Virtual control groups in non-clinical toxicology – A replicability challenge

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Thomas Steger-Hartmann , Guillemette Duchateau-Nguyen, Frank Bringezu, Manuela Onidi, Martina Stirn
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Steger-Hartmann, T. (2025) “Virtual control groups in non-clinical toxicology – A replicability challenge”, ALTEX - Alternatives to animal experimentation. doi: 10.14573/altex.2503061.
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Adedeji, A. O. and Naor, A. W. (2024). Virtual control groups in non-clinical toxicity studies: Impacts on toxicologic clinical pathology data interpretation. Toxicol Path 53, 164-172. doi:10.1177/01926233241300310

Adriaens, E., Barroso, J., Eskes, C. et al. (2014) Retrospective analysis of the Draize test for serious eye damage/eye irritation: importance of understanding the in vivo endpoints under UN GHS/EU CLP for the development and evaluation of in vitro test methods. Arch Toxicol 88, 701–723. doi:10.1007/s00204-013-1156-8

Andaya, R., Sullivan, R., Pourmohamad, T. et al. (2024). A proof-of-concept rat toxicity study highlights the potential utility and challenges of virtual control groups. ALTEX 41, 647–659. doi:10.14573/altex.2404201

Arnouts, S. J. A. C., Crezee, T., Dycke, K. C. G. H. V. et al. (2024). There is no need for overnight fasting of rats in regulatory toxicology studies. Toxicology 509, 153937. doi:10.1016/j.tox.2024.153937

Braakhuis, H. M., Theunissen, P., Slob, W. et al. (2019). Testing developmental toxicity in a second species: are the differences due to species or replication error? Regul Toxicol Pharmacol 107, 104410. doi:10.1016/j.yrtph.2019.104410

Browne, P., Judson, R. S., Casey, W. M. et al. (2015). Screening Chemicals for Estrogen Receptor Bioactivity Using a Computational Model, Environ Sci Techn 49, 8804-8814. doi:10.1021/acs.est.5b02641

Dumont, C., Barroso, J., Matys, I. et al. (2016). Analysis of the Local Lymph Node Assay (LLNA) variability for assessing the prediction of skin sensitisation potential and potency of chemicals with non-animal approaches. Toxicol in Vitro 34, 220-228. doi:10.1016/j.tiv.2016.04.008

Goicoechea, M., Cía, F., San José, C. et al. (2007). Minimizing creatine kinase variability in rats for neuromuscular research purposes. Lab Anim 42, 19–25. doi:10.1258/la.2007.06006e

Golden, E., Allen, D., Amberg, A. et al. (2024). Toward implementing virtual control groups in nonclinical safety studies: Workshop report and roadmap to implementation. ALTEX 41, 282–301. doi:10.14573/altex.2310041

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

Gurjanov, A., Vieira-Vieira, C., Vienenkoetter, J. et al. (2024). Replacing concurrent controls with virtual control groups in rat toxicity studies. Regul Toxicol Pharmacol 148, 105592. doi:10.1016/j.yrtph.2024.105592

Kandárová, H., Liebsch, M. Schmidt, E. et al. (2006). Assessment of the Skin Irritation Potential of Chemicals by Using the SkinEthic Reconstructed Human Epidermal Model and the Common Skin Irritation Protocol Evaluated in the ECVAM Skin Irritation Validation Study, Altern Lab Anim 34, 393-406. doi:10.1177/026119290603400407

Karmaus, A. L., Mansouri, K., To, K. T. et al. (2022). Evaluation of Variability Across Rat Acute Oral Systemic Toxicity Studies, Toxicol Sci 188, 34–47. doi:10.1093/toxsci/kfac042

Kluxen, F. M. (2024). Historical control data of rare events: Issues, chronological patterns and their relevance for toxicological evaluations. Regul Toxicol Pharmacol 151, 105673. doi:10.1016/j.yrtph.2024.105673

Luechtefeld, T., Maertens, A., Russo, D. P. et al. (2016). Analysis of Draize eye irritation testing and its prediction by mining publicly available 2008-2014 REACH data, ALTEX 33, 123-134. doi:10.14573/altex.1510053

Matsuzawa, T., Nomura, M., Unno, T. (2008). Clinical pathology reference ranges of laboratory animals. J Vet Med Sci 55(3), 351-362. doi:10.1292/jvms.55.351

Mecklenburg, L., Lenz, S., Hempel, G. (2023). How important are concurrent vehicle control groups in (sub)chronic non-human primate toxicity studies conducted in pharmaceutical development? An opportunity to reduce animal numbers. PLoS ONE 18, e0282404. doi:10.1371/journal.pone.0282404

National Academies of Sciences, Engineering, and Medicine. (2019). Reproducibility and replicability in science. Washington, DC: The National Academies Press. doi:10.17226/25303

OECD (2007), Test No. 440: Uterotrophic Bioassay in Rodents: A short-term screening test for oestrogenic properties, OECD Guidelines for the Testing of Chemicals, Section 4, OECD Publishing, Paris, doi:10.1787/9789264067417-en

OECD (2010), Test No. 429: Skin Sensitisation: Local Lymph Node Assay, OECD Guidelines for the Testing of Chemicals, Section 4, OECD Publishing, Paris, doi:10.1787/9789264071100-en

OECD (2021), Test No. 439: In Vitro Skin Irritation: Reconstructed Human Epidermis Test Method, OECD Guidelines for the Testing of Chemicals, Section 4, OECD Publishing, Paris, doi:10.1787/9789264242845-en

OECD (2023), Test No. 405: Acute Eye Irritation/Corrosion, OECD Guidelines for the Testing of Chemicals, Section 4, OECD Publishing, Paris, doi:10.1787/9789264185333-en

OECD (2015), Test No. 404: Acute Dermal Irritation/Corrosion, OECD Guidelines for the Testing of Chemicals, Section 4, OECD Publishing, Paris, doi:10.1787/9789264242678-en

Palazzi, X., Anger, L. T., Boulineau, T. et al. (2024). Points to consider regarding the use and implementation of virtual controls in nonclinical general toxicology studies. Regul Toxicol Pharmacol 150, 105632. doi:10.1016/j.yrtph.2024.105632

Pechacek, N., Osorio, M., Caudill, J. et al. (2015). Evaluation of the toxicity data for peracetic acid in deriving occupational exposure limits: A minireview, Toxicol Lett 233, 45-57. doi:10.1016/j.toxlet.2014.12.014

Rooney, J. P., Choksi, N. Y., Ceger, P. et al. (2021). Analysis of variability in the rabbit skin irritation assay, Regul Toxicol Pharmacol 122, 104920. doi:10.1016/j.yrtph.2021.104920

Sato, G., Nakajima, M., Sakai, K. et al. (2024). Potential issues associated with the introduction of virtual control groups into non-clinical toxicology studies. Translat Regul Sci 6, 1-9. doi:10.33611/trs.2023-009

Spielmann, H., Hoffmann, S., Liebsch, M. et al. (2007). The ECVAM international validation study on in vitro tests for acute skin irritation: report on the validity of the EPISKIN and EpiDerm assays and on the Skin Integrity Function Test. Altern Lab Anim 35, 559-601. doi:10.1177/026119290703500614

Steger-Hartmann, T., Kreuchwig, A., Vaas, L. et al. (2020). Introducing the concept of virtual control groups into preclinical toxicology testing. ALTEX 37, 343–349. doi:10.14573/altex.2001311

Steger-Hartmann, T., Sanz F., Bringezu, F., Soininen, I. (2024). IHI VICT3R: Developing and Implementing Virtual Control Groups to Reduce Animal Use in Toxicology Research. Toxicol Pathol. doi:10.1177/01926233241303906

Vermeulen, J. K., De Vries, A., Schlingmann F., Remie R. (1997). Food deprivation: common sense or nonsense? Animal Technology 48, 45-54.

Wright, P. S. R., Smith G. F., Briggs K. A. et al. (2023) Retrospective analysis of the potential use of virtual control groups in preclinical toxicity assessment using the eTOX database. Regul Toxicol Pharmacol, 138, 105309. doi:10.1016/j.yrtph.2022.105309

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