Applicability of NAMs to support a read-across based hazard assessment workflow for systemic toxicity: a conazole case study

Abstract This work explores the applicability of new approach methodologies (NAMs) using a read-across approach to predict systemic toxicity with liver as the critical target organ, and derive a point of departurefor the target compound (TC) difenoconazole. Eight conazoles were used as source compounds (SCs), alongside metabolites hydroxyitraconazole and 1,2,4-triazole. The case study was structured according to the Alternative Safety Profiling Algorithm (ASPA) workflow developed within the RISK-HUNT3R project. Hierarchical clustering using chemical fingerprints identified similarity of different SCs to the TC, supporting their inclusion in the read-across analysis. A broad screening panel of NAMs, including nuclear receptor reporter assays, ToxProfiler, Cell Painting PLUS, transcriptomics in primary human hepatocytes and H295R steroidogenesis assays, was used to characterize biological activity of the TC and SCs and to substantiate the structure-based read-across. In a first prediction round, the nearest neighbour quantitative read-across approach (based on allometrically-scaled human lowest-observed-adverse-effect levels (LOAELs) of the SC) was used to predict 6.57 mg/kg/day as the LOAEL of the TC. This closely aligned with the in vivo-based value of 4.88 mg/kg/day. In a second approach, data from NAMs were used to predict human equivalent dose (HED), and the respective LOAELs of SC and TC, based on physiologically based kinetic modelling with quantitative in vitro to in vivo extrapolation. The HED derived from NAMs was approximately ten-fold lower than the LOAELs from traditional approaches. This case study illustrates suitable (ASPA-guided) approaches as well as the toxicological applicability of a NAM-based read-across assessment to obtain safe/conservative estimates of toxicity. Graphical Abstract A stepwise procedure was used in this work for assessment of systemic toxicity of the target compound, difenoconazole, using a read-across approach

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Journal
Archives of Toxicology
Published
2026-09-30
DOI
https://doi.org/10.1007/s00204-026-04554-1
Primary Topic
Computational Drug Discovery Methods
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article
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article

Applicability of NAMs to support a read-across based hazard assessment workflow for systemic toxicity: a conazole case study

Amer Jamalpoor, Jenny Irwan, Tamara Meijer, Barira Islam et al.
Archives of Toxicology
Computational Drug Discovery Methods
article

Applicability of NAMs to support a read-across based hazard assessment workflow for systemic toxicity: a conazole case study

Amer Jamalpoor, Jenny Irwan, Tamara Meijer, Barira Islam, Marcel Leist, Laura Ines Furlong, Patrik Lundquist, Clémence Budin, Philip Marx‐Stoelting, Nadine Dreser, Lukas Wijaya, Bob Water, Sylvia E. Escher, Per Artursson, Guillaume Ollitrault, Baiba Gukalova, Mirjam Luijten, Tessa M. S. Hagens, Kathrin Bothe, Shu Liu, Marlene Wedler, Sibel Bahtiri, Jaione Telleria, Olivier Taboureau, Andrew White, Iain Gardner, Tjalf de Boer, Bas ter Braak, Sam Davidse, Edgars Liepins, Hennicke Kamp, Annika Järvinen
article en

Abstract

Abstract This work explores the applicability of new approach methodologies (NAMs) using a read-across approach to predict systemic toxicity with liver as the critical target organ, and derive a point of departurefor the target compound (TC) difenoconazole. Eight conazoles were used as source compounds (SCs), alongside metabolites hydroxyitraconazole and 1,2,4-triazole. The case study was structured according to the Alternative Safety Profiling Algorithm (ASPA) workflow developed within the RISK-HUNT3R project. Hierarchical clustering using chemical fingerprints identified similarity of different SCs to the TC, supporting their inclusion in the read-across analysis. A broad screening panel of NAMs, including nuclear receptor reporter assays, ToxProfiler, Cell Painting PLUS, transcriptomics in primary human hepatocytes and H295R steroidogenesis assays, was used to characterize biological activity of the TC and SCs and to substantiate the structure-based read-across. In a first prediction round, the nearest neighbour quantitative read-across approach (based on allometrically-scaled human lowest-observed-adverse-effect levels (LOAELs) of the SC) was used to predict 6.57 mg/kg/day as the LOAEL of the TC. This closely aligned with the in vivo-based value of 4.88 mg/kg/day. In a second approach, data from NAMs were used to predict human equivalent dose (HED), and the respective LOAELs of SC and TC, based on physiologically based kinetic modelling with quantitative in vitro to in vivo extrapolation. The HED derived from NAMs was approximately ten-fold lower than the LOAELs from traditional approaches. This case study illustrates suitable (ASPA-guided) approaches as well as the toxicological applicability of a NAM-based read-across assessment to obtain safe/conservative estimates of toxicity. Graphical Abstract A stepwise procedure was used in this work for assessment of systemic toxicity of the target compound, difenoconazole, using a read-across approach

Archives of Toxicology
Leiden University (NL), Uppsala University (SE), Centre National de la Recherche Scientifique (FR), Unilever (United Kingdom) (GB), University of Bedfordshire (GB), Inserm (FR), University of Konstanz (DE), Université Paris Cité (FR), Federal Institute for Risk Assessment (DE), BioDetection Systems (Netherlands) (NL), Innovation (Latvia) (LV), National Institute for Public Health and the Environment (NL), Fraunhofer Institute for Toxicology and Experimental Medicine (DE), Unit of Functional and Adaptive Biology (FR), Physiologie De L'Axe Gonadotrope (FR), Bayer (Germany) (DE), Freie Universität Berlin (DE)
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Computational Drug Discovery Methods
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