References
- Abdo, N., M. Xia, C. C. Brown, O. Kosyk, R. Huang, S. Sakamuru, Y. H. Zhou, J. R. Jack, P. Gallins, K. Xia, etal. 2015. Population-based in vitro hazard and concentration-response assessment of chemicals: The 1000 genomes high-throughput screening study. Environ. Health Perspect. 123::458–466. doi:https://doi.org/10.1289/ehp.1408775.
- Altschul, S. F., W. Gish, W. Miller, E. W. Myers, and D. J. Lipman. 1990. Basic local alignment search tool. J. Mol. Biol. 215 (3):403–10. doi:https://doi.org/10.1016/S0022-2836(05)80360-2.
- Bhat, V. S., M. E. B. Meek, M. Valcke, C. English, A. Boobis, and R. Brown. 2017. Evolution of chemical-specific adjustment factors (CSAF) based on recent international experience; Increasing utility and facilitating regulatory acceptance. Crit. Rev. Toxicol. 47::729–749. doi:https://doi.org/10.1080/10408444.2017.1303818.
- Blanchette, A., S. D. Burnett, I. Rusyn, and W. A. Chiu. 2021. A tiered approach to population-based in vitro testing for cardiotoxicity: Balancing estimates of potency and variability. Personal Communication.
- Blanchette, A. D., S. D. Burnett, F. A. Grimm, I. Rusyn, and W. A. Chiu. 2020. A Bayesian Method for population-wide cardiotoxicity hazard and risk characterization using an in vitro human model. Toxicol. Sci. 178::391–403. doi:https://doi.org/10.1093/toxsci/kfaa151.
- Bokkers, B. G. H., and W. Slob. 2007. Deriving a data-based interspecies assessment factor using the NOAEL and the benchmark dose approach. Critical Reviews in Toxicology 37 (5):355–73. doi:https://doi.org/10.1080/10408440701249224.
- Brown, M. F., T. P. Gratton, and J. A. Stuart. 2007. Metabolic rate does not scale with body mass in cultured mammalian cells. Am. J. Physiol. Regul. Integr. Comp. Physiol. 292:R2115–R2121. doi:https://doi.org/10.1152/ajpregu.00568.2006.
- Burnett, S. D., A. D. Blanchette, F. A. Grimm, J. S. House, D. M. Reif, F. A. Wright, W. A. Chiu, and I. Rusyn. 2019. Population-based toxicity screening in human induced pluripotent stem cell-derived cardiomyocytes. Toxicol. Appl. Pharmacol. 381:114711. doi:https://doi.org/10.1016/j.taap.2019.114711.
- Casadevall, A., and F. C. Fang. 2016. Rigorous science: A how-to guide. mBio 7 (6):e01902–1916. doi:https://doi.org/10.1128/mBio.01902-16.
- Chiu, W. A., and I. Rusyn. 2018. Advancing chemical risk assessment decision-making with population variability data: Challenges and opportunities. Mammalian Genome 29 (1–2):182–89. doi:https://doi.org/10.1007/s00335-017-9731-6.
- Chiu, W. A., F. A. Wright, and I. Rusyn. 2017. A tiered, Bayesian approach to estimating of population variability for regulatory decision-making. ALTEX 34:377–88. doi:https://doi.org/10.14573/altex.1608251.
- Croco, E., S. Marchionni, M. Bocchini, C. Angeloni, T. Stamato, C. Stefanelli, S. Hrelia, C. Sell, and A. Lorenzini. 2017. DNA damage detection by 53BP1: Relationship to species longevity. J. Gerontol. A Biol. Sci. Med. Sci. 72:763–70.
- Csiszar, A., A. Podlutsky, N. Podlutskaya, W. E. Sonntag, S. Z. Merlin, E. E. Philipp, K. Doyle, A. Davila, F. A. Recchia, P. Ballabh, et al. 2012. Testing the oxidative stress hypothesis of aging in primate fibroblasts: Is there a correlation between species longevity and cellular ROS production? The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 67 (8):841–52. doi:https://doi.org/10.1093/gerona/glr216.
- Domankevich, V., H. Eddini, A. Odeh, and I. Shams. 2018. Resistance to DNA damage and enhanced DNA repair capacity in the hypoxia-tolerant blind mole rat, Spalax. Journal of Experimental Biology 221:jeb174540. doi:https://doi.org/10.1242/jeb.174540.
- Gomes, N. M. V., O. A. Ryder, M. L. Houck, S. J. Charter, W. Walker, N. R. Forsyth, S. N. Austad, C. Venditti, M. Pagel, J. W. Shay, et al. 2011. Comparative biology of mammalian telomeres: Hypotheses on ancestral states and the roles of telomeres in longevity determination. Aging Cell 10 (5):761–68. doi:https://doi.org/10.1111/j.1474-9726.2011.00718.x.
- Gundert-Remy, U., and C. Sonich-Mullin. 2002. The use of toxicokinetic and toxicodynamic data in risk assessment: An international perspective. Science of the Total Environment 288 (1–2):3–11. doi:https://doi.org/10.1016/S0048-9697(01)01108-1.
- Haber, L. T., M. L. Dourson, B. C. Allen, R. C. Hertzberg, A. Parker, M. J. Vincent, A. Maier, and A. R. Boobis. 2018. Benchmark dose (BMD) modeling: Current practice, issues, and challenges. Critical Reviews in Toxicology 48 (5):387–415. doi:https://doi.org/10.1080/10408444.2018.1430121.
- Harper, J. M., A. B. Salmon, S. F. Leiser, A. T. Galecki, and R. A. Miller. 2007. Skin-derived fibroblasts from long-lived species are resistant to some, but not all, lethal stresses and to the mitochondrial inhibitor rotenone. Aging Cell 6 (1):1–13. doi:https://doi.org/10.1111/j.1474-9726.2006.00255.x.
- Harper, J. M., M. Wang, A. T. Galecki, J. Ro, J. B. Williams, and R. A. Miller. 2011. Fibroblasts from long-lived bird species are resistant to multiple forms of stress. Journal of Experimental Biology 214 (11):1902–10. doi:https://doi.org/10.1242/jeb.054643.
- Hart, R. W., and R. B. Setlow. 1974. Correlation between deoxyribonucleic acid excision-repair and life-span in a number of mammalian species. Proceedings of the National Academy of Sciences 71 (6):2169–73. doi:https://doi.org/10.1073/pnas.71.6.2169.
- Jimenez, A. G., J. Van Brocklyn, M. Wortman, J. B. Williams, and M. Sears. 2014. Cellular metabolic rate is influenced by life-history traits in tropical and temperate birds. PLoS One 9 (1):e87349. doi:https://doi.org/10.1371/journal.pone.0087349.
- Jimenez, A. G., and J. B. Williams. 2014. Cellular metabolic rates from primary dermal fibroblast cells isolated from birds of different body masses. Comparative Biochemistry and Physiology Part A: Molecular & Integrative Physiology 176:41–48. doi:https://doi.org/10.1016/j.cbpa.2014.07.009.
- Jones, K. E., J. Bielby, M. Cardillo, S. A. Fritz, J. O’Dell, C. D. L. Orme, K. Safi, W. Sechrest, E. H. Boakes, C. Carbone, et al. 2009. PanTHERIA: A species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90 (9):2648. doi:https://doi.org/10.1890/08-1494.1.
- Kapahi, P., M. E. Boulton, and T. B. L. Kirkwood. 1999. Positive correlation between mammalian life span and cellular resistance to stress. Free Radical Biology and Medicine 26 (5–6):495–500. doi:https://doi.org/10.1016/S0891-5849(98)00323-2.
- Kocher, T. D., W. K. Thomas, A. Meyer, S. V. Edwards, S. Paabo, F. X. Villablanca, and A. C. Wilson. 1989. Dynamics of mitochondrial DNA evolution in animals: Amplification and sequencing with conserved primers. Proceedings of the National Academy of Sciences 86 (16):6196–200. doi:https://doi.org/10.1073/pnas.86.16.6196.
- Krewski, D., M. Westphal, M. E. Andersen, G. M. Paoli, W. A. Chiu, M. Al-Zoughool, M. C. Croteau, L. D. Burgoon, and I. Cote. 2014. A framework for the next generation of risk science. Environmental Health Perspectives 122 (8):796–805. doi:https://doi.org/10.1289/ehp.1307260.
- Lorenzini, A., F. B. Johnson, A. Oliver, M. Tresini, J. S. Smith, M. Hdeib, C. Sell, V. J. Cristofalo, and T. D. Stamato. 2009. Significant correlation of species longevity with DNA double strand break recognition but not with telomere length. Mechanisms of Ageing and Development 130 (11–12):784–92. doi:https://doi.org/10.1016/j.mad.2009.10.004.
- Ma, S., A. Upneja, A. Galecki, Y.-M. Tsai, C. F. Burant, S. Raskind, Q. Zhang, Z. D. Zhang, A. Seluanov, V. Gorbunova, et al. 2016. Cell culture-based profiling across mammals reveals DNA repair and metabolism as determinants of species longevity. Elife 5:e19130. doi:https://doi.org/10.7554/eLife.19130.
- National Research Council. 2007. Toxicity Testing in the 21st Century: A Vision and a Strategy. Washington, DC: The National Academies Press.
- Ogburn, C. E., K. Carlberg, M. A. Ottinger, D. J. Holmes, G. M. Martin, and S. N. Austad. 2001. Exceptional cellular resistance to oxidative damage in long-lived birds requires active gene expression. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 56 (11):B468–B474. doi:https://doi.org/10.1093/gerona/56.11.B468.
- Paul Friedman, K., M. Gagne, L.-H. Loo, P. Karamertzanis, T. Netzeva, T. Sobanski, J. A. Franzosa, A. M. Richard, R. R. Lougee, A. Gissi, et al. 2020. Utility of in vitro bioactivity as a lower bound estimate of in vivo adverse effect levels and in risk-based prioritization. Toxicological Sciences 173 (1):202–25. doi:https://doi.org/10.1093/toxsci/kfz201.
- Pickering, A. M., M. Lehr, W. J. Kohler, M. L. Han, and R. A. Miller. 2015. Fibroblasts from longer-lived species of primates, rodents, bats, carnivores, and birds resist protein damage. The Journals of Gerontology: Series A 70 (7):791–99. doi:https://doi.org/10.1093/gerona/glu115.
- Price, P. S., R. E. Keenan, and J. C. Swartout. 2008. Characterizing interspecies uncertainty using data from studies of anti-neoplastic agents in animals and humans. Toxicology and Applied Pharmacology 233 (1):64–70. doi:https://doi.org/10.1016/j.taap.2008.03.026.
- Prinz, F., T. Schlange, and K. Asadullah. 2011. Believe it or not: How much can we rely on published data on potential drug targets? Nat Rev Drug Discov 10 : 712.
- Renwick, A. G. 1993. Data-derived safety factors for the evaluation of food additives and environmental contaminants. Food Additives and Contaminants 10 (3):275–305. doi:https://doi.org/10.1080/02652039309374152.
- Robin, X., N. Turck, A. Hainard, N. Tiberti, F. Lisacek, J. C. Sanchez, and M. Muller. 2011. pROC: An open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics 12: 77.
- Salmon, A. B., A. A. Sadighi Akha, R. Buffenstein, and R. A. Miller. 2008. Fibroblasts from naked mole-rats are resistant to multiple forms of cell injury, but sensitive to peroxide, ultraviolet light, and endoplasmic reticulum stress. J. Gerontol. A Biol. Sci. Med. Sci. 63:232–41.
- Schneider, K., J. Oltmanns, and M. Hassauer. 2004. Allometric principles for interspecies extrapolation in toxicological risk assessment—empirical investigations. Regulatory Toxicology and Pharmacology 39 (3):334–47. doi:https://doi.org/10.1016/j.yrtph.2004.03.001.
- Shapiro, A. J., S. Antoni, K. Z. Guyton, R. M. Lunn, D. Loomis, I. Rusyn, G. D. Jahnke, P. J. Schwingl, S. S. Mehta, J. Addington, et al. 2018. Software tools to facilitate systematic review used for cancer hazard identification. Environmental Health Perspectives 126 (10):104501. doi:https://doi.org/10.1289/EHP4224.
- Souci, L., and C. Denesvre. 2021. 3D skin models in domestic animals. Veterinary Research 52 (1):21. doi:https://doi.org/10.1186/s13567-020-00888-5.
- Swovick, K., D. Firsanov, K. A. Welle, J. R. Hryhorenko, J. P. Wise Sr., C. George, T. L. Sformo, A. Seluanov, V. Gorbunova, and S. Ghaemmaghami. 2021. Interspecies differences in proteome turnover kinetics are correlated with life spans and energetic demands. Molecular & Cellular Proteomics 20:100041. doi:https://doi.org/10.1074/mcp.RA120.002301.
- Tacutu, R., D. Thornton, E. Johnson, A. Budovsky, D. Barardo, T. Craig, E. Diana, G. Lehmann, D. Toren, J. Wang, et al. 2018. Human ageing genomic resources: New and updated databases. Nucleic Acids Research 46 (D1):D1083–D1090. doi:https://doi.org/10.1093/nar/gkx1042.
- Thomas, R. S., M. B. Black, L. Li, E. Healy, T.-M. Chu, W. Bao, M. E. Andersen, and R. D. Wolfinger. 2012. A comprehensive statistical analysis of predicting in vivo hazard using high-throughput in vitro screening. Toxicological Sciences 128 (2):398–417. doi:https://doi.org/10.1093/toxsci/kfs159.
- Tian, X., D. Firsanov, Z. Zhang, Y. Cheng, L. Luo, G. Tombline, R. Tan, M. Simon, S. Henderson, J. Steffan, et al. 2019. SIRT6 is responsible for more efficient DNA double-strand break repair in long-lived species. Cell 177 (3):e22. doi:https://doi.org/10.1016/j.cell.2019.03.043.
- U.S. Environmental Protection Agency. 2005. Guidelines for carcinogen risk assessment. Washington, DC: Risk Assessment Forum, US Environmental Protection Agency.
- U.S. EPA. 2011. Recommended Use of Body Weight^3/4 as the Default Method in Derivation of the Oral Reference Dose edited by Office of the Science Advisor Washington, DC: US Environmental Protection Agency
- U.S. EPA. 2014. Guidance for applying quantitative data to develop data-derived extrapolation factors for interspecies and intraspecies extrapolation, edited by Office of the Science Advisor. Washington, DC: Environmental Protection Agency.
- U.S. FDA. 2005. Guidance for industry : estimating the maximum safe starting dose in initial clinical trials for therapeutics in adult healthy volunteers.
- Ungvari, Z., and E. E. Philipp. 2011. Comparative Gerontology--From Mussels to Man. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 66A (3):295–97. doi:https://doi.org/10.1093/gerona/glq198.
- Ungvari, Z., D. Sosnowska, A. Podlutsky, P. Koncz, W. E. Sonntag, and A. Csiszar. 2011. Free radical production, antioxidant capacity, and oxidative stress response signatures in fibroblasts from Lewis dwarf rats: Effects of life span-extending peripubertal GH treatment. The Journals of Gerontology Series a : Biological Sciences and Medical Sciences 66A (5):501–10. doi:https://doi.org/10.1093/gerona/glr004.
- Wambaugh, J. F., B. A. Wetmore, C. L. Ring, C. I. Nicolas, R. G. Pearce, G. S. Honda, R. Dinallo, D. Angus, J. Gilbert, T. Sierra, et al. 2019. Assessing toxicokinetic uncertainty and variability in risk prioritization. Toxicological Sciences 172 (2):235–51. doi:https://doi.org/10.1093/toxsci/kfz205.
- Wetmore, B. A., J. F. Wambaugh, S. S. Ferguson, M. A. Sochaski, D. M. Rotroff, K. Freeman, H. J. Clewell 3rd, D. J. Dix, M. E. Andersen, K. A. Houck, et al. 2012. Integration of dosimetry, exposure, and high-throughput screening data in chemical toxicity assessment. Toxicological Sciences 125 (1):157–74. doi:https://doi.org/10.1093/toxsci/kfr254.
- WHO/IPCS. 2005. Chemical-specific adjustment factors for interspecies differences in human variability: Guidance document for use of data in dose/concentration-response assessment. Geneva, Switzerland: World Health Organization.
- WHO/IPCS. 2018. Guidance document on evaluating and expressing uncertainty in hazard characterization. Geneva, Switzerland: World Health Organization & International Programme on Chemical Safety.
- Zeise, L., F. Y. Bois, W. A. Chiu, D. Hattis, I. Rusyn, and K. Z. Guyton. 2013. Addressing human variability in next-generation human health risk assessments of environmental chemicals. Environmental Health Perspectives 121 (1):23–31. doi:https://doi.org/10.1289/ehp.1205687.