The Future of Toxicity Testing

REFERENCES

• Akamatsu , M. , Fujikawa , M. , Nakao , K. and Shimizu , R. 2009 . In silico prediction of human oral absorption based on QSAR analyses of PAMPA permeability . Chem. Biodivers. , 6 : 1845 – 1866 .
   PubMed Web of Science ®Google Scholar
• Alon , U. 2006 . An introduction to systems biology: Design of biological circuits , Boca Raton, FL : CRC Press .
   Google Scholar
• Andersen , M. E. 2010 . Calling on Science: Making “Alternatives” the New Gold Standard . ALTEX , in press
   PubMedGoogle Scholar
• Andersen , M. E. and Krewski , D. 2009 . Toxicity testing in the 21st century: Bringing the vision to life . Toxicol. Sci. , 107 : 324 – 330 .
   PubMed Web of Science ®Google Scholar
• Andersen , M. E. , Thomas , R. S. , Gaido , K. W. and Conolly , R. B. 2005 . Dose-response modeling in reproductive toxicology in the systems biology era . Reprod. Toxicol. , 19 : 327 – 337 .
   PubMed Web of Science ®Google Scholar
• Andersen , M. E. 2010 . “ ALTEX ” . In Calling on science: Making “alternatives” the new gold standard , in press .
   Google Scholar
• Ankley , G. T. , Bencic , D. C. , Breen , M. S. , Collette , T. W. , Conolly , R. B. , Denslow , N. D. , Edwards , S. W. , Ekman , D. R. , Garcia-Reyero , N. , Jensen , K. M. , Lazorchak , J. M. , Martinovic , D. , Miller , D. H. , Perkins , E. J. , Orlando , E. F. , Villeneuve , D. L. , Wang , R. L. and Watanabe , K. H. 2009 . Endocrine disrupting chemicals in fish: developing exposure indicators and predictive models of effects based on mechanism of action . Aquat. Toxicol. , 92 : 168 – 178 .
   PubMed Web of Science ®Google Scholar
• Arnot , J. A. , Mackay , D. , Parkerton , T. F. and Bonnell , M. 2008 . A database of fish biotransformation rates for organic chemicals . Environ. Toxicol. Chem. , 27 : 2263 – 2270 .
   PubMed Web of Science ®Google Scholar
• Arnot , J. A. , Meylan , W. , Tunkel , J. , Howard , P. H. , Mackay , D. , Bonnell , M. and Boethling , R. S. 2009 . A quantitative structure-activity relationship for predicting metabolic biotransformation rates for organic chemicals in fish . Environ. Toxicol. Chem. , 28 : 1168 – 1177 .
   PubMed Web of Science ®Google Scholar
• Au , W. W. and Ruchirawat , M . 2009 . Biomarkers in population studies: Environmental mutagenesis and risk for cancer . Rev. Environ. Health , 24 : 117 – 127 .
   PubMedGoogle Scholar
• Barnat , J. , Brim , L. , Cerna , I. , Drazan , S , Fabrikova , J. and Safranek , D. 2009 . On algorithmic analysis of transcriptional regulation by LTL model checking . Theor. Comput. Sci. , 410 : 3128 – 3148 .
   Google Scholar
• Basak , S. C. , Mills , D. , Hawkins , D. M. and Kraker , J. J . 2009 . Quantitative structure-activity relationship (QSAR) modeling of human blood:air partitioning with proper statistical methods and validation . Chem. Biodivers. , 6 : 487 – 502 .
   PubMedGoogle Scholar
• Benfenati , E. , Benigni , R. , DeMarini , D. M. , Helma , C. , Kirkland , D. , Martin , T. M. , Mazzatorta , P. , Ouedraogo-Arras , G. , Richard , A. M. , Schilter , B. , Schoonen , W. G. E. J. , Snyder , R. and Yang , C. 2009 . Predictive models for carcinogenicity and mutagenicity: Frameworks, state-of-the-art, and perspectives . J. Environ. Sci. Health C Environ. Carcinogen. Ecotoxicol. Rev. , 27 : 57 – 90 .
   PubMed Web of Science ®Google Scholar
• Benigni , R. and Bossa , C . 2008 . Predictivity of QSAR . J. Chem. Inform. Model. , 48 : 971 – 980 .
   PubMed Web of Science ®Google Scholar
• Benigni , R. , Bossa , C. , Netzeva , T. , Rodomonte , A. and Tsakovska , I. 2007 . Mechanistic QSAR of aromatic amines: New models for discriminating between homocyclic mutagens and non-mutagens, and validation of models for carcinogens . Environ. Mol. Mutagen. , 48 : 754 – 771 .
   PubMed Web of Science ®Google Scholar
• Berg , E. L. , Yang , J. , Melrose , J. , Nguyen , D. , Privat , S. , Rosler , E , Kunkel , E. J. and Ekins , S. 2010 . Chemical target and pathway toxicity mechanisms defined in primary human cell systems . J. Pharmacol. Toxicol. Meth. , 61 : 3 – 15 .
   PubMed Web of Science ®Google Scholar
• Blaauboer , B. J. 2001 . Toxicodynamic modelling and the interpretation of in vitro toxicity data . Toxicol. Lett. , 120 : 111 – 123 .
   PubMedGoogle Scholar
• Blaauboer , B. J. 2008 . The contribution of in vitro toxicity data in hazard and risk assessment: Current limitations and future perspectives . Toxicol. Lett. , 180 : 81 – 84 .
   PubMed Web of Science ®Google Scholar
• Blaauboer , B. J. , Hermens , J. and van Eijkeren , J . 2006 . Estimating acute toxicity based on in vitro cytotoxicity: Role of biokinetic modelling . ALTEX , 23 ( suppl ) : 250 – 253 .
   Google Scholar
• Boekelheide , K. and Campion , S. N. 2010 . Toxicity testing in the 21st century: using the new toxicity testing paradigm to create a taxonomy of adverse effects . Toxicol. Sci , 114 : 20 – 24 .
   PubMed Web of Science ®Google Scholar
• Boffetta , P. 2002 . Molecular epidemiology: A tool for understanding mechanisms of disease . Eur. J. Surg. , 168 : 62 – 69 .
   Google Scholar
• Brazma , A. 2009 . Minimum information about a microarray experiment (MIAME)—Successes, failures, challenges . Sci. World J. , 9 : 420 – 423 .
   Google Scholar
• Bus , J. S. and Becker , R. A . 2009 . Toxicity testing in the 21st century: A view from the chemical industry . Toxicol. Sci. , 112 : 297 – 302 .
   PubMed Web of Science ®Google Scholar
• Cavallo , D. , Ursini , C. L. , Rondinone , B. and Iavicoli , S . 2009 . Evaluation of a suitable DNA damage biomarker for human biomonitoring of exposed workers . Environ. Mol. Mutagen. , 50 : 781 – 790 .
   PubMed Web of Science ®Google Scholar
• Chapin , R. E. and Stedman , D. B . 2009 . Endless possibilities: Stem cells and the vision for toxicology testing in the 21st century . Toxicol. Sci. , 112 : 17 – 22 .
   PubMed Web of Science ®Google Scholar
• Chen , C. , Krausz , K. W. , Shah , Y. M. , Idle , J. R. and Gonzalez , F. J. 2009 . Serum metabolomics reveals irreversible inhibition of fatty acid beta-oxidation through the suppression of PPAR-alpha activation as a contributing mechanism of acetaminophen-induced hepatotoxicity . Chem. Res. Toxicol. , 22 : 699 – 707 .
   PubMed Web of Science ®Google Scholar
• Chiu , W. A. , Barton , H. A. , DeWoskin , R. S. , Schlosser , P. , Thompson , C. M. , Sonawane , B. , Lipscomb , J. C. and Krishnan , K. 2007 . Evaluation of physiologically based pharmacokinetic models for use in risk assessment . J. Appl. Toxicol. , 27 : 218 – 237 .
   PubMed Web of Science ®Google Scholar
• Cinquemani , E. , Milias-Argeitis , A. , Summers , S. and Lygeros , J. 2008 . Stochastic dynamics of genetic networks: Modelling and parameter identification . Bioinformatics , 24 : 2748 – 2754 .
   PubMedGoogle Scholar
• CIRM Workshop Report. 2008. Stem cells in predictive toxicology. Available at http://www.cirm.ca.gov/pub/pdf/CIRM_Predictive_ Tox.pdf
   Google Scholar
• Clarke , C. J. and Haselden , J. N . 2008 . Metabolic profiling as a tool for understanding mechanisms of toxicity . Toxicol. Pathol. , 36 : 140 – 147 .
   PubMed Web of Science ®Google Scholar
• Clewell , H. J. , Tan , Y. M. , Campbell , J. L. and Andersen , M. E . 2008 . Quantitative interpretation of human biomonitoring data . Toxicol. Appl. Pharmacol. , 231 : 122 – 133 .
   PubMed Web of Science ®Google Scholar
• Clewell , R. A. and Clewell , H. J . 2008 . Development and specification of physiologically based pharmacokinetic models for use in risk assessment . Regul. Toxicol. Pharmacol. , 50 : 129 – 143 .
   PubMed Web of Science ®Google Scholar
• Cochrane , G. R. and Galperin , M. Y. 2010 . The 2010 Nucleic Acids Research Database Issue and online database collection: A community of data resources . Nucleic Acids Res. , 38 ( database issue ) : D1 – D4 .
   PubMedGoogle Scholar
• Coen , M. , Holmes , E. , Lindon , J. C. and Nicholson , J. K. 2008 . NMR-based metabolic profiling and metabonomic approaches to problems in molecular toxicology . Chem. Res. Toxicol. , 21 : 9 – 27 .
   PubMed Web of Science ®Google Scholar
• Coen , M. , Lenz , E. M. , Nicholson , J. K. , Wilson , I. D , Pognan , F. and Lindon , J. C . 2003 . An integrated metabonomic investigation of acetaminophen toxicity in the mouse using NMR spectroscopy . Chem. Res. Toxicol. , 16 : 295 – 303 .
   PubMed Web of Science ®Google Scholar
• Coen , M. , Ruepp , S. U. , Lindon , J. C , Nicholson , J. K. , Pognan , F. , Lenz , E. M. and Wilson , I. D. 2004 . Integrated application of transcriptomics and metabonomics yields new insight into the toxicity due to paracetamol in the mouse . J. Pharm. Biomed. Anal. , 35 : 93 – 105 .
   PubMed Web of Science ®Google Scholar
• Cohen, B.C. 2008. Toxicity testing in the 21st century: better results, less use of animals 2008. The Environmental Forum. Available at http://www.toxicology.org/pm/FORUM_ToxicityTesting.pdf
   Google Scholar
• Collings , F. B. and Vaidya , V. S . 2008 . Novel technologies for the discovery and quantitation of biomarkers of toxicity . Toxicology , 245 : 167 – 174 .
   PubMed Web of Science ®Google Scholar
• Collins , F. S. , Gray , G. M. and Bucher , J. R. 2008 . Toxicology. Transforming environmental health protection . Science , 319 : 906 – 907 .
   PubMed Web of Science ®Google Scholar
• Conolly , R. B. 2009 . Commentary on “Toxicity Testing in the 21st Century: Implications for Human Health Risk Assessment” by Krewski et al . Risk Anal. , 29 : 480 – 481 .
   PubMedGoogle Scholar
• Council of Canadian Academies. 2010. Integrated testing of pesticides. Council of Canadian Academies http://www.scienceadvice.ca/pesticides.html
   Google Scholar
• Dahlin , D. C. , Miwa , G. T. , Lu , A. Y. and Nelson , S. D. 1984 . N-Acetyl-p-benzoquinone imine: A cytochrome P-450-mediated oxidation product of acetaminophen . Proc. Natl. Acad. Sci. USA , 81 : 1327 – 1331 .
   PubMed Web of Science ®Google Scholar
• De Buck , S. S. and Mackie , C. E. 2007 . Physiologically based approaches towards the prediction of pharmacokinetics: in vitro–in vivo extrapolation . Expert Opin. Drug Metab. Toxicol. , 3 : 865 – 878 .
   PubMed Web of Science ®Google Scholar
• de Jong , E. , Louisse , J. , Verwei , M. , Blaauboer , B. J. , van de Sandt , J. J. , Woutersen , R. A. , Rietjens , I. M. and Piersma , A. H . 2009 . Relative developmental toxicity of glycol ether alkoxy acid metabolites in the embryonic stem cell test as compared with the in vivo potency of their parent compounds . Toxicol. Sci. , 110 : 117 – 124 .
   PubMed Web of Science ®Google Scholar
• Dearden , J. C. , Cronin , M. T. D. and Kaiser , K. L. E. 2009 . How not to develop a quantitative structure-activity or structure-property relationship (QSAR/QSPR) . SAR QSAR Environ. Res. , 20 : 241 – 266 .
   PubMed Web of Science ®Google Scholar
• Dix , D. J. , Houck , K. A. , Martin , M. T. , Richard , A. M. , Setzer , R. W. and Kavlock , R. J. 2007 . The ToxCast program for prioritizing toxicity testing of environmental chemicals . Toxicol. Sci. , 95 : 5 – 12 .
   PubMed Web of Science ®Google Scholar
• Elliott , E. D. 2009 . Needed: A strategy for implementing the vision . Risk Anal. , 29 : 482
   PubMedGoogle Scholar
• Environmental Law Institute. 2008. Implementing alternatives to animal testing under U.S. toxics and pesticide laws [online]. An Environmental Law Institute white paper http://www.eli.org/pdf/research/ELI_Implementing_Alternatives_White_Paper_v.1_.pdf
   Google Scholar
• EuropeanCommission . 2009 . Alternative testing strategies progress report 2009. Replacing, reducing, and refining use of animals in research , Brussels, Belgium : Directorate-General for Research, Life Sciences, Genomics and Biotechnology for Health .
   Google Scholar
• Federoff , H. J. and Gostin , L. O. 2009 . Evolving from reductionism to holism is there a future for systems medicine? . J. Am. Med. Assoc. , 302 : 994 – 996 .
   PubMed Web of Science ®Google Scholar
• Fernandes , T. G. , Diogo , M. M. , Clark , D. S , Dordick , J. S. and Cabral , J. M. S. 2009 . High-throughput cellular microarray platforms: Applications in drug discovery, toxicology and stem cell research . Trends Biotechnol. , 27 : 342 – 349 .
   PubMed Web of Science ®Google Scholar
• Firestone , M. , Kavlock , R. , Zenick , H. , Kramer , M. and the U.S. EPA Working Group on the Future of Toxicity Testing . 2010 . The U.S. Environmental Protection Agency's strategic plan for evaluating the toxicity of chemicals . J. Toxicol. Environ. Health B , 13 : 139 – 162 .
   PubMed Web of Science ®Google Scholar
• Flaveny , C. A. , Murray , I. A. and Perdew , G. H. 2010 . Differential gene regulation by the human and mouse aryl hydrocarbon receptor . Toxicol. Sci. , 114 : 217 – 225 .
   PubMed Web of Science ®Google Scholar
• Fostel , J. M. 2008 . Towards standards for data exchange and integration and their impact on a public database such as CEBS (Chemical Effects in Biological Systems) . Toxicol. Appl. Pharmacol. , 233 : 54 – 62 .
   PubMedGoogle Scholar
• Freishtat , R. J. , Benton , A. S. , Watson , A. M. , Wang , Z. Y. , Rose , M. C. and Hoffman , E. P. 2009 . Delineation of a gene network underlying the pulmonary response to oxidative stress in asthma . J. Invest. Med. , 57 : 756 – 764 .
   PubMedGoogle Scholar
• Fry , R. C. , Navasumrit , P. , Valiathan , C. , Svensson , J. P. , Hogan , B. J. , Luo , M. , Bhattacharya , S. , Kandjanapa , K. , Soontararuks , S. , Nookabkaew , S. , Mahidol , C , Ruchirawat , M. and Samson , L. D. 2007 . Activation of inflammation/NF-kappaB signaling in infants born to arsenic-exposed mothers . PLoS Genet. , 3 : e207
   PubMed Web of Science ®Google Scholar
• Fry , R. C. , Svensson , J. P. , Valiathan , C. , Wang , E. , Hogan , B. J. , Bhattacharya , S. , Bugni , J. M. , Whittaker , C. A. and Samson , L. D. 2008 . Genomic predictors of interindividual differences in response to DNA damaging agents . Genes Dev. , 22 : 2621 – 2626 .
   PubMedGoogle Scholar
• Gao , J. , Garulacan , L. A. , Storm , S. M. , Hefta , S. A. , Opiteck , G. J. , Lin , J. H. , Moulin , F. and Dambach , D. M. 2004 . Identification of in vitro protein biomarkers of idiosyncratic liver toxicity . Toxicol. In Vitro , 18 : 533 – 541 .
   PubMed Web of Science ®Google Scholar
• Gao , Y. , Holland , R. D. and Yu , L. R . 2009 . Quantitative proteomics for drug toxicity . Brief Funct. Genomic. Proteomic. , 8 : 158 – 166 .
   PubMedGoogle Scholar
• Garcia-Reyero , N. , Kroll , K. J. , Liu , L. , Orlando , E. F. , Watanabe , K. H. , Sepulveda , M. S. , Villeneuve , D. L. , Perkins , E. J. , Ankley , G. T. and Denslow , N. D. 2009 . Gene expression responses in male fathead minnows exposed to binary mixtures of an estrogen and antiestrogen . BMC Genomics , 10 : 308
   PubMedGoogle Scholar
• Gatzidou , E. T. , Zira , A. N. and Theocharis , S. E. 2007 . Toxicogenomics: A pivotal piece in the puzzle of toxicological research . J. Appl. Toxicol. , 27 : 302 – 309 .
   PubMed Web of Science ®Google Scholar
• Ge , F. and He , Q. Y. 2009 . Genomic and proteomic approaches for predicting toxicity and adverse drug reactions . Expert Opin. Drug Metab. Toxicol. , 5 : 29 – 37 .
   PubMed Web of Science ®Google Scholar
• Ginsburg , G. S. and Willard , H. F . 2009 . Genomic and personalized medicine: Foundations and applications . Transl. Res. , 154 : 277 – 287 .
   PubMed Web of Science ®Google Scholar
• Gramatica , P. 2007 . Principles of QSAR models validation: Internal and external . QSAR Comb. Sci. , 26 : 694 – 701 .
   Google Scholar
• Greenberg , M. and Lowrie , K . 2009 . Toxicity testing in the 21st century . Risk Anal. , 29 : 471 – 473 .
   PubMedGoogle Scholar
• Grzegorczyk , M. 2008 . Comparison of two different stochastic models for extracting protein regularly pathways using Bayesian networks . J. Toxicol. Environ. Health A , 71 : 827 – 834 .
   PubMed Web of Science ®Google Scholar
• Harrill , A. H. and Rusyn , I. 2008 . Systems biology and functional genomics approaches for the identification of cellular responses to drug toxicity . Expert Opin. Drug Metab. Toxicol. , 4 : 1379 – 1389 .
   PubMed Web of Science ®Google Scholar
• Hartung , T. 2009 . A toxicology for the 21st century—Mapping the road ahead . Toxicol. Sci. , 109 : 18 – 23 .
   PubMed Web of Science ®Google Scholar
• Hattis , D. 2009 . High-throughput testing—The NRC vision, the challenge of modeling dynamic changes in biological systems, and the reality of low-throughput environmental health decision making . Risk Anal. , 29 : 483 – 484 .
   PubMedGoogle Scholar
• He , M. , Stoevesandt , O. and Taussig , M. J. 2008 . In situ synthesis of protein arrays . Curr. Opin. Biotechnol. , 19 : 4 – 9 .
   PubMed Web of Science ®Google Scholar
• Heneweer , M. , Houtman , R. , Poortman , J. , Groot , M. , Maliepaard , C. and Peijnenburg , A . 2007 . Estrogenic effects in the immature rat uterus after dietary exposure to ethinylestradiol and zearalenone using a systems biology approach . Toxicol. Sci. , 99 : 303 – 314 .
   PubMed Web of Science ®Google Scholar
• Heng , B. C. , Richards , M. , Ge , Z. and Shu , Y . 2009 . Induced adult stem (iAS) cells and induced transit amplifying progenitor (iTAP) cells—A possible alternative to induced pluripotent stem (iPS) cells? . J. Tissue Eng. Regen. Med. , 4 : 159 – 162 .
   Google Scholar
• Holsapple , M. P. , Afshari , C. A. and Lehman-McKeeman , L. D . 2009 . Forum Series: The “vision” for toxicity testing in the 21st century: Promises and conundrums . Toxicol. Sci. , 107 : 307 – 308 .
   PubMed Web of Science ®Google Scholar
• Hopf , N. B. , Carreon , T. and Talaska , G . 2009 . Biological markers of carcinogenic exposure in the aluminum smelter industry—A systematic review . J. Occup. Environ. Hyg. , 6 : 562 – 581 .
   PubMed Web of Science ®Google Scholar
• Houck , K. A. , Dix , D. J. , Judson , R. S. , Kavlock , R. J. , Yang , J. and Berg , E. L. 2009 . Profiling bioactivity of the ToxCast chemical library using BioMAP primary human cell systems . J. Biomol. Screen. , 14 : 1054 – 1066 .
   PubMed Web of Science ®Google Scholar
• Houck , K. A. and Kavlock , R. J . 2008 . Understanding mechanisms of toxicity: Insights from drug discovery research . Toxicol. Appl. Pharmacol. , 227 : 163 – 178 .
   PubMed Web of Science ®Google Scholar
• Hubal , E. A. 2009 . Biologically relevant exposure science for 21st century toxicity testing . Toxicol. Sci. , 111 : 226 – 232 .
   PubMed Web of Science ®Google Scholar
• Humane Society of the United States, The Humane Society Legislative Fund, and Humane Society International. 2009. Human toxicology project consortium http://www.thehamner.org/docs/HTOX_flyer_8-21-09.pdf
   Google Scholar
• Inglese , J. 2002 . Expanding the HTS paradigm . Drug Discov. Today. , 7 : S105 – S106 .
   PubMed Web of Science ®Google Scholar
• Inglese , J. , Auld , D. S. , Jadhav , A. , Johnson , R. L. , Simeonov , A. , Yasgar , A. , Zheng , W. and Austin , C. P. 2006 . Quantitative high-throughput screening: A titration-based approach that efficiently identifies biological activities in large chemical libraries . Proc. Natl. Acad. Sci. USA , 103 : 11473 – 1148 .
   PubMed Web of Science ®Google Scholar
• Jacobson-Kram , D. and Contrera , J. F . 2007 . Genetic toxicity assessment: Employing the best science for human safety evaluation Part I: Early screening for potential human mutagens . Toxicol. Sci. , 96 : 16 – 20 .
   PubMed Web of Science ®Google Scholar
• Jaworska , J. S. , Comber , M. , Auer , C. and Van Leeuwen , C. J . 2003 . Summary of a workshop on regulatory acceptance of (Q)SARs for human health and environmental endpoints . Environ. Health Perspect. , 111 : 1358 – 1360 .
   PubMed Web of Science ®Google Scholar
• Judson , R. , Richard , A. , Dix , D. , Houck , K. , Elloumi , F. , Martin , M. , Cathey , T. , Transue , T. R. , Spencer , R. and Wolf , M. 2008 . ACToR—Aggregated computational toxicology resource . Toxicol. Appl.Pharmacol. , 233 : 7 – 13 .
   PubMed Web of Science ®Google Scholar
• Judson , R. , Richard , A. , Dix , D. J. , Houck , K. , Martin , M. , Kavlock , R. , Dellarco , V. , Henry , T. , Holderman , T. , Sayre , P. , Tan , S. , Carpenter , T. and Smith , E. 2009 . The toxicity data landscape for environmental chemicals . Environ. Health Perspect. , 117 : 685 – 695 .
   PubMed Web of Science ®Google Scholar
• Kar , S. and Roy , K . 2009 . QSAR modeling of toxicity of diverse organic chemicals to Daphnia magna using 2D and 3D descriptors . J. Hazard. Mater. , 177 : 344 – 351 .
   PubMedGoogle Scholar
• Kavlock , R. J. , Austin , C. P. and Tice , R. R. 2009 . Toxicity testing in the 21st century: Implications for human health risk assessment . Risk Anal. , 29 : 485 – 487 .
   PubMed Web of Science ®Google Scholar
• Khetani , S. R. and Bhatia , S. N. 2008 . Microscale culture of human liver cells for drug development . Nat. Biotechnol. , 26 : 120 – 126 .
   PubMed Web of Science ®Google Scholar
• Kim , H. D. , Shay , T. , O'Shea , E. K. and Regev , A. 2009 . Transcriptional regulatory circuits: Predicting numbers from alphabets . Science , 325 : 429 – 432 .
   PubMed Web of Science ®Google Scholar
• Kirkland , D. J. , Henderson , L. , Marzin , D. , Muller , L. , Parry , J. M. , Speit , G. , Tweats , D. J. and Williams , G. M. 2005 . Testing strategies in mutagenicity and genetic toxicology: An appraisal of the guidelines of the European Scientific Committee for Cosmetics and Non-Food Products for the evaluation of hair dyes . Mutat. Res.Genet Toxicol. Environ. Mutagen , 588 : 88 – 105 .
   PubMed Web of Science ®Google Scholar
• Kiyosawa , N. , Ando , Y. , Manabe , S. and Yamoto , T . 2009 . Toxicogenomic biomarkers for liver toxicity . J. Toxicol. Pathol. , 22 : 35 – 52 .
   PubMed Web of Science ®Google Scholar
• Knight , A. W. , Little , S. , Houck , K. , Dix , D. , Judson , R. , Richard , A. , McCarroll , N. , Akerman , G. , Yang , C. H. , Birrell , L. and Walmsley , R. M. 2009 . Evaluation of high-throughput genotoxicity assays used in profiling the US EPA ToxCast (TM) chemicals . Regul. Toxicol. Pharmacol. , 55 : 188 – 199 .
   PubMedGoogle Scholar
• Krewski , D. , Acosta , D. , Andersen , M. , Anderson , H. , Bailar , J. C. , Boekelheide , K. , Brent , R. , Charnley , G. , Cheung , V. G. , Green , S. , Kelsey , K. T. , Kerkvleit , N. K. , Lee , A. , McCray , L. , Meyer , O. , Patterson , R., D. , Pennie , W. , Scalar , R. A. , Solomon , G. M. , Stephens , M. , Yager , J. , Zeise , L. and the Staff Committee on Toxicity Assessment of Environmental Agents . 2010 . Toxicity testing in the twenty-first century: A vision and a strategy . J. Toxicol. Environ. Health B , 13 : 51 – 138 .
   PubMed Web of Science ®Google Scholar
• Krewski , D. , Andersen , M. E. , Mantus , E. and Zeise , L. 2009 . Toxicity testing in the 21st century: implications for human health risk assessment . Risk Anal. , 29 : 474 – 479 .
   PubMed Web of Science ®Google Scholar
• Lankveld , D. P. , Van Loveren , H. , Baken , K. A. and Vandebriel , R. J. 2010 . In vitro testing for direct immunotoxicity: State of the art . Methods Mol. Biol. , 598 : 401 – 423 .
   PubMedGoogle Scholar
• Lee , J. , Lilly , G. D. , Doty , R. C. , Podsiadlo , P. and Kotov , N. A. 2009 . In vitro toxicity testing of nanoparticles in 3D cell culture . Small , 5 : 1213 – 1221 .
   PubMed Web of Science ®Google Scholar
• Liao , K. H. , Tan , Y. M. and Clewell , H. J . 2007 . Development of a screening approach to interpret human biomonitoring data on volatile organic compounds: Reverse dosimetry on biomonitoring data for trichloroethylene . Risk Anal. , 27 : 1223 – 1236 .
   PubMed Web of Science ®Google Scholar
• Liu , X. M. , Kramer , J. A. , Swaffield , J. C. , Hu , Y. , Chai , G. X. and Wilson , A. G. E. 2008 . Development of a highthroughput yeast-based assay for detection of metabolically activated genotoxins . Mutat. Res. , 653 : 63 – 69 .
   PubMedGoogle Scholar
• MacDonald , J. S. and Robertson , R. T. 2009 . Toxicity testing in the 21st century: a view from the pharmaceutical industry . Toxicol. Sci. , 110 : 40 – 46 .
   PubMed Web of Science ®Google Scholar
• Maherali , N. , Ahfeldt , T. , Rigamonti , A. , Utikal , J. , Cowan , C. and Hochedlinger , K. 2008 . A high-efficiency system for the generation and study of human induced pluripotent stem cells . Cell Stem Cell , 3 : 340 – 345 .
   PubMed Web of Science ®Google Scholar
• Maherali , N. and Hochedlinger , K. 2009 . Tgfbeta signal inhibition cooperates in the induction of iPSCs and replaces Sox2 and cMyc . Curr. Biol. , 19 : 1718 – 1723 .
   PubMed Web of Science ®Google Scholar
• Manini , P. , De Palma , G. , Andreoli , R. , Marczynski , B. , Hanova , M. , Mozzoni , P. , Naccarati , A. , Vodickova , L. , Hlavac , P. , Mutti , A. and Vodicka , P. 2009 . Biomarkers of nucleic acid oxidation, polymorphism in, and expression of, hOGG1 gene in styrene-exposed workers . Toxicol. Lett. , 190 : 41 – 47 .
   PubMed Web of Science ®Google Scholar
• Marinelli , F. , Pietrucci , F. , Laio , A. and Piana , S. 2009 . A kinetic model of Trp-cage folding from multiple biased molecular dynamics simulations 1 . PLoS Comput. Biol. , 5 : e1000452
   PubMed Web of Science ®Google Scholar
• Mayer , J. , Cheesemar , M. A. and Twaroski , M. L. 2008 . Structure-activity relationship analysis tools: Validation and applicability in predicting carcinogens . Regul. Toxicol. Pharmacol. , 50 : 50 – 58 .
   PubMed Web of Science ®Google Scholar
• Mazur , J. , Ritter , D. , Reinelt , G. and Kaderali , L. 2009 . Reconstructing nonlinear dynamic models of gene regulation using stochastic sampling . BMC Bioinformatics , 10 : 448
   PubMedGoogle Scholar
• Mazzoleni , G. , Di Lorenzo , D. and Steimberg , N. 2009 . Modelling tissues in 3D: The next future of pharmaco-toxicology and food research? . Genes Nutr. , 4 : 13 – 22 .
   PubMed Web of Science ®Google Scholar
• McMillian , M. , Nie , A. , Parker , J. B. , Leone , A. , Kemmerer , M. , Bryant , S. , Herlich , J. , Yieh , L. , Bittner , A. , Liu , X. , Wan , J. , Johnson , M. D. and Lord , P. 2005 . Drug-induced oxidative stress in rat liver from a toxicogenomics perspective . Toxicol. Appl. Pharmacol. , 207 ( suppl ) : 171 – 178 .
   PubMedGoogle Scholar
• Meek , B. and Doull , J. 2009 . Pragmatic challenges for the vision of toxicity testing in the 21st century in a regulatory context: another Ames test? … or a new edition of “the Red Book”? . Toxicol. Sci. , 108 : 19 – 21 .
   PubMed Web of Science ®Google Scholar
• Merrick , B. A. and Witzmann , F. A. 2009 . The role of toxicoproteomics in assessing organ specific toxicity . Experientia Suppl. , 99 : 367 – 400 .
   PubMedGoogle Scholar
• Nakao , K. , Fujikawa , M. , Shimizu , R. and Akamatsu , M.. 2009 . QSAR application for the prediction of compound permeability with in silico descriptors in practical use . J. Comput. Aided Mol. Design , 23 : 309 – 319 .
   PubMed Web of Science ®Google Scholar
• Nantasenamat , C. , Isarankura-Na-Ayudhya , C. , Naenna , T. and Prachayasittikul , V. 2009 . A practical overview of quantitative structure-activity relationship . Exp. Clin. Sci. J. , 8 : 74 – 88 .
   Google Scholar
• National Library of Medicine. 2010. TOXNET: Toxicology data network [online] http://toxnet.nlm.nih.gov (Accessed: 10 March 2010 ).
   Google Scholar
• National Research Council . 2006 . Toxicity testing for assessment of environmental agents: Interim report , Washington, DC : National Academies Press .
   Google Scholar
• National Research Council . 2007a . Toxicity testing in the 21st century, A vision and a strategy , Washington, DC : National Academies Press .
   Google Scholar
• National Research Council . 2007b . Applications of toxicogenomic technologies to predictive toxicology and risk assessment , Washington, DC : National Academies Press .
   Google Scholar
• Nigsch , F. , Macaluso , N. J. M. , Mitchell , J. B. O. and Zmuidinavicius , D. 2009 . Computational toxicology: An overview of the sources of data and of modeling methods . Expert Opin. Drug Metab. Toxicol. , 5 : 1 – 14 .
   PubMed Web of Science ®Google Scholar
• Nirmalanandhan , V. S. and Sittampalam , G. S. 2009 . Stem cells in drug discovery, tissue engineering, and regenerative medicine: emerging opportunities and challenges . J. Biomol. Screen. , 14 : 755 – 768 .
   PubMedGoogle Scholar
• Organization for Economic Co-Operation and Development. 2007. Guidance document on the validation of (quantitative) structure-activity relationship [(Q)SAR] models. Organization for Economic Co-Operation and Development http://www.oecd.org/dataoecd/55/35/38130292.pdf
   Google Scholar
• Olaharski , A. J , Uppal , H , Cooper , M. , Platz , S. , Zabka , T. S. and Kolaja , K. L. 2009 . In vitro to in vivo concordance of a high throughput assay of bone marrow toxicity across a diverse set of drug candidates . Toxicol Lett. , 188 : 98 – 103 .
   PubMedGoogle Scholar
• Olson , H. , Betton , G. , Robinson , D. , Thomas , K. , Monro , A. , Kolaja , G. , Lilly , P. , Sanders , J. , Sipes , G. , Bracken , W. , Dorato , M. , Van Deun , K. , Smith , P. , Berger , B. and Heller , A. 2000 . Concordance of the toxicity of pharmaceuticals in humans and in animals . Regul. Toxicol. Pharmacol. , 32 : 56 – 67 .
   PubMed Web of Science ®Google Scholar
• Pampaloni , F. , Stelzer , E. H. and Masotti , A. 2009 . Three-dimensional tissue models for drug discovery and toxicology . Recent Pat. Biotechnol. , 3 : 103 – 117 .
   PubMedGoogle Scholar
• Pereira , D. A. and Williams , J. A . 2007 . Origin and evolution of high throughput screening . Br. J. Pharmacol. , 152 : 53 – 61 .
   PubMed Web of Science ®Google Scholar
• Pisabarro , A. G. , Perez , G. , Lavin , J. L. and Ramirez , L. 2008 . Genetic networks for the functional study of genomes . Brief. Funct. Genomics Proteomics , 7 : 249 – 263 .
   PubMedGoogle Scholar
• Poynton , H. C. , Varshavsky , J. R. , Chang , B. , Cavigiolio , G. , Chan , S. , Holman , P. S. , Loguinov , A. V. , Bauer , D. J. , Komachi , K. , Theil , E. C. , Perkins , E. J. , Hughes , O. and Vulpe , C. D. 2007 . Daphnia magna ecotoxicogenomics provides mechanistic insights into metal toxicity . Environ. Sci. Technol. , 41 : 1044 – 1050 .
   PubMed Web of Science ®Google Scholar
• Ramachandran , N. , Raphael , J. V. , Hainsworth , E. , Demirkan , G. , Fuentes , M. G. , Rolfs , A. , Hu , Y. and LaBaer , J . 2008 . Next-generation high-density self-assembling functional protein arrays . Nat. Methods , 5 : 535 – 538 .
   PubMed Web of Science ®Google Scholar
• Reiter, L. W. 2009. Transforming exposure in the 21st century: A challenge and opportunity http://www.isesweb.org/Meetings/mtgs_pas.htm
   Google Scholar
• Rhomberg , L. R. 2009 . Risk Assessment in the 21st century: Changes wrought by changing science . Risk Anal. , 29 : 488 – 489 .
   PubMedGoogle Scholar
• Richard , A. M. , Yang , C. and Judson , R. S. 2008 . Toxicity data informatics: Supporting a new paradigm for toxicity prediction . Toxicol. Mech. Methods , 18 : 103 – 118 .
   PubMed Web of Science ®Google Scholar
• Rietjens , I. M. , Punt , A. , Schilter , B. , Scholz , G. , Delatour , T. and van Bladeren , P. J. 2009 . In silico methods for physiologically based biokinetic models describing bioactivation and detoxification of coumarin and estragole: Implications for risk assessment . Mol. Nutr. Food Res. , 26 : 195 – 207 .
   Google Scholar
• Ritter , R. , Scheringer , M. , MacLeod , M. , Schenker , U. and Hungerbuhler , K. 2009 . A multi-individual pharmacokinetic model framework for interpreting time trends of persistent chemicals in human populations: Application to a post-ban situation . Environ. Health Perspect. , 117 : 1280 – 1286 .
   PubMed Web of Science ®Google Scholar
• Schmidt , C. W. 2003 . Data explosion: Bringing order to chaos with bioinformatics . Environ. Health Perspect , 111 : A340 – A345 .
   Google Scholar
• Scott , M. , Hwa , T. and Ingalls , B. 2007 . Deterministic characterization of stochastic genetic circuits . Proc. Nat. Acad. Sci. USA , 104 : 7402 – 7407 .
   PubMedGoogle Scholar
• Seidle , T. and Stephens , M. L. 2009 . Bringing toxicology into the 21st century: A global call to action . Toxicol. In Vitro , 23 : 1576 – 1579 .
   PubMed Web of Science ®Google Scholar
• Shi , L. M. , Reid , L. H. , Jones , W. D. , Shippy , R. , Warrington , J. A. , Baker , S. C. , Collins , P. J. , de Longueville , F. , Kawasaki , E. S. , Lee , K. Y. , Luo , Y , Sun , Y. A , Willey , J. C. , Setterquist , R. A , Fischer , G. M , Tong , W. , Dragan , Y. P. , Dix , D. J. , Frueh , F. W. , Goodsaid , F. M. , Herman , D. , Jensen , R. V. , Johnson , C. D. , Lobenhofer , E. K. , Puri , R. K. , Schrf , U. , Thierry-Mieg , J. , Wang , C. , Wilson , M. , Wolber , P. K. , Zhang , L , Amur , S , Bao , W , Barbacioru , C. C. , Lucas , A. B. , Bertholet , V. , Boysen , C. , Bromley , B. , Brown , D. , Brunner , A. , Canales , R , Cao , X. M , Cebula , T. A. , Chen , J. J. , Cheng , J. , Chu , T. M. , Chudin , E , Corson , J , Corton , J. C. , Croner , L. J. , Davies , C. , Davison , T. S. , Delenstarr , G. , Deng , X. , Dorris , D. , Eklund , A. C. , Fan , X. H. , Fang , H. , Fulmer-Smentek , S. , Fuscoe , J. C. , Gallagher , K. , Ge , W. , Guo , L. , Guo , X. , Hager , J. , Haje , P. K , Han , J , Han , T. , Harbottle , H. C. , Harris , S. C. , Hatchwell , E. , Hauser , C. A. , Hester , S. , Hong , H. , Hurban , P. , Jackson , S. A. , Ji , H. , Knight , C. R. , Kuo , W. P. , LeClerc , J. E. , Levy , S. , Li , Q. Z. , Liu , C. , Liu , Y. , Lombardi , M. J. , Ma , Y. , Magnuson , S. R. , Maqsodi , B. , McDaniel , T. , Mei , N. , Myklebost , O. , Ning , B. , Novoradovskaya , N. , Orr , M. S. , Osborn , T. W. , Papallo , A. , Patterson , T. A. , Perkins , R. G. , Peters , E. H. , Peterson , R. , Philips , K. L. , Pine , P. S. , Pusztai , L. , Qian , F , Ren , H. , Rosen , M. , Rosenzweig , B. A. , Samaha , R. R. , Schena , M. , Schroth , G. P. , Shchegrova , S. , Smith , D. D. , Staedtler , F. , Su , Z. , Sun , H. , Szallasi , Z , Tezak , Z. , Thierry-Mieg , D. , Thompson , K. L. , Tikhonova , I. , Turpaz , Y. , Vallanat , B. , Van , C. , Walker , S. J. , Wang , S. J. , Wang , Y. , Wolfinger , R. , Wong , A. , Wu , J. , Xiao , C. , Xie , Q. , Xu , J. , Yang , W. , Zhang , L. , Zhong , S. , Zong , Y. and Slikker , W. Jr. 2006 . The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements . Nat. Biotechnol. , 24 : 1151 – 1161 .
   PubMed Web of Science ®Google Scholar
• Shmulevich , I. and Aitchison , J. D. 2009 . Deterministic and stochastic models of genetic regulatory networks . Methods Enzymol. , 467 : 335 – 356 .
   PubMedGoogle Scholar
• Simmons , S. O. 2009 . Hypoxia response: A model toxicity pathway for high-throughput screening . Toxicol. Sci. , 112 : 1 – 3 .
   PubMedGoogle Scholar
• Simmons , S. O. , Fan , C. Y. and Ramabhadran , R. 2009 . Cellular stress response pathway system as a sentinel ensemble in toxicological screening . Toxicol. Sci. , 111 : 202 – 225 .
   PubMed Web of Science ®Google Scholar
• Singleton , D. R. , Ramirez , L. G. and Aitken , M. D. 2009 . Characterization of a polycyclic aromatic hydrocarbon degradation gene cluster in a phenanthrene-degrading acidovorax strain . Appl. Environ. Microbiol. , 75 : 2613 – 2620 .
   PubMed Web of Science ®Google Scholar
• Spielmann , H. and Liebsch , M. 2001 . Lessons learned from validation of in vitro toxicity test: From failure to acceptance into regulatory practice . Toxicol. In Vitro , 15 : 585 – 590 .
   PubMed Web of Science ®Google Scholar
• Stummann , T. C. , Hareng , L. and Bremer , S. 2009 . Hazard assessment of methylmercury toxicity to neuronal induction in embryogenesis using human embryonic stem cells . Toxicology , 257 : 117 – 126 .
   PubMed Web of Science ®Google Scholar
• Subramanian , K. , Raghavan , S. , Bhat , A. R. , Das , S. , Dikshit , J. B. , Kumar , R. , Narasimha , M. K. , Nalini , R. , Radhakrishnan , R. and Raghunathan , S. 2008 . A systems biology based integrative framework to enhance the predictivity of in vitro methods for drug-induced liver injury . Expert Opin. Drug Safety , 7 : 647 – 662 .
   PubMed Web of Science ®Google Scholar
• Sung , J. H. and Shuler , M. L. 2010 . In vitro microscale systems for systematic drug toxicity study . Bioprocess Biosyst. Eng. , 33 : 5 – 19 .
   PubMed Web of Science ®Google Scholar
• Takahashi , K. , Narita , M. , Yokura , M. , Ichisaka , T. and Yamanaka , S. 2009 . Human induced pluripotent stem cells on autologous feeders . PLoS One. , 4 : e8067
   Google Scholar
• Takahashi , K. , Tanabe , K. , Ohnuki , M. , Narita , M. , Ichisaka , T. , Tomoda , K. and Yamanaka , S. 2007 . Induction of pluripotent stem cells from adult human fibroblasts by defined factors . Cell , 131 : 861 – 872 .
   PubMed Web of Science ®Google Scholar
• Talaska , G. and Al Zoughool , M. 2003 . Aromatic amines and biomarkers of human exposure . J. Environ. Sci. Health C Environ. Carcinogen. Ecotoxicol. Rev. , 21 : 133 – 164 .
   PubMed Web of Science ®Google Scholar
• Taylor , C. F. , Paton , N. W. , Lilley , K. S. , Binz , P. A. , Julian , R. K. , Jones , A. R. , Zhu , W. , Apweiler , R. , Aebersold , R. , Deutsch , E. W. , Dunn , M. J. , Heck , A. J. , Leitner , A. , Macht , M. , Mann , M. , Martens , L. , Neubert , T. A. , Patterson , S. D. , Ping , P. , Seymour , S. L. , Souda , P. , Tsugita , A. , Vandekerckhove , J. , Vondriska , T. M. , Whitelegge , J. P. , Wilkins , M. R. , Xenarios , I. , Yates , J. R. and Hermjakob , H. 2007 . The minimum information about a proteomics experiment (MIAPE) . Nat. Biotechnol. , 25 : 887 – 893 . 3rd.,
   PubMed Web of Science ®Google Scholar
• Taylor , N. S. , Weber , R. J. M. , Southam , A. D. , Payne , T. G. , Hrydziuszko , O. , Arvanitis , T. N. and Viant , M. R. 2009 . A new approach to toxicity testing in Daphnia magna: Application of high throughput FT-ICR mass spectrometry metabolomics . Metabolomics , 5 : 44 – 58 .
   Web of Science ®Google Scholar
• Thompson , C. M. , Johns , D. O. , Sonawane , B. , Barton , H. A. , Hattis , D. , Tardif , R. and Krishnan , K. 2009 . Database for physiologically based pharmacokinetic (PBPK) modeling: Physiological data for healthy and health-impaired elderly . J. Toxicol. Environ. Health B , 12 : 1 – 24 .
   PubMed Web of Science ®Google Scholar
• Tsuji , J. S. and Garry , M. R. 2009 . Advances in toxicity testing herald improvements and challenges for risk assessment . Risk Anal. , 29 : 490 – 491 .
   PubMedGoogle Scholar
• U.S. Environmental Protection Agency. 2008. Memorandum of understanding [online] http://www.epa.gov/comptox/articles/comptox_mou. html (Accessed: 10 March 2010 ).
   Google Scholar
• U.S. Environmental Protection Agency. 2009. The U.S. Environmental Protection Agency's strategic plan for evaluating the toxicity of chemicals [online] http://www.epa.gov/spc/toxicitytesting (Accessed: 10 March 2010 ).
   Google Scholar
• Valavanidis , A. , Vlachogianni , T. and Fiotakis , C. 2009 . 8-Hydroxy-2’-deoxyguanosine (8-OHdG): A critical biomarker of oxidative stress and carcinogenesis . J. Environ. Sci. Health C Environ. Carcinogen. Ecotoxicol. Rev. , 27 : 120 – 139 .
   PubMed Web of Science ®Google Scholar
• Valerio , L. G. 2009 . In silico toxicology for the pharmaceutical sciences . Toxicol. Appl. Pharmacol. , 241 : 356 – 370 .
   PubMed Web of Science ®Google Scholar
• Vineis , P. and Perera , F. 2007 . Molecular epidemiology and biomarkers in etiologic cancer research: The new in light of the old . Cancer Epidemiol. Biomarkers Prev. , 16 : 1954 – 1965 .
   PubMed Web of Science ®Google Scholar
• Walker , N. J. and Bucher , J. R. 2009 . A 21st century paradigm for evaluating the health hazards of nanoscale materials? . Toxicol. Sci. , 110 : 251 – 254 .
   PubMed Web of Science ®Google Scholar
• Waters , M. , Stasiewicz , S. , Merrick , B. A. , Tomer , K. , Bushel , P. , Paules , R. , Stegman , N. , Nehls , G. , Yost , K. J. , Johnson , C. H. , Gustafson , S. F. , Xirasagar , S. , Xiao , N. , Huang , C. C. , Boyer , P. , Chan , D. D. , Pan , Q. , Gong , H. , Taylor , J. , Choi , D. , Rashid , A. , Ahmed , A. , Howle , R. , Selkirk , J. , Tennant , R. and Fostel , J. 2008 . CEBS—Chemical Effects in Biological Systems: A public data repository integrating study design and toxicity data with microarray and proteomics data . Nucleic Acids Res. , 36 ( database issue ) : D892 – D900 .
   Google Scholar
• Westerink , W. M. A. , Stevenson , J. C. R. , Lauwers , A. , Griffioen , G. , Horbach , G. J. and Schoonen , W. G. E. J. 2009 . Evaluation of the Vitotox (TM) and RadarScreen assays for the rapid assessment of genotoxicity in the early research phase of drug development . Mutat. Res. , 676 : 113 – 130 .
   PubMed Web of Science ®Google Scholar
• Wetmore , B. A. and Merrick , B. A. 2004 . Toxicoproteomics: Proteomics applied to toxicology and pathology . Toxicol. Pathol. , 32 : 619 – 642 .
   PubMed Web of Science ®Google Scholar
• Woodall , G. M. 2008 . An exposure-response database for detailed toxicity data . Toxicol. Appl. Pharmacol. , 233 : 14 – 16 .
   PubMedGoogle Scholar
• Wu , F. T. H. , Stefanini , M. O. , Gabhann , F. M. and Popel , A. S. 2009 . Modeling of growth factor-receptor systems from molecular-level protein interaction networks to whole-body compartment models . Methods Enzymol. , 467 : 461 – 497 .
   PubMedGoogle Scholar
• Wullenweber , A. , Kroner , O. , Kohrman , M. , Maier , A. , Dourson , M. , Rak , A. , Wexler , P. and Tomljanovic , C. 2008 . Resources for global risk assessment: The International Toxicity Estimates for Risk (ITER) and Risk Information Exchange (RiskIE) databases . Toxicol. Appl. Pharmacol. , 233 : 45 – 53 .
   PubMedGoogle Scholar
• Xia , M. H. , Huang , R. L. , Sun , Y. , Semenza , G. L. , Aldred , S. F. , Witt , K. L. , Inglese , J. , Tice , R. R. and Austin , C. P. 2009 . Identification of chemical compounds that induce HIF-1 alpha activity . Toxicol. Sci. , 112 : 153 – 163 .
   PubMedGoogle Scholar
• Yang , C. , Benz , R. D. and Cheeseman , M. A. 2006 . Landscape of current toxicity databases and database standards . Curr. Opin. Drug Discov. Dev. , 9 : 124 – 133 .
   PubMed Web of Science ®Google Scholar
• Yang , C. , Hasselgren , C. H. , Boyer , S. , Arvidson , K. , Aveston , S. , Dierkes , P. , Benigni , R. , Benz , R. D. , Contrera , J. , Kruhlak , N. L. , Matthews , E. J. , Han , X. , Jaworska , J. , Kemper , R. A. , Rathman , J. F. and Richard , A. M. 2008 . Understanding genetic toxicity through data mining: The process of building knowledge by integrating multiple genetic toxicity databases . Toxicol. Mech. Methods , 18 : 277 – 295 .
   PubMed Web of Science ®Google Scholar
• Yang , F. , Mei , Y. , Langer , R. and Anderson , D. G. 2009 . High throughput optimization of stem cell microenvironments . Comb. Chem. High Throughput Screen. , 12 : 554 – 561 .
   PubMed Web of Science ®Google Scholar
• Yu , J. , Vodyanik , M. A. , Smuga-Otto , K. , Antosiewicz-Bourget , J. , Frane , J. L. , Tian , S. , Nie , J. , Jonsdottir , G. A. , Ruotti , V. , R. Stewart , R. , Slukvin , I. I. and Thomson , J. A. 2007 . Induced pluripotent stem cell lines derived from human somatic cells . Science , 318 : 1917 – 1920 .
   PubMed Web of Science ®Google Scholar
• Zhang , Q. , Bhattacharya , S. , Andersen , M. E. and Conolly , R. B. 2010 . Computational systems biology and dose response modeling in relation to new directions in toxicity testing . J. Toxicol. Environ. Health B , 13 : 252 – 275 .
   Google Scholar
• Zhao , R. and Daley , G. Q. 2008 . From fibroblasts to iPS cells: Induced pluripotency by defined factors . J. Cell Biochem. , 105 : 949 – 955 .
   PubMed Web of Science ®Google Scholar
• Zhou , Y. , Vaidya , V. S. , Brown , R. P. , Zhang , J. , Rosenzweig , B. A. , Thompson , K. L. , Miller , T. J. , Bonventre , J. V. and Goering , P. L. 2008 . Comparison of kidney injury molecule-1 and other nephrotoxicity biomarkers in urine and kidney following acute exposure to gentamicin, mercury, and chromium . Toxicol. Sci. , 101 : 159 – 170 .
   PubMed Web of Science ®Google Scholar
• Zvinavashe , E. , Murk , A. J. and Rietjens , I. M. C. M. 2008 . Promises and pitfalls of quantitative structure–activity relationship approaches for predicting metabolism and toxicity . Chem. Res. Toxicol. , 21 : 2229 – 2236 .
   PubMed Web of Science ®Google Scholar