The Implementation Moonshot Project for Alternative Chemical Testing (IMPACT) toward a Human Exposome Project
Main Article Content
Abstract
The Human Exposome Project aims to revolutionize our understanding of how environmental exposures affect human health by systematically cataloging and analyzing the myriad exposures individuals encounter throughout their lives. This initiative draws a parallel with the Human Genome Project, expanding the focus from genetic factors to the dynamic and complex nature of environmental interactions. The project leverages advanced methodologies such as omics technologies, biomonitoring, microphysiological systems (MPS), and artificial intelligence (AI), forming the foundation of exposome intelligence (EI) to integrate and interpret vast datasets. Key objectives include identifying exposure-disease links, prioritizing hazardous chemicals, enhancing public health and regulatory policies, and reducing reliance on animal testing. The Implementation Moonshot Project for Alternative Chemical Testing (IMPACT), spearheaded by the Center for Alternatives to Animal Testing (CAAT), is a new element in this endeavor, driving the creation of a public-private partnership toward a Human Exposome Project with a stakeholder forum in 2025. Establishing robust infrastructure, fostering interdisciplinary collaborations, and ensuring quality assurance through systematic reviews and evidence-based frameworks are crucial for the project’s success. The expected outcomes promise transformative advancements in precision public health, disease prevention, and a more ethical approach to toxicology. This paper outlines the strategic imperatives, challenges, and opportunities that lie ahead, calling on stakeholders to support and participate in this landmark initiative for a healthier, more sustainable future.
Plain language summary
This paper outlines a proposal for a “Human Exposome Project” to comprehensively study how environmental exposures affect human health throughout our lives. The exposome refers to all the environmental factors we are exposed to, from chemicals to diet to stress. The project aims to use advanced technologies like artificial intelligence, lab-grown mini-organs, and detailed biological measurements to map how different exposures impact our health. This could help identify causes of diseases and guide better prevention strategies. Key goals include finding links between specific exposures and health problems, determining which chemicals are most concerning, improving public health policies, and reducing animal testing. The project requires collaboration between researchers, government agencies, companies, and others. While ambitious, this effort could revolutionize our understanding of environmental health risks. The potential benefits for improving health and preventing disease make this an important endeavor to a precise and comprehensive approach to public health and disease prevention.
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Abdelzaher, H., Tawfik, S. M., Nour, A. et al. (2022). Climate change, human health, and the exposome: Utilizing OMIC technologies to navigate an era of uncertainty. Front Public Health 10, 973000. doi:10.3389/fpubh.2022.973000
Alépée, N., Bahinski, T., Daneshian, M. et al. (2014). State-of-the-art of 3D cultures (organs-on-a-chip) in safety testing and pathophysiology – A t4 report. ALTEX 31, 441-477. doi:10.14573/altex.1406111
Ankley, G. T., Bennett, R. S., Erickson, R. J. et al. (2010). Adverse outcome pathways: A conceptual framework to support ecotoxicology research and risk assessment. Environ Toxicol Chem 29, 730-741. doi:10.1002/etc.34
Bailey, J., Knight, A. and Balcombe, J. (2005). The future of teratology research is in vitro. Biogenic Amines 19, 97-145. doi:10.1163/1569391053722755
Beilmann, M., Boonen, H., Czich, A. et al. (2019). Optimizing drug discovery by investigative toxicology: Current and future trends. ALTEX 36, 3-17. doi:10.14573/altex.1808181
Bouhifd, M., Hogberg, H. T., Kleensang, A. et al. (2014). Mapping the human toxome by systems toxicology. Basic Clin Pharmacol Toxicol 115, 24-31. doi:10.1111/bcpt.12198
Bouhifd, M., Andersen, M. E., Baghdikian, C. et al. (2015). The human toxome project. ALTEX 32, 112-124. doi:10.14573/altex.1502091
de Vries, R. B. M., Angrish, M., Browne, P. et al. (2021). Applying evidence-based methods to the development and use of adverse outcome pathways construct mechanistic frameworks for the development and use of non-animal toxicity tests. ALTEX 38, 336-347. doi:10.14573/altex.2101211
Escher, B. I., Hackermüller, J., Polte, T. et al. (2017). From the exposome to mechanistic understanding of chemical-induced adverse effects. Environ Inter 99, 97-106. doi:10.1016/j.envint.2016.11.029
Farhat, N., Tsaioun, K., Saunders-Hastings, P. et al. (2022). Systematic review in evidence-based risk assessment. ALTEX 39, 463-479. doi:10.14573/altex.2004111
Gao, P. (2021). The exposome in the era of One Health. Environ Sci Technol 55, 2790-2799. doi:10.1021/acs.est.0c07033
Gottmann, E., Kramer, S., Pfahringer, B. et al. (2001). Data quality in predictive toxicology: Reproducibility of rodent carcinogenicity experiments. Environ Health Perspect 109, 509-514. doi:10.1289/ehp.01109509
Gray, G. M., Li, P., Shlyakhter, I. et al. (1995). An empirical examination of factors influencing prediction of carcinogenic hazard across species. Regul Toxicol Pharmacol 22, 283-291. doi:10.1006/rtph.1995.0011
Haddad, N., Andrianou, X. D. and Makris, K. C. (2019). A scoping review on the characteristics of human exposome studies. Curr Pollution Rep 5, 378-393. doi:10.1007/s40726-019-00130-7
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. (2016). E-cigarettes and the need and opportunities for alternatives to animal testing. ALTEX 33, 211-224. doi:10.14573/altex.1606291
Hartung, T., FitzGerald, R., Jennings, P. et al. (2017). Systems toxicology – Real world applications and opportunities. Chem Res Toxicol 30, 870-882. doi:10.1021/acs.chemrestox.7b00003
Hartung, T. (2018). 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. (2023a). A call for a human exposome project. ALTEX 40, 4-33. doi:10.14573/altex.2301061
Hartung, T. (2023b). ToxAIcology – The evolving role of artificial intelligence in advancing toxicology and modernizing regulatory science. ALTEX 40, 559-570. doi:10.14573/altex.2309191
Hartung, T. (2023c). AI as the new frontier in chemical risk assessment. Front Artif Intell 4, 559-570. doi:10.3389/frai.2023.1269932
Hartung, T., Smirnova, L., Morales Pantoja, I. E. et al. (2023). The Baltimore declaration toward the exploration of organoid intelligence. Front Sci 1, 1017235. doi:10.3389/fsci.2023.1017235
Hartung, T. and Tsaioun, K. (revised). Evidence-based approaches in toxicology: Their origins, challenges, and future directions. Evid Based Toxicol.
Hoffmann, S., Hartung, T. and Stephens, M. (2016). Evidence-based toxicology. Adv Exp Med Biol 856, 231-241. doi:10.1007/978-3-319-33826-2_9
Hoffmann, S., Aiassa, E., Angrish, M. et al. (2022a). Application of evidence-based methods to construct mechanism-driven chemical assessment frameworks. ALTEX 39, 499-518. doi:10.14573/altex.2202141
Hoffmann, S., Whaley, P. and Tsaioun, K. (2022b). How evidence-based methodologies can help identify and reduce uncertainty in chemical risk assessment. ALTEX 39, 175‐182. doi:10.14573/altex.2201131
Hurtt, M. E., Cappon, G. D. and Browning, A. (2003). Proposal for a tiered approach to developmental toxicity testing for veterinary pharmaceutical products for food-producing animals. Food Chem Toxicol 41, 611-619. doi:10.1016/s0278-6915(02)00326-5
Karlsson, O., Rocklöv, J., Lehoux, A. P. et al. (2021). The human exposome and health in the Anthropocene. Inter J Epidem 50, 378-389, doi:10.1093/ije/dyaa231
Kleinstreuer, N. and Hartung, T. (2024). Artificial intelligence (AI) – It’s the end of the tox as we know it (and I feel fine) – AI for predictive toxicology. Arch Toxicol 98, 735-754. doi:10.1007/s00204-023-03666-2
Kleensang, A., Maertens, A., Rosenberg, M. et al. (2014). Pathways of toxicity. ALTEX 31, 53-61. doi:10.14573/altex.1309261
Knight, J., Hartung, T. and Rovida, C. (2023). 4.2 million and counting… the animal toll for REACH systemic toxicity studies. ALTEX 40, 389-407. doi:10.14573/altex.2303201
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
Krewski, D., Saunders-Hastings, P., Baan, R. et al. (2022). Development of an evidence-based risk assessment framework. ALTEX 39, 667-693. doi:10.14573/altex.2004041
Leist, M., Ghallab, A., Graepel, R. et al. (2017). Adverse outcome pathways: Opportunities, limitations and open questions. Arch Toxicol 31, 221-229. doi:10.1007/s00204-017-2045-3
Logan, A. C., Prescott, S. L., Haahtela, T. et al. (2018). The importance of the exposome and allostatic load in the planetary health paradigm. J Physiol Anthropol 37, 15. doi:10.1186/s40101-018-0176-8
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
Maertens, A., Golden, E., Luechtefeld, T. H. et al. (2022). Probabilistic Risk Assessment – the Keystone for the Future of Toxicology. ALTEX 39, 3-29. doi:10.14573/altex.2201081
Maertens, A., Luechtefeld, T. and Hartung, T. (2024a). Alternative methods go green! Green toxicology as a sustainable approach for assessing chemical safety and designing safer chemicals. ALTEX 41, 3-19. doi:10.14573/altex.2312291
Maertens, A., Antignac, E., Benfenati, E. et al. (2024b). The probable future of toxicology - probabilistic risk assessment. ALTEX 41, 273–281. doi: 10.14573/altex.2310301.
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
Menon, J. M. L., Struijs, F. and Whaley, P. (2022). The methodological rigour of systematic reviews in environmental health. Crit Rev Toxicol 52, 167-187. doi:10.1080/10408444.2022.2082917
Miller, G. W. (2013). The Exposome: A Primer. Waltham, MA: Academic Press, Elsevier, Inc.
Miller, G. W. and Jones, D. P. (2014). The nature of nurture: Refining the definition of the exposome. Toxicol Sci 137, 1-2. doi:10.1093/toxsci/kft251
Monticello, T. M., Jones, T. W., Dambach, D. M. et al. (2017). Current nonclinical testing paradigm enables safe entry to first-In-human clinical trials: The IQ consortium nonclinical to clinical translational database. Toxicol Appl Pharmacol 334, 100-109. doi:10.1016/j.taap.2017.09.006
Morales Pantoja, I. E., Smirnova, L., Muotri, A. R. et al. (2023). First organoid intelligence (OI) workshop to form an OI community. Front Artif Intell 6, 1116870. doi:10.3389/frai.2023.1116870
Niedzwiecki, M. M., Walker, D. I., Vermeulen, R. et al. (2019). The exposome: Molecules to populations. Annu Rev Pharmacol Toxicol 59, 107-127. doi:10.1146/annurev-pharmtox-010818-021315
NRC – National Research Council (2007). Toxicity Testing in the 21st Century: A Vision and a Strategy. Washington, DC, USA: The National Academies Press.
Olson, H., Betton, G., Robinson, D. et al. (2000). Concordance of the toxicity of pharmaceuticals in humans and in animals. Regul Toxicol Pharmacol 32, 56-67. doi:10.1006/rtph.2000.1399
Pamies, D., Barreras, P., Block, K. et al. (2017a). A human brain microphysiological system derived from iPSC to study central nervous system toxicity and disease. ALTEX 34, 362-376. doi:10.14573/altex.1609122
Pamies, D., Bal-Price, A. and Simeonov, A. (2017b). Good cell culture practice for stem cells and stem-cell-derived models. ALTEX 34, 95-132. doi:10.14573/altex.1607121
Pamies, D., Bal-Price, A., Chesné, C. et al. (2018). Advanced good cell culture practice for human primary, stem cell-derived and organoid models as well as microphysiological systems. ALTEX 35, 353-378. doi:10.14573/altex.1710081
Pamies, D., Leist, M., Coecke, S. et al. (2020). Good cell and tissue culture practice 2.0 (GCCP 2.0) – Draft for stakeholder discussion and call for action. ALTEX 37, 490-492. doi:10.14573/altex.2007091
Pamies, D., Leist, M., Coecke, S. et al. (2022). Guidance document on good cell and tissue culture practice 2.0 (GCCP 2.0). ALTEX 39, 30-70. doi:10.14573/altex.2111011
Ramos, R. G. and Olden, K. (2008). Gene-environment interactions in the development of complex disease phenotypes. Int J Environ Res Public Health 5, 4-11. doi:10.3390/ijerph5010004
Roth, A. and MPS-WS Berlin 2019 (2021). Human microphysiological systems for drug development. Science 373, 1304-1306. doi:10.1126/science.abc3734
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
Rovida, C., Asakura, S., Daneshian, M. et al. (2015). Toxicity testing in the 21st century beyond environmental chemicals. ALTEX 32, 171-181. doi:10.14573/altex.1506201
Rovida, C., Busquet, F., Leist, M. et al. (2023). REACH out-numbered! The future of REACH and animal numbers. ALTEX 40, 367-388. doi:10.14573/altex.2307121
Sarigiannis, D. A., Hartung, T. and Karakitsios, S. P. (2021). The exposome – A new paradigm for non-animal toxicology and integrated risk assessment. In A. M. Tsatsakis, Toxicological Risk Assessment and Multi-System Health Impacts from Exposure (23-30). London, UK: Elsevier, Academic Press.
Sauer, J. M., Hartung, T., Leist, M. et al. (2015). Systems toxicology: The future of risk assessment. Inter J Toxicol 34, 346-348. doi:10.1177/1091581815576551
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
Sillé, F. C. M., McCormack, M. and Hartung, T. (2022). The exposome applied: A step toward defining the totality of environmental exposures in asthma. Am J Respir Crit Care Med 206, 1187-1188. doi:10.1164/rccm.202207-1430ED
Sillé, F. C. M. and Hartung, T. (2024). Metabolomics in preclinical drug safety assessment: Current status and future trends. Metabolites 14, 98. doi:10.3390/metabo14020098
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
Smirnova, L., Morales Pantoja, I. E. and Hartung, T. (2023). Organoid intelligence (OI) – The ultimate functionality of a brain microphysiological system. ALTEX 40, 191-203. doi:10.14573/altex.2303261
Smirnova, L. and Hartung, T. (2024). The promise and potential of brain organoids. Adv Healthc Mater, 2302745. doi:10.1002/adhm.202302745
von Aulock, S., Busquet, F., Locke, P. et al. (2022). Engagement of scientists with the public and policymakers to promote alternative methods. ALTEX 39, 543-559. doi:10.14573/altex.2209261
Wang, B. and Gray, G. (2014). 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
Whaley, P., Piggott, T., Morgan, R. L. et al. (2022). Biological plausibility in environmental health systematic reviews: A GRADE concept paper. Environ Inter 162, 107109. doi:10.1016/j.envint.2022.107109
Wild, C. P. (2005). Complementing the genome with an “exposome”: The outstanding challenge of environmental exposure measurement in molecular epidemiology. Cancer Epidemiol Biomarkers Prev 14, 1847-1850. doi:10.1158/1055-9965