The state of the scientific revolution in toxicology

Main Article Content

Thomas Hartung , Aristides M. Tsatsakis
[show affiliations]

Abstract

 Science changes in waves, the so-called paradigm shifts or scientific revolutions. This concept was prominently elabo­rated by Thomas S. Kuhn more than 50 years ago in what remains one of the most cited science philosophy books of all time. Kuhn described how “normal science” experiences anomalies, which bring it to crisis and revolution from which a new, immature scientific paradigm results, which over time becomes the new normal. Building on an analysis on how this applies to toxicology and its change in approach in 2008, we concluded at the time that toxicology had encountered a number of such anomalies and was moving into crisis. Here, the progress along Kuhn’s trajectory over the last 12 years of a scientific revolution is discussed. We conclude that this decade has shown up even more anomalies, and the perception of crisis has spread and consolidated. Indications of revolutionary paradigm changes are emerging.

Article Details

How to Cite
Hartung, T. and Tsatsakis, A. M. (2021) “The state of the scientific revolution in toxicology”, ALTEX - Alternatives to animal experimentation, 38(3), pp. 379–386. doi: 10.14573/altex.2106101.
Section
Food for Thought ...
References

Beilmann, M., Boonen, H., Czich, A. et al. (2019). Optimizing drug discovery by investigative toxicology: Current and future trends. ALTEX 36, 289-313. doi:10.14573/altex.1808181

Bottini, A. A., Amcoff, P. and Hartung, T. (2007). Food for thought … on globalization of alternative methods. ALTEX 24, 255-261. doi:10.14573/altex.2007.4.255

Bottini, A. A. and Hartung, T. (2009). Food for thought … on economics of animal testing. ALTEX 26, 3-16. doi:10.14573/altex.2009.1.3

Bottini, A. A. and Hartung, T. (2010). The economics of animal testing. ALTEX 27, Spec Issue 1, 67-77.

Busquet, F., Kleensang, A., Rovida, C. et al. (2020a). New European Union statistics on laboratory animal use – What really counts! ALTEX 37, 167-186. doi:10.14573/altex.2003241

Busquet, F., Hartung, T., Rovida, C. et al. (2020b). Harnessing the power of novel animal-free test methods for the development of COVID-19 drugs and vaccines. Arch Toxicol 94, 2263-2272. doi:10.1007/s00204-020-02787-2

Collins, F. S. (2011). Reengineering translational science: The time is right. Sci Transl Med 3, 90cm17. doi:10.1126/scitranslmed.3002747

Davis, M., Boekelheide, K., Boverhof, D. R. et al. (2013). The new revolution in toxicology: The good, the bad, and the ugly. Ann N Y Acad Sci 1278, 11-24. doi:10.1016/j.fct.2018.03.052

Docea, A. O., Gofita, E., Goumenou, M. et al. (2018). Six months exposure to a real life mixture of 13 chemicals’ below individual NOAELs induced non monotonic sex-dependent biochemical and redox status changes in rats. Food Chem Toxicol 115, 470-481. doi:10.1016/j.fct.2018.03.052

Fountoucidou, P., Veskoukis, A. S., Kerasioti, E. et al. (2019). A mixture of routinely encountered xenobiotics induces both redox adaptations and perturbations in blood and tissues of rats after a long-term low-dose exposure regimen: The time and dose issue. Toxicol Lett 317, 24-44. doi:10.1016/j.toxlet.2019.09.015

Hartung, T. (2008a). Towards a new toxicology – Evolution or revolution? Altern Lab Anim 36, 635-639. doi:10.1177/026119290803600607

Hartung, T. (2008b). Food for thought … on alternative methods for cosmetics safety testing. ALTEX 25, 147-162. doi:10.14573/altex.2008.3.147

Hartung, T. and Koëter, H. (2008). Food for thought … on alternative methods for food safety testing. ALTEX 25, 259-264. doi:10.14573/altex.2008.4.259

Hartung, T. and Hoffmann, S. (2009). Food for thought on … in silico methods in toxicology. ALTEX 26, 155-166. doi:10.14573/altex.2009.3.155

Hartung, T. and Rovida, C. (2009a). Chemical regulators have overreached. Nature 460, 1080-1081. doi:10.1038/4601080a

Hartung, T. and Rovida, C. (2009b). That which must not, cannot be... a reply to the EChA and EDF responses to the REACH analysis of animal use and costs. ALTEX 26, 307-311. doi:10.14573/altex.2009.4.307

Hartung, T. (2010a). Food for thought … on alternative methods for chemical safety testing. ALTEX 27, 3-14. doi:10.14573/altex.2010.1.3

Hartung, T. (2010b). Comparative analysis of the revised Directive 2010/63/EU for the protection of laboratory animals with its predecessor 86/609/EEC – A t4 report. ALTEX 27, 285-303. doi:10.14573/altex.2010.4.285

Hartung, T. (2010c). Food for thought … on alternative methods for nanoparticle safety testing. ALTEX 27, 87-95. doi:10.14573/altex.2010.2.87

Hartung, T. and McBride, M. (2011). Food for thought … on mapping the human toxome. ALTEX 28, 83-93. doi:10.14573/altex.2011.2.083

Hartung, T. and Sabbioni, E. (2011). Alternative in vitro assays in nanomaterial toxicology. WIREs Nanomed Nanobiotechnol 3, 545-573. doi:10.1002/wnan.153

Hartung, T. (2013). Look back in anger – What clinical studies tell us about preclinical work. ALTEX 30, 275-291. doi:10.14573/altex.2013.3.275

Hartung, T. (2016a). E-cigarettes and the need and opportunities for alternatives to animal testing. ALTEX 33, 211-224. doi:10.14573/altex.1606291

Hartung, T. (2016b). Making big sense from big data in toxicology by read-across. ALTEX 33, 83-93. doi:10.14573/altex.1603091

Hartung, T. (2017). Evolution of toxicological science: The need for change. Int J Risk Assess Manag 20, 21-45. doi:10.1504/IJRAM.2017.082570

Hartung, T. (2018a). Perspectives on in vitro to in vivo extrapolations. Appl In Vitro Toxicol 4, 305-316. doi:10.1089/aivt.2016.0026

Hartung, T. (2018b). Rebooting the generally recognized as safe (GRAS) approach for food additive safety in the US. ALTEX 35, 3-25. doi:10.14573/altex.1712181

Hartung, T. (2018c). Making big sense from big data. Front Big Data 1, 5. doi:10.3389/fdata.2018.00005

Hartung, T. (2019). Predicting toxicity of chemicals: Software beats animal testing. EFSA J 17, Issue S1, e170710. doi:10.2903/j.efsa.2019.e170710

Hernández, A. F. and Tsatsakis, A. M. (2017). Human exposure to chemical mixtures: Challenges for the integration of toxicology with epidemiology data in risk assessment. Food Chem Toxicol 103, 188-193. doi:10.1016/j.fct.2017.03.012

Hernandez, A. F., Buha, A., Constantin, C. et al. (2019). Critical assessment and integration of separate lines of evidence for risk assessment of chemical mixtures. Arch Toxicol 93, 2741-2757. doi:10.1007/s00204-019-02547-x

Juberg, D. R., Knudsen, T. B., Sander, M. et al. (2008). FutureTox III: Bridges for translation. Toxicol Sci 155, 22-31. doi:10.1093/toxsci/kfw194

Kerry, R., Maddocks, M. and Mumford, S. (2008). Philosophy of science and physiotherapy: An insight into practice. Physiother Theory Pract 24, 397-407. doi:10.1080/09593980802511797

Kleensang, A., Maertens, A., Rosenberg, M. et al. (2014). Pathways of toxicity. ALTEX 31, 53-61. doi:10.14573/altex.1309261

Krewski, D., Andersen, M., Tyshenko, M. G. et al. (2020). Toxicity testing in the 21st century: Progress in the past decade and future perspectives. Arch Toxicol 94, 1-58. doi:10.1007/s00204-019-02613-4

Kuhn, T. S. (1970). The Structure of Scientific Revolutions (212 pp). 2nd edition. Chicago, IL, USA: University of Chicago Press.

Luechtefeld, T., Maertens, A., Russo, D. P. et al. (2016). Global analysis of publicly available safety data for 9,801 substances registered under REACH from 2008-2014. ALTEX 33, 95-109. doi:10.14573/altex.1510052

Luechtefeld, T. and Hartung, T. (2017). Computational approaches to chemical hazard assessment. ALTEX 34, 459-478. doi:10.14573/altex.1710141

Luechtefeld, T., Marsh, D., Rowlands, C. et al. (2018). Machine learning of toxicological big data enables read-across structure activity relationships (RASAR) outperforming animal test reproducibility. Toxicol Sci 165, 198-212. doi:10.1093/toxsci/kfy152

Marx, U., Andersson, T. B., Bahinski, A. et al. (2016). Biology-inspired microphysiological system approaches to solve the prediction dilemma of substance testing using animals. ALTEX 33, 272-321. doi:10.14573/altex.1603161

Marx, U., Akabane, T., Andersson, T. B. et al. (2020). Biology-inspired microphysiological systems to advance medicines for patient benefit and animal welfare. ALTEX 37, 364-394. doi:10.14573/altex.2001241

Meigs, L., Smirnova, L., Rovida, C. et al. (2018). Animal testing and its alternatives – The most important omics is economics. ALTEX 35, 275-305. doi:10.14573/altex.1807041

Moné, M. J., Pallocca, G., Escher, S. E. et al. (2020). Setting the stage for next-generation risk assessment with non-animal approaches: The EU-ToxRisk project experience. Arch Toxicol 94, 3581-3592. doi:10.1007/s00204-020-02866-4

Rovida, C. and Hartung, T. (2009). Re-evaluation of animal numbers and costs for in vivo tests to accomplish REACH legislation requirements. ALTEX 26, 187-208. doi:10.14573/altex.2009.3.187

Sagan, C. (1987). Special report CSICOP’s 1987 conference in Pasadena. Skeptical Inquirer 121987, 12..

Sergievich, A. A., Khoroshikh, P. P., Artemenko, A. F. et al. (2020). Behavioral impacts of a mixture of six pesticides on rats. Sci Total Environ 727, 138491. doi:10.1016/j.scitotenv.2020.138491

Silbergeld, E. K., Contreras, E. Q., Hartung, T. et al. (2011). Nanotoxicology: “The end of the beginning” – Signs on the roadmap to a strategy for assuring the safe application and use of nanomaterials. ALTEX 28, 236-241. doi:10.14573/altex.2011.3.236

Sillé, F. C. M., Karakitsios, S., Kleensang, A. et al. (2020). The exposome – A new approach for risk assessment. ALTEX 37, 3-23. doi:10.14573/altex.2001051

Smirnova, L., Harris, G., Leist, M. et al. (2015). Cellular resilience. ALTEX 32, 247-260. doi:10.14573/altex.1509271

Smirnova, L., Kleinstreuer, N., Corvi, R. et al. (2018). 3S – Systematic, systemic, and systems biology and toxicology. ALTEX 35, 139-162. doi:10.14573/altex.1804051

Tsaioun, K., Blaauboer, B. J. and Hartung, T. (2016). Evidence-based absorption, distribution, metabolism, excretion and toxicity (ADMET) and the role of alternative methods. ALTEX 33, 343-358. doi:10.14573/altex.1610101

Tsatsakis, A. M., Docea, A. O. and Tsitsimpikou, C. (2016). New challenges in risk assessment of chemicals when simulating real exposure scenarios; simultaneous multi-chemicals’ low dose exposure. Food Chem Toxicol 96, 174-176. doi:10.1016/j.fct.2016.08.011

Tsatsakis, A. M., Docea, A. O., Calina, D. et al. (2019a). Neurobehavioral effects of low dose toxic chemical mixtures in real-life risk simulation (RLRS) in rats. Food Chem Toxicol 125, 141-149. doi:10.1016/j.fct.2018.12.043

Tsatsakis, A., Docea, A. O., Constantin, C. et al. (2019b). Genotoxic, cytotoxic, and cytopathological effects in rats exposed for 18 months to a mixture of 13 chemicals in doses below NOAEL levels. Toxicol Lett 316, 154-170. doi:10.1016/j.toxlet.2019.09.004

Tsatsakis, A., Tyshko, N. V., Docea, A. O. et al. (2019c). The effect of chronic vitamin deficiency and long term very low dose exposure to 6 pesticides mixture on neurological outcomes – A real-life risk simulation approach. Toxicol Lett 315, 96-106. doi:10.1016/j.toxlet.2019.07.026

Wang, B. and Gray, G. (2016). Concordance of noncarcinogenic endpoints in rodent chemical bioassays. Risk Anal 35, 1154-1166. doi:10.1111/risa.12314

Wang, Z., Walker, G. W., Muir, D. C. G. et al. (2020). Toward a global understanding of chemical pollution: A first comprehensive analysis of national and regional chemical inventories. Environ Sci Technol 54, 2575-2584. doi:10.1021/acs.est.9b06379

Most read articles by the same author(s)

1 2 3 4 5 6 7 8 9 10 > >>