Features of the evidence base formation for the assessment and classification of the hazards of chemicals based on specific and long-term effects

Introduction. To eliminate the difficulties encountered in classifying chemicals by specific and long-term effects in accordance with the GHS, the Scientific Information and Analytical Center “Russian Register of Potentially Hazardous Chemical and Biological Substances” has developed a decision-making algorithm based on the weight of evidence. It includes a systematic assessment of the full range of available data, both confirming and refuting the effect, taking into account their contribution (from 1 to 3 points) according to the criteria of reliability, consistency, biological plausibility, dose-effect relationship, comparability of the effect observed in animals with potential consequences for human health. Evidence is ranked by the sum of points, and evidence with the lowest number of points is given priority when assessing and classifying the hazard of a chemical according to the GHS. The algorithm is applicable to all types of effects, including carcinogenicity, mutagenicity, reprotoxicity, sensitization, and effects on the endocrine system.

The purpose of the study was to demonstrate approaches to the evidence base formation for assessing and classifying the hazards of chemicals by specific and long-term effects, taking into account the characteristics of these types of exposure.

Material and methods. The analysis of national and international approaches to the evidence base formation for the assessment and classification of the hazards of chemicals with specific and long-term effects is carried out.

Results. The features of using a decision-making algorithm in assessing the mutagenic, carcinogenic, reprotoxic, sensitizing effects and effects of chemicals on the endocrine system are described, as well as the procedure for applying appropriate testing methods and interpreting the results.

Limitations. The research is limited to the analysis of open literary sources, including databases Scopus, Web of Science, PubMed, ResearchGate, Cyberleninka, RSCI, eLibrary.

Conclusion. Basic schemes for the formation of evidence bases for assessing and classifying chemical hazards based on specific and long-term effects were presented, taking into account the characteristics of these types of exposure, which contribute to the transparency and reliability of decision-making.

Compliance with ethical standards. The study does not require an opinion from the Bioethics Commission.

Authors’ contribution:
Khamidulina Kh.Kh., Tarasova E.V. – concept and design of the study, editing, approval of the final version of the article, responsibility for the integrity of all parts of the article;
Nazarenko A.K., Tverskaya A.S., Dorofeeva E.V., Zamkova I.V., Proskurina A.S., Rabikova D.N., Lastovetskiy M.L., Araslanov I.N., Aniskova Yu. Yu., Balashov P.E. – collecting and processing material, writing text, editing.

Conflict of interests. The authors declare the absence of obvious and potential conflicts of interest in connection with the publication of this article.

Funding. The study was carried out as part of the research project “Validation of alternative research methods in assessing the hazard and risk of exposure to chemicals on human health as a tool for regulating the safety of chemical factors” under the industry research program on hygiene for 2024–2025.

Received: November 5, 2025 / Accepted: November 25, 2025 / Published: January 15, 2026

1. Klimisch H.J., Andreae M., Tillmann U. A systematic approach for evaluating the quality of experimental toxicological and ecotoxicological data. Regul. Toxicol. Pharmacol. 1997; 25(1): 1–5. https://doi.org/10.1006/rtph.1996.1076

2. Martin P., Bladier C., Meek B., Bruyere O., Feinblatt E., Touvier M., et al. Weight of evidence for hazard identification: a critical review of the literature. Environ. Health Perspect. 2018; 126(7): 076001. https://doi.org/10.1289/ehp3067

3. Lee K.C., Guiney P.D., Menzie C.A., Belanger S.E. Advancing the weight of evidence approach to enable chemical environmental risk assessment for decision-making and achieving protection goals. Integr. Environ. Assess. Manag. 2023; 19(5): 1188–91. https://doi.org/10.1002/ieam.4803

4. Khamidulina Kh.Kh., Rabikova D.N., Tarasova E.V., Sinitskaya T.A., Zamkova I.V., Nazarenko A.K. Modern approaches to the assessment and classification of the hazard posed by substances with mutagenic effects. Health Risk Analysis. 2024; (4): 4–13. https://doi.org/10.21668/health.risk/2024.4.01.eng https://elibrary.ru/bmvzpk

5. Johnson G.E., Slob W., Doak S.H., Fellows M.D., Gollapudi B.B., Heflich R.H., et al. New approaches to advance the use of genetic toxicology analyses for human health risk assessment and regulatory decision-making. Toxicol. Res. 2015; 4(3): 667–76. https://doi.org/10.1039/C4TX00118D

6. Steiblen G., van Benthem J., Johnson G. Strategies in genotoxicology: Acceptance of innovative scientific methods in a regulatory context and from an industrial perspective. Mutat. Res. Genet. Toxicol. Environ. Mutagen. 2020; 853: 503171. https://doi.org/10.1016/j.mrgentox.2020.503171

7. Basei G., Zabeo A., Rasmussen K., Tsiliki G., Hristozov D. A Weight of Evidence approach to classify nanomaterials according to the EU Classification, Labelling and Packaging Regulation criteria. NanoImpact. 2021; 24: 100359. https://doi.org/10.1016/j.impact.2021.100359

8. Hartwig A., Arand M., Epe B., Guth S., Jahnke G., Lampen A., et al. Mode of action-based risk assessment of genotoxic carcinogens. Arch. Toxicol. 2020; 94(6): 1787–877. https://doi.org/10.1007/s00204-020-02733-2

9. Kumari M., Kumar A. Identification of component-based approach for prediction of joint chemical mixture toxicity risk assessment with respect to human health: A critical review. Food Chem. Toxicol. 2020; 143: 111458. https://doi.org/10.1016/j.fct.2020.111458

10. Chrz J., Hošíková B., Svobodová L., Očadlíková D., Kolářová H., Dvořáková M., et al. Comparison of methods used for evaluation of mutagenicity/genotoxicity of model chemicals – parabens. Physiol. Res. 2020; 69(Suppl. 4): S661–79. https://doi.org/10.33549/physiolres.934615

11. Adiga G.P., Ranjan B., Venkataramulu D., Krishnappa M., Ahuja V. P03-25: Predicting genotoxicity, carcinogenicity and skin sensitization of agrochemicals using OECD QSAR Toolbox, Toxtree, Pred-Skin and TEST. Toxicol. Lett. 2023; 384(Suppl. 1): S95. https://doi.org/10.1016/S0378-4274(23)00489-7

12. Chinen K., Malloy T. Multi-strategy assessment of different uses of QSAR under REACH analysis of alternatives to advance information transparency. Int. J. Environ. Res. Public Health. 2022; 19(7): 4338. https://doi.org/10.3390/ijerph19074338

13. Pawar G., Madden J.C., Ebbrell D., Firman J.W., Cronin M.T.D. In silico toxicology data resources to support read-across and (Q)SAR. Front. Pharmacol. 2019; 10: 561. https://doi.org/10.3389/fphar.2019.00561

14. Chien H.T., Roos P., Russel F.G.M., Theunissen P.T., van Meer P.J.K. The use of weight-of-evidence approaches to characterize developmental toxicity risk for therapeutic monoclonal antibodies in humans without in vivo studies. Regul. Toxicol. Pharmacol. 2024; 152: 105682. https://doi.org/10.1016/j.yrtph.2024.105682

15. Catlin N.R., Cappon G.D., Davenport S.D., Stethem C.M., Nowland W.S., Campion S.N., et al. New approach methodologies to confirm developmental toxicity of pharmaceuticals based on weight of evidence. Reprod. Toxicol. 2024; 129: 108686. https://doi.org/10.1016/j.reprotox.2024.108686

16. Hargitai R., Parráková L., Szatmári T., Monfort-Lanzas P., Galbiati V., Audouze K., et al. Chemical respiratory sensitization: Current status of mechanistic understanding, knowledge gaps and possible identification methods of sensitizers. Front. Toxicol. 2024; 6: 1331803. https://doi.org/10.3389/ftox.2024.1331803

17. Gilmour N., Reynolds J., Przybylak K., Aleksic M., Aptula N., Baltazar M.T., et al. Next generation risk assessment for skin allergy: Decision making using new approach methodologies. Regul. Toxicol. Pharmacol. 2022; 131: 105159. https://doi.org/10.1016/j.yrtph.2022.105159

18. Lee I., Na M., Lavelle M., Api A.M. Derivation of the no expected sensitization induction level for dermal quantitative risk assessment of fragrance ingredients using a weight of evidence approach. Food Chem. Toxicol. 2022; 159: 112705. https://doi.org/10.1016/j.fct.2021.112705

19. Khamidulina Kh.Кh., Tarasova E.V., Proskurina A.S. Conceptual approach to hazard assessment and classification of endocrine disruptors. Meditsina truda i ekologiya cheloveka. 2024; (3): 56–77. https://doi.org/10.24412/2411-3794-2024-10304 https://elibrary.ru/kgqtkq (in Russian)

20. Street M.E., Audouze K., Legler J., Sone H., Palanza P. Endocrine disrupting chemicals: current understanding, new testing strategies and future research needs. Int. J. Mol. Sci. 2021; 22(2): 933. https://doi.org/10.3390/ijms22020933