interspecies variability. J Pharm Sci 103(7):2189–2198
28. Zhu X-W, Sedykh A, Zhu H, Liu S-S, Tropsha A (2013) The use of pseudo-equilibrium constant affords improved QSAR models of human plasma protein binding. Pharm Res 30(7):1790–1798
29. Ingle BL, Veber BC, Nichols JW, Tornero-Velez R (2016) Informing the human plasma protein binding of environmental chemicals by machine learning in the pharmaceutical space: applicability domain and limits of predictability. J Chem Inf Model 56(11):2243–2252
30. Obach RS, Lombardo F, Waters NJ (2008) Trend analysis of a database of intravenous pharmacokinetic parameters in humans for 670 drug compounds. Drug Metab Dispos 36(7):1385–1405
31. Pearce RG, Setzer RW, Strope CL, Sipes NS, Wambaugh JF (2017) Httk: R package for high-throughput toxicokinetics. J Stat Softw 79(1):1–26
32. R Development Core Team (2010) R: A language and environment for statistical computing. R Foundation for Statistical Computing.
33. Pearce R, Strope C, Setzer RW, Sipes N, Wambaugh JF (2016) httk: r package for high-throughput toxicokinetics. J Stat Softw (in press)
34. Core Team R (2016) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna
35. Schmitt W (2008) Corrigendum to: “General approach for the calculation of tissue to plasma partition coefficients” [Toxicology in Vitro 22 (2008) 457–467]. Toxicol In Vitro 22(6):1666. doi:10.1016/j.tiv.2008.04.020
36. 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(6):1259–1276
37. Rodgers T, Leahy D, Rowland M (2005) Tissue distribution of basic drugs: Accounting for enantiomeric, compound and regional differences amongst β-blocking drugs in rat. J Pharm Sci 94(6):1237–1248
38. Gueorguieva I, Nestorov IA, Murby S, Gisbert S, Collins B, Dickens K, Duffy J, Hussain Z, Rowland M (2004) Development of a whole body physiologically based model to characterise the pharmacokinetics of benzodiazepines. 1: estimation of rat tissue-plasma partition ratios. J Pharmacokinet Pharmacodyn 31(4):269–298
39. Poulin P, Schoenlein K, Theil FP (2001) Prediction of adipose tissue: plasma partition coefficients for structurally unrelated drugs. J Pharm Sci 90(4):436–447
40. Björkman S (2002) Prediction of the volume of distribution of a drug: which tissue-plasma partition coefficients are needed? J Pharm Pharmacol 54(9):1237–1245
41. Yun Y, Edginton A (2013) Correlation-based prediction of tissue-to-plasma partition coefficients using readily available input parameters. Xenobiotica 43(10):839–852
42. Uchimura T, Kato M, Saito T, Kinoshita H (2010) Prediction of human blood-to-plasma drug concentration ratio. Biopharm Drug Dispos 31(5–6):286–297
43. Davies B, Morris T (1993) Physiological parameters in laboratory animals and humans. Pharm Res 10(7):1093–1095
44. Parham F, Kohn M, Matthews H, DeRosa C, Portier C (1997) Using structural information to create physiologically based pharmacokinetic models for all polychlorinated biphenyls: I. Tissue: blood partition coefficients. Toxicol Appl Pharmacol 144(2):340–347
45. Paixão P, Gouveia LF, Morais JA (2012) Prediction of the human oral bioavailability by using in vitro and in silico drug related parameters in a physiologically based absorption model. Int J Pharm 429(1):84–98
46. Naritomi Y, Terashita S, Kagayama A, Sugiyama Y (2003) Utility of hepatocytes in predicting drug metabolism: comparison of hepatic intrinsic clearance in rats and humans in vivo and in vitro. Drug Metab Dispos 31(5):580–588
47. Obach RS (1999) Prediction of human clearance of twenty-nine drugs from hepatic microsomal intrinsic clearance data: an examination of in vitro half-life approach and nonspecific binding to microsomes. Drug Metab Dispos 27(11):1350–1359
48. Strope C, Mansouri K, Clewell H, Rabinowitz JR, Stevens C, Wambaugh JF (2017) High-throughput in-silico prediction of ionization equilibria for pharmacokinetic modeling. Sci Total Environ (in press)
49. Strope CL, Mansouri K, Kancherla J, Stevens C, Wambaugh JF (2015) High-throughput pharmacokinetic modeling using computationally predicted parameter values: dissociation constants. In: Society of toxicology annual meeting, San Diego, CA
50. Poulin P, Haddad S (2012) Advancing prediction of tissue distribution and volume of distribution of highly lipophilic compounds from a simplified tissue-composition-based model as a mechanistic animal alternative method. J Pharm Sci 101(6):2250–2261
51. Snyder W, Cook M, Nasset E, Karhausen L, Howells G, Tipton I (1975) ICRP Publication 23: report of the task group on reference man. International Commission on Radiological Protection
52. International Commission on Radiological Protection (1975) Report of the task group on reference man, vol 23. Pergamon, Oxford
53. Endo S, Escher BI, Goss K-U (2011) Capacities of membrane lipids to accumulate neutral organic chemicals. Environ Sci Technol 45(14):5912–5921
54. Simulations Plus (2010) GastroPlus™ Manual California, EUA
55. Simulations Plus (2017) ADMET Predictor
56. Barton HA, Chiu WA, Setzer RW, Andersen ME, Bailer AJ, Bois FY, DeWoskin RS, Hays S, Johanson G, Jones N (2007) Characterizing uncertainty and variability in physiologically based pharmacokinetic models: state of the science and needs for research and implementation. Toxicol Sci 99(2):395–402
57. McLanahan ED, El-Masri HA, Sweeney LM, Kopylev LY, Clewell HJ, Wambaugh JF, Schlosser PM (2012) Physiologically based pharmacokinetic model use in risk assessment: why being published is not enough. Toxicol Sci 126(1):5–15. doi:10.1093/toxsci/kfr295
58. Bois FY (1999) Analysis of PBPK models for risk characterization. Ann N Y Acad Sci 895(1):317–337
59. Hack CE (2006) Bayesian analysis of physiologically based toxicokinetic and toxicodynamic models. Toxicology 221(2):241–248
60. Tsamandouras N, Rostami-Hodjegan A, Aarons L (2015) Combining the ‘bottom up’and ‘top down’approaches in pharmacokinetic modelling: fitting PBPK models to observed clinical data. Br J Clin Pharmacol 79(1):48–55
61. Bois FY (2000) Statistical analysis of Clewell et al. PBPK model of trichloroethylene kinetics. Environ Health Perspect 108(Suppl 2):307
62. Liao KH, Tan YM, Conolly RB, Borghoff SJ, Gargas ML, Andersen ME, Clewell HJ (2007) Bayesian estimation of pharmacokinetic and pharmacodynamic parameters in a mode-of-action-based cancer risk assessment for chloroform. Risk Anal 27(6):1535–1551
63. Nong A, Tan Y-M, Krolski ME, Wang J, Lunchick C, Conolly RB, Clewell HJ III (2008) Bayesian calibration of a physiologically based pharmacokinetic/pharmacodynamic model of carbaryl cholinesterase inhibition. J Toxicol Environ Health Part A 71(20):1363–1381
64. Yang Y, Xu X, Georgopoulos PG (2010) A bayesian population PBPK model for multiroute chloroform exposure. J Expo Sci Environ Epidemiol 20(4):326–341
65. Evans M, Chiu W, Okino M, Caldwell J (2009) Development of an updated PBPK model for trichloroethylene and metabolites in mice, and its application to discern the role of oxidative metabolism in TCE-induced hepatomegaly. Toxicol Appl Pharmacol 236(3):329–340
66. Gelman A, Bois F, Jiang J (1996) Physiological pharmacokinetic analysis using population modeling and informative prior distributions. J Am Stat Assoc 91(436):1400–1412
67. Garcia RI, Ibrahim JG, Wambaugh JF, Kenyon EM, Setzer RW (2015) Identifiability of PBPK models with applications to dimethylarsinic acid exposure. J Pharmacokinet Pharmacodyn 42(6):591–609. doi:10.1007/s10928-015-9424-2
68. Tornero-Velez R, Davis J, Scollon E, Starr JM, Setzer RW, Goldsmith M, Chang D, Xue J, Zartarian V, DeVito MJ (2012) A pharmacokinetic model of cis-and trans-permethrin disposition in rats and humans with aggregate exposure application. Toxicol Sci 130:33–47
69. Tornero-Velez R, Davis J, Scollon EJ, Starr JM, Setzer RW, Goldsmith M-R, Chang DT, Xue J, Zartarian V, De Vito MJ (2012) A pharmacokinetic model of cis-and trans-permethrin disposition in rats and humans with aggregate exposure application. Toxicol Sci 130(1):33–47
70. Simon TW, Zhu Y, Dourson ML, Beck NB (2016) Bayesian methods for uncertainty factor application for derivation of reference values. Regul Toxicol Pharmacol 80:9–24. doi:10.1016/j.yrtph.2016.05.018
71. Box GE (1979) Robustness in the strategy of scientific model building. Robust Stat 1:201–236
72. Oreskes N (1998) Evaluation (not validation) of quantitative models. Environ Health Perspect 106(Suppl 6):1453
73. Sheridan RP, Feuston BP, Maiorov VN, Kearsley SK (2004) Similarity to molecules in the training set is a good discriminator for prediction accuracy in QSAR. J Chem Inf Comput Sci 44(6):1912–1928
74. Nagar S, Korzekwa K (2017) Drug distribution. Part 1. Models to predict membrane partitioning. Pharm Res 34(3):535–543
75. Korzekwa K, Nagar S (2017) Drug distribution part 2. Predicting volume of distribution from plasma protein binding and membrane partitioning. Pharm Res 34(3):544–551
76. Khor S, Mayersohn M (1991) Potential error in the measurement of tissue to blood distribution coefficients in physiological pharmacokinetic modeling. Residual tissue blood. I. Theoretical considerations. Drug Metab Dispos 19(2):478–485
77. Thompson MD, Beard DA, Wu F (2012) Use of partition coefficients in flow-limited physiologically-based pharmacokinetic modeling. J Pharmacokinet Pharmacodyn 39(4):313–327. doi:10.1007/s10928-012-9252-6
78. De Bruijn J, Busser F, Seinen W, Hermens J (1989) Determination of octanol/water partition coefficients for hydrophobic organic chemicals with the “slow-stirring” method. Environ Toxicol Chem 8(6):499–512. doi:10.1002/etc.5620080607
79. Dionisio KL, Frame AM, Goldsmith M-R, Wambaugh JF, Liddell A, Cathey T, Smith D, Vail J, Ernstoff AS, Fantke P (2015) Exploring consumer exposure pathways and patterns of use for chemicals in the environment. Toxicol Rep 2:228–237