# Hazard associated with the synthesis of epoxy-vitrimer: In vitro risk assessment and scoring strategy

Marion Berenguer, David Béal, Justine Bétemps, Jade Boudard, Jean-Luc Ravanat, Manon C Bouwmeester, Yvonne C.M. Staal, Virginia Cazzagon, Ana Candalija, Ruben Martinez, et al.

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► To cite this version:

Marion Berenguer, David Béal, Justine Bétemps, Jade Boudard, Jean-Luc Ravanat, et al. Hazard associated with the synthesis of epoxy-vitrimer: In vitro risk assessment and scoring strategy. Toxicology in Vitro, 2026, 113, pp.106214. 10.1016/j.tiv.2026.106214. hal-05519693

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# Hazard associated with the synthesis of epoxy-vitrimer: *In vitro* risk assessment and scoring strategy

Marion Berenguer<sup>a</sup>, David Béal<sup>a</sup>, Justine Bétemps<sup>a</sup>, Jade Boudard<sup>a</sup>, Jean-Luc Ravanat<sup>a</sup>, Manon C. Bouwmeester<sup>b</sup>, Yvonne C.M. Staal<sup>b</sup>, Virginia Cazzagon<sup>c</sup>, Ana Candalija<sup>c</sup>, Ruben Martinez<sup>c</sup>, Nina Hambruch<sup>d</sup>, Arrate Huegun<sup>e</sup>, Valeria Berner<sup>f</sup>, Carl-Christoph Höhne<sup>f</sup>, Delphine Tissier<sup>g</sup>, Sebastien Artous<sup>h</sup>, Jean Breton<sup>a</sup>, Thierry Douki<sup>a,*</sup>

## ARTICLE INFO

Editor: Maxime Culot

**Keywords:**

Chemical toxicity

Hazard assessment

Plastics

Scoring

Safe, sustainable, and recyclable by design

## ABSTRACT

In the framework of a Safe, Sustainable, and Recyclable by Design approach for the synthesis of novel plastics, we investigated the toxicological impact of epoxy vitrimers' synthesis. Emphasis was placed on the substitution of conventional hardeners and flame retardants with alternative ingredients. Data were also obtained on the leachates extracted from the final materials. Several toxicological endpoints (cytotoxicity, oxidative stress, epigenetics, genotoxicity, endocrine disruption) were assessed on human cell lines, and aquatic toxicity was evaluated in *Daphnia* and zebrafish embryo. The bulk of the results showed that use of alternative products did not increase, and in some cases decreased, the toxicological impact of the synthesis of the vitrimers. To facilitate the use of the numerous collected data, they were combined in scores. We first designed a toxicity score that compared each substance with the positive controls of the assays. This score was found to be valuable to report the results in a convenient and easily understandable way. We also developed a performance score that compared the properties of each alternative substance to the conventional reference. This score aimed to be used in a digital decision-making tool for the development of new industrial processes.

## 1. Introduction

Assessment of the toxicological impact of chemicals used in industrial processes and of the final products along their life cycle is a key issue in the acceptability of technologies and materials. Such investigations require the collection of information on a wide range of biological endpoints and for a large array of substances. This is in particular the case for investigations following a Safe, Sustainable and Recyclable by Design (SSRbD) approach (Caldeira et al., 2022), like the present project that aimed to develop novel polymeric materials (Soeteman-Hernández et al., 2025). The SSRbD approach was applied to three case studies including one dealing with resistant epoxy-vitrimer

materials for the railway sector. Vitrimers have emerged in the recent years as innovative materials exhibiting interesting mechanical properties, lightness and recyclability (Alabiso and Schlögl, 2020). Epoxy-vitrimers are among the most promising (Yang et al., 2021). These polymer composites are prepared by reaction of diepoxy monomers, the epoxy resin, with diamino products, referred to as the hardeners (Scheme 1). Different substances are added during the process to provide specific properties to the final products. First, flame retardants are combined with the epoxy resin to obtain A-Parts. Those are mixed with the hardeners and carbon fibers to obtain, after polymerization, the final solid composite.

In the present project, the initial epoxy resin was the same in all

<footnote><sup>a</sup> Univ. Grenoble-Alpes, CEA, CNRS, Grenoble INP, SyMMES UMR 5819, France</footnote>

<footnote><sup>b</sup> RIVM, the Netherlands</footnote>

<footnote><sup>c</sup> Leitat technological center, Terrassa, Spain</footnote>

<footnote><sup>d</sup> BASF, Germany</footnote>

<footnote><sup>e</sup> CIDETEC, Basque Research and Technology Alliance, Donostia-San Sebastian, Spain</footnote>

<footnote><sup>f</sup> Fraunhofer Institute for Chemical Technology ICT, Germany</footnote>

<footnote><sup>g</sup> IPC, Industrial Plastic composites Technical, France</footnote>

<footnote><sup>h</sup> DES/LITEN, CEA-Grenoble, France</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>E-mail address: thierry.douki@cea.fr (T. Douki).</footnote>
<figure><img src="image_5.png" /><figcaption>**Scheme 1.** The major steps in the preparation of epoxy-vitrimer materials. Epoxy resin is a diepoxide that is mixed with a flame retardant to provide A-Parts. In a subsequent step, polymerization is triggered by the addition of a diamino hardener that reacts with the resin, in the presence of carbon fibers. Characterization of the substances extractable from the final product is performed on leachates which are obtained by incubation in specific solvents.</figcaption></figure>

materials, and the research efforts were directed toward the selection of the flame retardants and the hardeners. Several flame retardants were considered as a replacement for the toxic halogenated substances currently used (Kefeni et al., 2011; Waaijers et al., 2013) and in particular tris(2-chloropropyl) phosphate (TCPP) (Antonopoulou et al., 2022). Regarding hardeners, we were interested in substituting a conventional substance, 4,4'-diaminodiphenylmethane (MDA), with aromatic disulfide alternative hardeners, 4-aminophenyl disulfide (4-AFD) and 2-aminophenyl disulfide (2-AFD), which have been reported to provide improved properties to the composites (Azcune et al., 2021; Berner et al., 2025; Ji et al., 2020; Luo et al., 2022). Combination of these different ingredients led to the preparation of a series of composites. To determine their ability to release toxic substances (Delaeter et al., 2022; Kabir et al., 2023), we evaluated the hazard associated with leachates obtained upon incubation in media simulating physiological and environmental conditions.

Hazard information was collected for the tested substances on relevant biological models. The toxicological field is moving away from hazard assessment using animal testing, and alternative methods, such as *in vitro* assays, are preferred. 3D models, such as organoids or spheroids, and primary cell cultures are the most representative of *in vivo* environments. Unfortunately, they are not available for all organs and cannot be prepared in the large amounts required for testing many substances at different concentrations with several toxicological assays and in an appropriate number of replicates. Use of cell lines appears thus as an interesting alternative since it makes possible a quick screening providing relevant information during optimization of industrial processes. In particular, the obtained results are suitable for comparing and ranking products based on hazard information. In the present work, cytotoxicity, oxidative stress, genotoxicity and epigenetics (DNA methylation) were assessed in two human cell lines: HaCaT keratinocytes and Caco-2 intestinal cells. Endocrine disruption potential was investigated in an engineered human bone cell line using the CALUX® approach, while assessment of aquatic toxicity focused on *Daphnia* immobilization, an endpoint notion similar to survival, and zebrafish embryo toxicity. We could thus obtain information on the toxicity of the ingredients that are relevant for occupational exposure, and data on leachates that are of interest for exposure during the lifetime of the final products.

In a subsequent step, we developed a scoring strategy aimed to synthesize the large amount of information gathered for each substance. For this purpose, we combined the obtained experimental results within four toxicity pillars. The first, referred to as human health, was related to common cellular responses (cytotoxicity, oxidative stress, epigenetics). Two other pillars were defined to separately characterize genotoxicity, which is linked to cancer induction, and endocrine disruption, which affects development and fertility among others. The last pillar included the data on aquatic toxicity. Two scores were developed. The first was a toxicity score that aimed to provide a brief overview of the toxicity of a

substance. The second score involved a comparison of the effects of a reference substance with those of alternative substances developed for the project. This score was designed to be included into a digital tool aimed to facilitate decision making in the framework of SSRbD approach.

## 2. Materials and methods

### 2.1. Chemicals and solvent

Dimethylsulfoxyde (DMSO), Triton-X100, Sodium Dodecyl Sulfate (SDS), etoposide, methylmethane sulfonate (MMS), ethanol, 2 amino-phenyl disulfide (2-AFD), 4 aminophenyl disulfide (4-AFD), 4,4'-Diaminodiphenylmethane (MDA), bisphenol A diglycidyl ether (BADGE), acetic acid, isopropanol, formic acid, ammonium formate and acetonitrile (ACN) were purchased from Sigma-Aldrich.

### 2.2. Case study substances

Samples for the human health hazard and aquatic toxicity assessment of epoxy-vitrimer materials were provided by Fraunhofer Institute for Chemical Technology ICT, CIDETEC and Centre Technique Industriel de la Plasturgie et des Composites / IPC Industrial Plastic and Composites technical center. These samples were dispatched into a series of campaigns focusing on A-Parts, hardeners and leachates, respectively. Substances and their abbreviations are listed in Table 1.

### 2.3. Cell culture

HaCaT cells (CLS, Eppelheim, Germany), an immortalized human keratinocytic cell line, were cultured in high glucose Dulbecco's modified Eagle's medium with Glutamine (DMEM + GlutaMAX™; Gibco, Illkirch, France) supplemented with 10% fetal bovine serum (FBS, Gibco), 100 UI/mL penicillin and 0.1 mg/mL streptomycin (Sigma). Caco-2 cells (ATCC HTB-37), an immortalized cell line of human colorectal adenocarcinoma, were cultured in the same medium, with additional complementation by 1% non-essential amino acids (NEAA, Sigma). Cells were maintained under an atmosphere of 5% CO₂ at 37 °C.

For CALUX® assays, Estrogen Receptor alpha responsive (ERα) and Androgen Receptor responsive (AR) cells lines were purchased from BioDetection Systems (BDS, Netherlands). Both cell lines, derived from USO2 cells, were cultured in Dulbecco's modified Eagle's / F12 medium (1:1) with phenol red and GlutaMAX™ Supplement (Gibco, Illkirch, France) supplemented with 7.5% fetal bovine serum (FBS, Gibco), 1%

<caption>**Table 1**</caption>

Substances tested during this work. Substances underlined in blue are the reference of each campaign. This convention will be applied in all tables. Hardeners were pure commercial products while A-Parts and leachates were mixtures produced by the partners of the project.

<table><thead><tr><th>Campaign</th><th>Substance name</th><th>Abbreviation</th></tr></thead><tbody><tr><td rowspan="7">A-Parts</td><td>Epoxy resin + TCPP</td><td>AP-Cl</td></tr><tr><td>Epoxy resin w/o flame retardant</td><td>AP1</td></tr><tr><td>Epoxy resin + DOPO modified epoxy resin</td><td>AP2</td></tr><tr><td>Epoxy resin + Phosphorous modified epoxy</td><td>AP3</td></tr><tr><td>Epoxy resin + Aluminum diethyl phosphinate</td><td>AP4</td></tr><tr><td>4,4'-Diaminodiphenylmethane</td><td>MDA</td></tr><tr><td>4-Aminophenyl disulfide</td><td>4-AFD</td></tr><tr><td rowspan="3">Hardeners</td><td>2-Aminophenyl disulfide</td><td>2-AFD</td></tr><tr><td>Leachate from composite with TCPP</td><td>Leach-Cl</td></tr><tr><td>Leachate from composite with AP1 (w/o flame retardant)</td><td>Leach1</td></tr><tr><td rowspan="4">Leachates*</td><td>Leachate from composite with AP2</td><td>Leach2</td></tr><tr><td>Leachate from composite with AP3</td><td>Leach3</td></tr><tr><td>Leachate from composite with AP4</td><td>Leach4</td></tr><tr><td></td><td></td></tr></tbody></table>

<footnote>* Leachates were prepared by 10-days incubation of the composites in 95% ethanol. They were then concentrated 32 times by evaporation.</footnote>
non-essential amino acids (NEAA, Sigma), 10 UI/mL penicillin and 10 µg/mL streptomycin (Sigma), and 0.2 mg/mL geneticin (G-418) as selective agent. Cells were maintained under an atmosphere of 5% CO₂ at 37 °C.

## 2.4. Cytotoxicity

On the day prior to the treatment, HaCaT and Caco-2 cells were seeded into 96-well plates (3.5 × 10⁴ and 3.0 × 10⁴ cells/well, respectively) in culture medium. On the next day, suspensions containing increasing concentration of the tested substance was added (100 µL/well) and incubated for 48 h. For hardeners, the reference product was tested up to 5 mM whereas the alternative substances were assessed up to 300 µM. All A-Parts were tested up to 200 µg/mL. For leachates, the lowest dilution in medium tested was set as being the lowest non-cytotoxic dilution of pure solvent (ethanol, namely 0.2% on HaCaT and 1% on Caco-2 cells. As positive control, Triton-X100 was added at 0.1% to the cells. At the end of the treatment, assay was performed with WST-1 reagent (Cell Proliferation Reagent WST-1, Roche), according to the manufacturer instructions. The absorbance of each sample was measured (value at 450 nm minus value at 650 nm) and data were normalized by setting the solvent control level at 100% viability. For each substance, the WST-1 assay allowed to define conditions for assays either at equimolar concentration (the highest concentration of the most toxic substance of a campaign leading to 100% viability) or at equitoxic concentration (the concentration of each substance of a campaign leading to 80% viability). For hardeners, a few additional experiments were performed with the mitochondrial MTT viability assay performed as previously described (Aubry et al., 2025), and cell counting using trypan blue labeling carried out like for the 53BP1 assays described below.

## 2.5. Oxidative stress

Production of intracellular ROS content was measured using CM-H₂DCFDA (5(and-6)-chloromethyl-2'7'-dichlorodihydrofluorescein diacetate, acetyl ester, Invitrogen, France) assay. On the day prior to the treatment, HaCaT cells and Caco-2 cells were seeded into black 96-well plates (respectively 3.5 × 10⁴ and 3.0 × 10⁴ cells/well) in culture medium. On the next day, assay was performed as described previously (Aubry et al., 2025). For hardeners assessment, the tested equimolar concentrations were 50 µM in HaCaT and 60 µM in Caco-2 cells, respectively. The equitoxic concentrations were 500 µM, 80 µM and 200 µM in HaCaT for MDA, 4-AFD and 2-AFD, respectively. The corresponding values were 1500, 115 and 150 µM in Caco-2. A-Parts were tested only in an equiconcentration of 33 µg/mL in both cell lines. For the leachates, the lowest dilution was set at 0.2% and 1% for respectively HaCaT and Caco-2 cells. As positive control, a 250 µM solution of tert-butyl hydroperoxide (tBuOOH, Sigma) was added to wells. The fluorescence intensities (excitation: 488 nm, emission: 535 nm) was measured in each after 4 h incubation. For each condition, values were subtracted from those obtained in the absence of the probe. Results were then normalized by setting the solvent control level at 0% and the positive control level at 100%.

## 2.6. Genotoxicity

### 2.6.1. 53BP1 assay

For hardeners, two concentrations have been chosen for the analysis: one equimolar concentration (30 µM in HaCaT and Caco-2 cells) and one equitoxic concentration (leading to 80% viability, for each substance in each cell line). A-Parts have been tested at 20 µg/mL in both cell lines. For the leachates, the lowest dilution was set at 0.2% and 1% for respectively HaCaT and Caco-2 cells. As positive control for the assay, etoposide at 100 µM was used to induce DNA breaks. The number of p53-binding protein 1 (53BP1) foci per cell nucleus was evaluated by

immunostaining of cells as described previously (Fontaine et al., 2023). Briefly, cells were fixed for 20 min in 4% paraformaldehyde, permeabilized for 30 min in 0.2% triton X-100, and labelled using anti-53BP1 antibody (Abnova, dilution 1/200, Clinisciences, Nanterre, France) and anti-rabbit secondary antibody coupled to Atto488 (dilution 1/2000, Merck, St. Louis, MO, USA). Cell nuclei were then stained for 20 min with DAPI (Sigma-Aldrich, 1 µg/mL). Analyses were performed using a CellInsight CX5 High Content Screening automated imaging and image analysis system (Thermo Fisher Scientific). Five entire wells were analyzed per condition. Results are expressed as average numbers of 53BP1 foci per cell nucleus.

### 2.6.2. Comet assay

The comet assay was performed in its alkaline version. Cell culture, cell treatments and harvest, electrophoresis and measurement of tail DNA (expressed in %) were performed as described previously (Aubry et al., 2025). Treatment conditions were the same as described above for the 53BP1 assay. Methyl methanesulfonate (MMS), at 20 and 30 µg/mL, was used as positive control for the assay to induce DNA strand breaks.

## 2.7. DNA methylation

Caco-2 cells were grown to 60-70% confluence in 6-well plates with 3 mL of medium per well. Treatment solutions were added to the cells and incubated for 48 h. Treatment conditions are the same as for the 53BP1 assay. Cells were then collected and rinsed twice with Dulbecco's Phosphate Buffered Saline (DPBS, Gibco, Illkirch, France). DNA was extracted and hydrolyzed as previously described (Ravanat et al., 2002). The level of genome-wide DNA methylation was determined using an HPLC coupled to tandem mass spectrometry (HPLC-MS/MS) assay adapted from (Lafaye et al., 2014). After hydrolysis, DNA samples were freeze-dried and resuspended in 50 µL of a solution containing 25 µM isotopically labelled internal standard ([¹³C,¹⁵N₂]-5-methyl-2'-deoxycytidine (5-mdCyd) and [¹³C₉,¹⁵N₂]-2'-deoxycytidine (dCyd)). The samples were injected into a HPLC system (ExionLC, SCIEX) equipped with a reverse phase HPLC column (BEH 1.7 microm VanGuard FIT. 2.1x100mm column, Waters, Drinagh, Ireland) and elution was performed at a flow rate of 0.3 mL min⁻¹ in the gradient mode. The mobile phases were an aqueous solution of 2 mM ammonium formate containing 0.05% formic acid (A) and ACN (B). The initial composition of the gradient was pure A and kept for 2 min. The proportion of B was then increased to 20% at 5 min. It was then increase to 80% in 2 min, and further to 100% A in 3 min. dCyd and 5-mdCyd were detected and quantified by mass spectrometry with a 6500 + QTrap mass spectrometer (SCIEX) in the positive ionization mode using the multiple reaction monitoring detection mode. Monitored transitions were m/z = 228→112 and m/z = 242→126 for dCyd and 5-mdCyd, respectively. The corresponding internal standards were detected with the m/z 240→119 and m/z 245→129 transitions for [¹³C₉,¹⁵N₂]-dCyd and [¹³C,¹⁵N₂]-5-mdCyd, respectively. Concentrations were inferred from the ratio between the area of the chromatographic peaks of each analyte and its internal standard. The reported results are expressed as the percentage of 5-mdCyd relative to dCyd.

## 2.8. Endocrine disruption potential

CALUX® cells seeding, treatment, lysis and data analysis were performed according to the OECD guidelines TG455 (OECD, 2021) and TG458 (OECD, 2023). For cell culture, Dextran Charcoal treated fetal bovine serum was purchased at Sigma. Luciferase luminescence activity was measured in a microplate reader. First 100 µL of Illuminate Mix (BDS, Netherlands) was added to the wells, and luminescence was measured for 4000 ms. Then, 100 µL NaOH 0.2 M was injected to stop the reaction before reading the next well. For both agonist and antagonist CALUX® assays, the endocrine disruption potential assessment started with a pre-test. This pre-test aimed to assess the maximal non-
cytotoxic dose of the tested substances, and to determine whether the tested substances exhibited an agonist or antagonist effect on the ERα or AR receptors. If a response was observed in the pre-test, a complete evaluation test was performed within a narrower concentration range. In case of antagonist assessment, this evaluation was performed in parallel with a specificity test. All experiments included positive and negative controls. A reference product was first used in the agonist assays for comparing the results of the tested products. In the antagonist version of the assays, the investigated substance was tested for its capacity at displacing the product used as reference in the agonist method. The reference was mixed at its IC50 concentration with the tested substance in the pre-test and the complete evaluation test. The same reference was used in much larger concentration in the specificity test, namely 50 and 100 times its IC50 for ERα and AR, respectively. For agonist assays, reference products were 5α-dihydrotestosterone (DHT) and 17β-estradiol for respectively AR and ERα cells. Positive and negative controls were 17 α-methyltestosterone and corticosterone. For antagonist assays, control reference products were flutamine and tamoxifene for AR and ERα cells, respectively. Positive and negative controls were linuron and levonorgestrel for the AR assay, and 4-hydroxytyamoxifene and resveratrol for Erα. Starting condition for the dilution range during pre-test was 100 µM for hardeners, 50 µg/mL for A-Parts and 1% dilution for leachates. For the complete evaluation, the highest concentration of the poorly cytotoxic hardener MDA was increased to 400 µM.

## 2.9. *Daphnia immobilization*

*Daphnia magna* adults (clone F) were cultured in ASTM hard water medium under a 16:8 h light-dark photoperiod and at 20 ± 1 °C. Once every two days, medium was renewed to maintain optimal conditions and *Daphnia* individuals were fed with the microalgae *Raphidocelis subcapitata* as a nutrient. Aquatic toxicity, using *Daphnia magna* neonates, was assessed following the OECD Test Guideline 202 (OECD, 2004) with slight modifications. Briefly, newborn *Daphnia magna* individuals (<24 h old) were collected the day of the experiment and placed into 24 multi-well plates filled with different concentrations of the test substances and the control media. Test solutions were made freshly, and the pH of each stock solution was adjusted with diluted NaOH or HCl, if necessary, to assure that it was on acceptable range (6.0–9.0). In each well, a unique neonate and 2 mL of the respective treatment were placed (n ≥ 20). Exposures were carried out in static conditions, without aeration, without feeding, and in dark conditions. At 24 and 48 h, immobilization (as a surrogation of mortality) of each *Daphnia* individual was recorded, and the percentage of immobilized organisms was calculated to determine the EC₅₀ values according to a sigmoidal regression model.

## 2.10. Zebrafish embryo toxicity (ZFET)

Zebrafish embryos (*Danio rerio*) were exposed to the substances at subtoxic concentrations following an exposure protocol adapted from the OECD TG236 (OECD, 2025). For breeding purposes, females were separated in a 3.5 L tank and fed with frozen artemia three times a day for a period of 4 days. The evening prior to mating, four females and four males were joined in a 1.7 L sloped breeding tank. Spawning was triggered by the onset of light, and eggs were collected within 30 min after spawning and transferred to Petri dishes. Successfully fertilized eggs were kept for further use. Eggs at cleavage stage were exposed in 24-well plates containing one egg in 2 mL of test medium (E3) with 0.1% DMSO (Merck, Darmstadt, Germany) (Staal et al., 2018). Development and teratology of exposed embryos were assessed at both 3 and 5 days post-fertilization under the stereomicroscope in a zebrafish embryo toxicity test (ZFET), as previously described (Hermsen et al., 2011). For the purpose of concentration-response analysis, data in the ZFET (morphology and teratology scores) were analyzed using the PROAST

software tool (v70.0; RIVM, Bilthoven, the Netherlands, https://www.rivm.nl/en/proast/), as a package in R statistical software v3.6.0–4.0.0 (RIVM, Bilthoven, the Netherlands) (Slob, 2002). The PROAST tool analyses the input data for the optimal fit using an exponential function from a nested family of 1–4 parameter models and their variants. A benchmark concentration (BMC or critical effect dose (CED)) can be derived from the dose-response fit at a defined critical effect size (CES). To compare the potency of the individual substances, a CED20 was used (CED at CES = 20%) which was used here as a measure of aquatic toxicity.

## 2.11. Statistical analysis

Unless otherwise stated, experiments were designed with at least 3 technical replicates for each condition and were carried out in a minimum of 3 biological replicates. For endocrine disruption on ERα and AR CALUX® cells, only one assay with triplicates was performed, based on the pre-test assay. The ZFET test were performed in biological triplicates of technical duplicates.

In the case of assay over a range of concentrations (for cytotoxicity, endocrine disruption CALUX® assays, *Daphnia* immobilization, Zebrafish Embryo Toxicity test), no assessment of the statistical significance of the differences between the products was done. EC50 and IC50 values were calculated using the GraphPad Prism software (version 10.5.0), by fitting the curves with 4PL models, unless otherwise stated. For Zebrafish Embryo Toxicity test the EC20 was determined using the PROAST software tool.

In the case of the evaluation of a biological response at specific concentrations (for oxidative stress, epigenetics and genotoxicity assays), data were analyzed using Kruskal-Wallis test with Dunn's multiple comparison test. Values of *p* ≤ 0.05 were considered statistically significant and marked with * for comparison between the tested substances and the solvent control and with # for comparison between the alternatives and the reference product. For the epigenetic modifications with HPLC-MS/MS assay, comparison between the positive control and its solvent control was performed using the Kolmogorov-Smirnov test.

# 3. Results

## 3.1. Collection of toxicological data

Assessing the hazard associated with epoxy vitrimer synthesis led us to investigate a wide variety of substances. They were either pure ingredients (e.g. hardeners), mixtures of ingredient (e.g. A-Parts) or solutions of poorly-defined composition (e.g. leachates). It should be noted that flame retardants were tested only in A-Parts because some of them were not pure molecules but were pre-mixed with resin. All substances were tested in several biological models. A large faction of the work was performed in HaCaT and Caco-2 human cell lines. HaCaT cells are immortalized keratinocytes chosen as mimics of skin and representative of a dermal exposure. Caco-2 cells originate from a colorectal adenocarcinoma and were selected as relevant to intestine and exposure by ingestion. Endocrine disruption was investigated in engineered USO2 human cells while aquatic toxicity was studied in *Daphnia* and zebrafish embryo.

### 3.1.1. Cytotoxicity

Assessing the cytotoxicity of evaluated substances is a mandatory step in toxicological studies. Firstly, the ability of substances to induce cell death is a key information in the comparison of the adverse biological effects. Secondly, evaluation of cytotoxicity is necessary to define experimental conditions associated with an appropriate survival of the tested cells in order to avoid artifactual responses in the different endpoints. The chosen assay was WST-1, a colorimetric test based on the metabolism of a probe in the mitochondria of viable cells (Berridge
et al., 2005). In the present study, the substances were tested on a wide range of concentrations in order to determine the dose leading to 50% viability (IC50). For this purpose, the data were fitted with a four parameters logistic (4PL) sigmoidal regression (Fig. 1a). In a few cases, this fitting was not possible because the range of concentrations did not allow us to completely describe the sigmoid. Consequently, a second order polynomial regression was applied and the IC50 calculated. (Fig. 1b).

An unexpected observation was made for the viability tests with the alternative hardeners 2-AFD and 4-AFD. A strong increase in viability, as determined with the colorimetric WST-1 test was observed in the low concentration range (Fig. 2a). This was not the case for MDA that was approximately 10 times less toxic. Surprisingly, other methods for evaluating cytotoxicity (MTT, Alamar blue, trypan blue and DAPI) did not show the same effect (Fig. 2b). We concluded that this response was an artifact of the WST-1 assay maybe associated with the disulfide structure of the compounds that could interfere with the redox chemistry of the test. IC50 values were calculated using a second order polynomial fit in the decreasing part of the curve. It should be stressed that the obtained values were close to those inferred from other cytotoxicity assays.

The IC50 values obtained with the WST-1 assay were compiled in Table 2. For each campaign, we also determined the concentrations leading to 80% viability for the different substances (equitoxicity experiments). In the case of hardeners, we determined the highest concentration that did not decrease the cellular viability even for the most toxic substance (equiconcentration experiments). Differences were observed in both cell lines for the hardeners. MDA was found to be a least one order of magnitude less toxic than the disulfide hardeners. Regarding these two substances, 4-AFD induced a slightly larger loss of viability than 2-AFD. In contrast to hardeners, A-Parts were found to be all similarly cytotoxic. The IC50 (on the average 35 and 42 µg/mL in HaCaT and Caco-2, respectively) represented approximately 2.5% of that of the positive control. No difference was also found in the cytotoxicity of leachates that did not induce loss of viability in the tested range of dilution, except at the highest concentration for the reference substance Leach-Cl in Caco-2.

### 3.1.2. Oxidative stress

Induction of oxidative stress is a common feature of toxic chemical and physical agents (Kappus, 1987). It results from either decreased antioxidant defenses, induction of prooxidant processes, or both. As a result, oxidizing species are produced which damage biomolecules and trigger specific cellular responses. We chose the measure the extent of oxidative stress through the quantification of reactive oxygen species (ROS) by an assay based on the use of the CM-H₂DCFDA probe (Koopman et al., 2006), a reduced fluorescein derivative that becomes fluorescent in the present of ROS.

The response of the positive control was always strongly significant, showing the ability of the assay at detecting the increase in the level of

ROS in cells. As a general trend, the obtained fluorescence values were larger in HaCaT than in Caco-2 cells, likely reflecting differences in uptake of the probe. Hardeners were tested in two campaigns, one including MDA and 4-AFD and the other MDA and 2-AFD. Induction of oxidative stress was mostly observed for the reference substance MDA (Fig. 3a and Supplementary material Table S1). The alternative ingredients 4-AFD and 2-AFD induced a lower level of ROS than MDA. Regarding other substances, no statistically significant difference in the level of ROS was observed between solvent controls and leachates (Supplementary material Table S1). A small but significant increase was observed for most A-Parts in both cell types (Fig. 3b and Supplementary material Table S1).

### 3.1.3. DNA methylation

Epigenetic modifications are processes leading to heritable modulation of gene expression without modification of their DNA sequence and in a reversible way. Epigenetic signals can involve histone modification, synthesis of non-coding RNA like microRNA, or reversible modifications of DNA like cytosine methylation. Modulation of epigenetics has been proposed as a pathway involved in the effects of chemical exposure (Hou et al., 2012; Marczylo et al., 2016). We investigated the modulation of cytosine methylation as it has been shown to be involved in deleterious processes such as cancer. Increase proportion of 5-mCyt decreases the accessibility to promotors and has been associated with reduced expression of tumor suppressor genes. In contrast, decrease in 5-mCyt level is associated with increased expression of oncogenes.

The endpoint used in the present work was the average level of cytosine methylation in the overall genome. It was quantified by HPLC coupled to tandem mass spectrometry (HPLC-MS/MS) following DNA extraction and hydrolysis into nucleosides. The positive control was 5-azacytidine that induced a 50% decrease in the level of 5-mCyt in nuclear DNA (Fig. 4). It should be noted that the assay was performed only in Caco-2 cells because the positive control failed to modulate the level of 5-mCyt in HaCaT cells. In addition, the assay was not applied to leachates that were available in too small amounts. In spite of the accuracy and sensitivity of the assay, none of the tested substances was found to modulate DNA methylation that was found to remain at approximately 4% (5-mCyt / Cyt) like in non-treated cells (Supplementary material Table S2).

### 3.1.4. Genotoxicity

Genotoxicity corresponds to processes leading to the increase in the level of DNA damage in nuclear DNA and their conversion into mutations (Phillips and Arlt, 2009). This represents a major step in the onset of tumorigenesis since mutations in genes regulating control of cellular replications are the basis of the initiation phase of cancers. We applied two assays to the investigation of DNA damage. The first was the well-known Comet assay that provides information on the formation of single- and double-strand breaks in DNA, as well as on base damage

<figure><img src="image_6.png" /><figcaption>**Fig. 1.** Cytotoxicity of A-Parts and leachates in Caco-2. Cells were grown to 80% confluency and exposed for 48 h to increasing concentration of each hardener. Viability was assessed by the WST-1 assay. IC50 were determined by a 4PL fit for A-Parts and a second order polynomial regression for leachates. Reported data are means of at least three independent experiments with three technical replicates each.</figcaption></figure>
<figure><img src="image_7.png" /><figcaption>**Fig. 2.** Cytotoxicity of alternative hardeners in HaCaT cells. Cells were exposed for 48 h to the tested substances at increasing concentration. a) evaluation of 2-AFD and 4-AFD by the WST-1 assay. The dotted line is the quadratic fit. b) evaluation of 4-AFD with the MTT and trypan blue assays. The solid lines are the 4PL sigmoidal fits. Reported data are medians of at least three independent experiments with three technical replicates each for WST-1. Only one experiment in technical triplicate was performed for MTT and Trypan blue. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

**Table 2**

Cytotoxicity data for HaCaT and Caco-2 cells. Cells were grown to 80% confluency and exposed for 48 h to increasing concentration of each substance. Viability was assessed by the WST-1 assay performed at least in biological triplicates each based on technical triplicates. IC50 were determined by a 4PL fit except for 4-AFD, 2-AFD and Leach-Cl for which a second order polynomial regression was used. Reported data are IC50 determined by the results of at least three independent experiments with three technical replicates each. Values for equiconcentration (equiconc) and equitoxicity (equitox) conditions are also reported. For A-Parts and leachates, equiconcentration and equitoxicity correspond to the same conditions.

<table><thead><tr><th rowspan="2"></th><th rowspan="2"></th><th colspan="3">HaCaT cells</th><th colspan="3">Caco-2 cells</th></tr><tr><th>IC50*</th><th>Equitox*</th><th>Equiconc*</th><th>LD50*</th><th>Equitox*</th><th>Equiconc*</th></tr></thead><tbody><tr><td rowspan="5">A-Parts</td><td>AP-Cl</td><td>33.8</td><td>33</td><td></td><td>43.6</td><td>33</td><td></td></tr><tr><td>AP1</td><td>36.5</td><td>33</td><td></td><td>34.7</td><td>33</td><td></td></tr><tr><td>AP2</td><td>35.7</td><td>33</td><td></td><td>51.1</td><td>33</td><td></td></tr><tr><td>AP3</td><td>36.7</td><td>33</td><td></td><td>42.9</td><td>33</td><td></td></tr><tr><td>AP4</td><td>34.5</td><td>33</td><td></td><td>41.5</td><td>33</td><td></td></tr><tr><td rowspan="5">Hardeners</td><td>MDA</td><td>2844</td><td>500</td><td>50</td><td>3342</td><td>1500</td><td>60</td></tr><tr><td>4-AFD</td><td>83</td><td>80</td><td>50</td><td>139</td><td>115</td><td>60</td></tr><tr><td>2-AFD</td><td>161</td><td>200</td><td>50</td><td>170</td><td>150</td><td>60</td></tr><tr><td>Leach-Cl</td><td>&gt; 0.2</td><td>0.2</td><td></td><td>2.05</td><td>1</td><td></td></tr><tr><td>Leach1</td><td>&gt; 0.2</td><td>0.2</td><td></td><td>&gt; 2</td><td>1</td><td></td></tr><tr><td rowspan="4">Leachates</td><td>Leach2</td><td>&gt; 0.2</td><td>0.2</td><td></td><td>&gt; 2</td><td>1</td><td></td></tr><tr><td>Leach3</td><td>&gt; 0.2</td><td>0.2</td><td></td><td>&gt; 2</td><td>1</td><td></td></tr><tr><td>Leach4</td><td>&gt; 0.2</td><td>0.2</td><td></td><td>&gt; 2</td><td>1</td><td></td></tr></tbody></table>

<figure><img src="image_8.png" /><figcaption>**Fig. 3.** Induction of ROS by a) 4-AFD and MDA in Caco-2 cells in equiconcentration and equitoxicity experiments, and b) A-Parts in HaCaT at equiconcentration. Data were obtained with the CM-H₂DCFDA assay. Increase in fluorescence was measured 4 h after addition of the substance and the probe. All experiments were biological triplicates of technical triplicates. Data were normalized values of fluorescence measured with respect to the tBuOOH positive control. Results were expressed as the median, the first and third quartiles and the minimum and maximum values. Statistical analysis was based on a Kruskal-Wallis test followed by a Dunn's multiple comparison test (n = 9): comparison to the control (*p* < 0.05, **p* < 0.01, ***p* < 0.001) and comparison to the reference substance (#p < 0.05, ##p < 0.01, ###p < 0.001).</figcaption></figure>

converted into additional breaks under the alkaline conditions of the analysis (Cordelli et al., 2021). The second technique was the quantification of 53BP1 foci in the nucleus. This method is based on an immunofluorescence detection of the 53BP1 protein, which binds to double-strand breaks as part of the repair process. The 53BP1 test is similar to

the well-known γ-H2AX histone detection but is more specific toward DNA damage and slightly more sensitive (Fontaine et al., 2023).

None of the tested substances was found to induce a signal in the Comet assay apart from positive controls. The only significant modulations of the response were a few decreases below that of the solvent

<footnote>* Results are expressed in µg/mL for A-Parts, µM for hardeners and % of dilution for leachates.</footnote>
<figure><img src="image_9.png" /><figcaption>Fig. 4. Representative chromatograms of the analysis of 5-mdCyd in DNA. Samples were the solvent control (blue trace) and 5-AzaCytidine positive control (red trace). Cells were incubated for 48 h in the absence or the presence of the 10 µM 5-azacytidine. DNA was then extracted, enzymatically hydrolyzed into nucleosides and analyzed by HPLC-MS/MS. Reported traces correspond to mass spectrometry signal for 5-mdCyd (retention time 2.6 min) and dCyd (retention time 1.8 min). The similarity in the intensity of peak corresponding to dCyd shows that similar amounts of DNA were analyzed. Yet, the peak corresponding to 5-mCyd was twice lower in 5-AzaCyd-treated cells. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

control (Supplementary material Table S3). A similar low genotoxicity was observed in the 53BP1 assay for the leachates and the hardeners (Supplementary material Table S4), with the exception of a small but detectable increase for 4-AFD in HaCaT cells at the highest tested concentration. This effect remained to be confirmed since an opposite slight decrease in signal was observed under the same conditions in Caco-2 cells. In contrast, a strong genotoxicity was observed in the 53BP1 assay for all A-Parts in both cell types. The numbers of foci per cell were very similar from one A-Part to the other (Fig. 5 and Supplementary material Table S4). The difference in response between the Comet and 53BP1 assays shows that direct induction of strand breaks may not be the major underlying genotoxic event. This observation is most likely driven by the formation of bulky DNA adducts leading to blocking and collapse of replication forks in double strand-breaks (Branzei and Foiani, 2005; Patel and Weiss, 2018). As a matter of fact, A-Parts were

composed of the monomer of epoxy resin which are highly reactive diepoxides. All A-Parts except AP1 also contained a flame retardant. The fact that AP1 was as genotoxic as other A-Parts showed that FR were not involved in the genotoxic processes. Interestingly, the resin used is composed mostly of bisphenol A diglycidyl ether (BADGE), a substance known to be mutagenic and induce micronuclei (Xue et al., 2022). In addition, early works have shown that DNA nucleosides react with BADGE to form stable covalent adducts (Vanhoutte et al., 1996). Using HPLC-mass spectrometry analysis of DNA enzymatically hydrolyzed into nucleosides, we could detect the adduct between 2'-deoxyguanosine and BADGE in Caco-2 cells exposed to A-Parts (Supplementary material Fig. S1). Identification of the product was based on a comparison with isolated DNA exposed to high concentration of BADGE.

<figure><img src="image_10.png" /><figcaption>Fig. 5. Genotoxicity of A-Parts in HaCaT cells a) Comet assay b) 53BP1 foci quantification. Cells were exposed to the tested substances for 48 h. For the comet assay, cells were analyzed after lysis under alkaline condition on microscopy slides inside in a gel, followed by electrophoresis and fluorescence labelling of the DNA. Data are expressed as the percentage of fluorescence in the tail of the image of nuclei of 50 cells. For 53BP1 labeling, fixed cells were immuno-stained first by a 53BP1 rabbit antibody and then an anti-rabbit secondary fluorescent antibody. Nuclei were stained by DAPI and cells analyzed by fluorescence imaging. All results were expressed as the median, the first and third quartiles and the minimum and maximum values. Statistical analysis was based on a Kruskal-Wallis test followed by a Dunn's multiple comparison test (n = 9): comparison to the control (*p* < 0.05, **p* < 0.01, ***p* < 0.001). Comparison to the reference substance (AP-Cl) did not provide significant results.</figcaption></figure>
### 3.1.5. Endocrine disruption

Endocrine disruptors are chemicals that interfere with the physiological hormonal system. As a consequence, endocrine disruptors exhibit deleterious effects on fertility, development and puberty. Other effects are documented such as impacts on the nervous and immune systems, as well as a role in the onset of some cancers. One specificity of endocrine disruptors is that they may be active at very low concentration and that their dose-response is not linear and can be bell-shaped (Vandenberg et al., 2012). Endocrine disruption is a main concern for plastics (Darbre, 2020) since well characterized endocrine disruptors such as bisphenol A and phthalates have been extensively used to improve their mechanical properties. It is thus mandatory to ascertain that the substances associated with novel materials do not exhibit this type of toxic properties.

A mechanism frequently involved in endocrine disruption is the binding of chemicals to the hormone receptors, leading to the expression of genes and induction of specific cellular responses. We quantified the ability of the tested substances to induce this response through CALUX® (Chemically Activated LUCiferase eXpression) assays (OECD, 2021, 2023). This approach is based on the use of mammalian cell lines transfected with the firefly luciferase gene coupled to responsive elements specific for the investigated response. Increase in luminescence upon addition of luciferin thus reflects an interaction between the responsive element and the tested substance. In the present work, two cell lines derived from human osteosarcoma cell lines U2OS were used, one carrying the estrogen receptor alpha (ERα) and the other to the androgen receptor (AR). Both were used to detect either agonist or antagonist effects.

Most of the tested substances failed to induce a response in the AR and ERα tests, neither in the agonist nor the antagonist configuration (Supplementary material Table S5). This was in particular the case for A-Parts that showed positive response in none of the tests. For the hardeners, MDA was positive in the agonist ERα and the antagonist AR assays. The leachates of composites prepared with 4-AFD and AP-Cl (Leach-Cl) or AP3 (Leach3) were responsive in the agonist ERα test. Leach-Cl was also positive in the agonist AR assay (Fig. 6). It should be pointed that the positive responses of the tested substances in the CALUX® tests were always observed in the highest range of tested concentrations.

### 3.1.6. Aquatic toxicity

The assessment of aquatic toxicity relied on the *in vitro* evaluation of the viability of zebrafish embryo and *Daphnia*. The results were similar to those obtained in human cell lines. First, the two alternative hardeners, 2-AFD and 4-AFD, were found to be more toxic than the reference MDA (Fig. 7 for *Daphnia*). For A-Parts, no toxicity was observed in *Daphnia* and only a slight effect in zebrafish. Last, none of the dilution used for the leachates could induce toxicity in either model.

## 3.2. Scoring of toxicological properties

The developed toxicity scoring approach for *in vitro* human hazard relied on three pillars (human health, genotoxicity and endocrine disruption), to which aquatic toxicity was added. The principle of our toxicity scoring is a comparison of the data for each substance with the positive controls of the assays in each campaign (Scheme 2). It should be reminded that the results of the tests were either IC50 (or CED20 for ZFET) when a wide range of concentrations was investigated, or data obtained at specific concentrations (equitoxicity or equiconcentration experiments). In a first step of the toxicity scoring, experimental results were normalized with respect to the cellular response to the positive control. From a calculation point of view, these data had to be treated differently in these two cases. For assays providing IC50, Eq. (1) was used to reflect the fact that the lower the IC50, the more toxic the substances are. Consequently, the value for the positive control is the numerator. Conversely, the most toxic substances in tests performed at specific concentrations were those inducing the largest response in cells. In this case, Eq. (2) was applied, with the result of the positive control at the denominator. The results of the statistical analysis were also taken into account in these calculations. When the response of a tested substance was not statistically different from that of the solvent control, the normalized data was set to 0. The same was done for substance for which no IC50 could not be determined in the investigated concentration range.

$$ \text{normalized data} = 100 \times \frac{\text{IC50positive crtl}}{\text{IC50compound}} \quad (1) $$

$$ \text{normalized data} = 100 \times \frac{X_{\text{compound}} - X_{\text{solvent}}}{X_{\text{positive crtl}} - X_{\text{solvent}}} \quad \text{with X being the response of the assay.} \quad (2) $$

<figure><img src="image_11.png" /><figcaption>Fig. 6. CALUX® assays for Leach-Cl a) ERα agonist assay b) AR antagonist assay (dotted line: specificity test). Results are means ± standard deviations (n = 3). The dotted blue trace for the AR antagonist test refers to the specificity test in which the reference substance that is displaced by the tested compound (5α-dihydrotestosterone for AR) is used in 100 times higher concentration than the first test (solid blue trace). The dotted horizontal lines are threshold of significance of the assays. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>
<figure><img src="image_12.png" /><figcaption>**Fig. 7.** 24 (A) and 48 h (B) immobilization results in *Daphnia magna* (OECD 202) for the hardeners. Juveniles were exposed in multi-well plates to increasing concentration of the hardeners. At 24 and 48 h, immobilization of each Daphnia individual was recorded, and the percentage of immobilized organisms was calculated. The IC50 values were determined at 48 h according to a sigmoidal regression model. Reported values are expressed as means ± SEM (n ≥ 3). Please, note that x-axis is in logarithmic form.</figcaption></figure>

<figure><img src="image_13.png" /><figcaption>**Scheme 2.** Principle of the calculation of toxicity scores. In a first step, results for each substance and each assay were normalized with respect to the positive controls. For assays performed on both HaCaT and Caco-2, normalized values for the two cell lines were averaged. Final scores for each pillar were obtained by averaging the normalized data of all relevant assays Hazard categories were defined based on the value of the scores.</figcaption></figure>

The normalized data were then averaged into a score within each pillar. Data obtained for cytotoxicity, oxidative stress and epigenetics were averaged in the final human health score, while results for the 53 PB1 and Comet assays were averaged in a genotoxicity score. For the human health and genotoxicity pillars, normalized data from HaCaT and Caco-2 cell lines were averaged for each assay prior to the calculation of the score. Normalized data from the CALUX® agonist and antagonist tests were averaged in an endocrine disruption score. It should be stressed that the response of the positive controls of the agonist tests was much larger than that of the antagonist versions. To avoid a predominant weight of the antagonist data in the score, the agonist results were multiplied by 300, which is the ratio between the response of the positive controls in the antagonist and agonist tests. In addition, an aquatic toxicity score was obtained from the normalized data for *Daphnia* and zebrafish toxicity. Last, a categorization system was adopted, with different thresholds for the different pillars, in order to facilitate the visualization of the results (Supplementary material Table S6). The thresholds were not the same in the different pillars. Low thresholds for high toxicity were assigned to endpoints associated with the most severe health impacts like genotoxicity or endocrine disruption. An appropriate choice of thresholds was also important for the endocrine disruption that

can be induced a much larger range of concentrations than the other effects.

The toxicity scores were calculated for all the tested substances. The case of hardeners illustrates how different endpoints can affect the final score (Table 3 and Fig. 8). The two alternative ingredients 4-AFD and 2-AFD exhibited larger, although moderate, cytotoxicity compared to that of MDA. However, the latter substance was a potent inducer of oxidative stress. None of the hardeners had an impact on epigenetics. Consequently, the human health score of MDA was the largest after combining the results in the relevant assays. Regarding genotoxicity, only 4-AFD was found to exhibit a positive, but moderate, score. The endocrine disruption score was larger than 0 only for MDA in the AR antagonist and ERα agonist assays. The aquatic toxicity score was the only one providing larger values for 2-AFD and 4-AFD than MDA. This actually reflects the fact the cytotoxicity was larger for the alternative than the reference hardener in *Daphnia* and zebra fish, like in human cell lines. It should be noted that the data discussed above arose from the equitoxicity experiments. Those carried out at equiconcentration showed only very weak effects because the tested concentrations were quite low (data not shown).

The reference substance for A-Parts, AP-Cl, was the most toxic in the
<caption>**Table 3**</caption>

Toxicity scores for hardeners. The values reported for individual assays were normalized with respect to the positive controls. When assays were performed on both HaCaT and Caco-2 cells, values were averaged. The final score in each pillar (human health, genotoxicity, endocrine disruption, aquatic toxicity) was calculated by averaging the normalized data in each assay. Results are expressed as % of the positive controls of the assays. The colour codes correspond to the categories defined in Supplementary material Table S6.

<table><thead><tr><th></th><th>MDA</th><th>4-AFD</th><th>2-AFD</th></tr></thead><tbody><tr><td colspan="4"><strong>human health</strong></td></tr><tr><td>cytotoxicity</td><td>0.1</td><td>2.0</td><td>1.2</td></tr><tr><td>stress ox</td><td>68.7</td><td>7.8</td><td>0</td></tr><tr><td>5-meCyt</td><td>0</td><td>0</td><td>0</td></tr><tr><td><strong>score</strong></td><td><strong>22.9</strong></td><td><strong>3.3</strong></td><td><strong>0.4</strong></td></tr><tr><td colspan="4"><strong>Genotoxicity</strong></td></tr><tr><td>53BP1</td><td>0</td><td>9.1</td><td>0</td></tr><tr><td>Comet</td><td>0</td><td>0</td><td>-2.8</td></tr><tr><td><strong>score</strong></td><td><strong>0</strong></td><td><strong>4.6</strong></td><td><strong>-1.4</strong></td></tr><tr><td colspan="4"><strong>Endocrine disruption</strong></td></tr><tr><td>AR agonist</td><td>0</td><td>0</td><td>0</td></tr><tr><td>ERα agonist</td><td>0.004</td><td>0</td><td>0</td></tr><tr><td>AR antagonist</td><td>0.58</td><td>0</td><td>0</td></tr><tr><td>ERα antagonist</td><td>0</td><td>0</td><td>0</td></tr><tr><td><strong>score</strong></td><td><strong>0.15</strong></td><td><strong>0</strong></td><td><strong>0</strong></td></tr><tr><td colspan="4"><strong>Aquatic toxicity</strong></td></tr><tr><td>Zebra Fish</td><td>0</td><td>1.0</td><td>10.0</td></tr><tr><td><em>Daphnia</em></td><td>15.9</td><td>25.0</td><td>33.3</td></tr><tr><td><strong>score</strong></td><td><strong>7.9</strong></td><td><strong>13.0</strong></td><td><strong>21.7</strong></td></tr></tbody></table>

<figure><img src="image_14.png" /><figcaption>**Fig. 8.** Graphical representation of toxicity scores for hardeners for the 4 pillars. Detailed values are reported in Table 3. In each case, colored lines correspond to the threshold for toxicity categories defined in Supplementary material Table S6 (—: negligible; —: moderate; —: significant; —:strong).</figcaption></figure>

human health score (Table 4 and Supplementary material Fig. S2). Induction of oxidative stress was important in the ranking of A-Parts in the human health score, since the ROS level was not significantly increased in cells exposed to neither AP2 nor AP4, but was in cells exposed to the three other substances. The genotoxicity score reflected that all A-Parts

induced some DNA damage. In contrast, none of them was characterized as endocrine disruptor. The only remarkable feature in the toxicity of leachates was the weak but detectable endocrine disruption properties of reference substance based on the TCPF flame retardant, as well as to a lesser extent, leachates from the composite prepared with AP3 (Table 4).

### 3.3. Performance scoring for safer-by-design applications

The second scoring strategy was associated with the development, in the project, of an open-access tool aiming to guide material designers and recyclers in the design of SSRbD polymeric materials. This digital infrastructure combined information on several aspects investigated in the project: release and exposure, environmental impact, life cycle costing, and hazard. The general strategy for combining these very different sets of data was to categorize the studied substances on the basis of the comparison of their properties with those of conventional references. The determination of categories was based on the calculation of a Difference in Performance index (DiP), a value defined as the ratio between the difference of results between the reference and the alternative substances on the one hand, and the response of the reference on the other hand. It should be emphasized that the DiP for the reference substances is 0 because it corresponds to the comparison of the properties of a substance with itself.

Accordingly, we developed a categorization system for hazard assessment (Scheme 3). DiP values of each investigated substance were calculated for all toxicological endpoints. When assays were applied to both HaCaT and Caco-2 cell lines, DiP values were averaged. The equation used for the calculation of DiP of each experiment depended on the type of data. For assays providing a IC50 (or a CED20 value in ZET), Eq. (3) was used.

$$ DiP = 100 \times \frac{IC50alt - IC50ref}{IC50ref} \qquad (3) $$

with IC50ref and IC50alt the IC50 for the response of the cell to the reference and alternative substances in the considered assay. The same formalism was used for CED20 instead of IC50. DiP could be calculated with Eq. (3) only when both the IC50 of the reference (IC50ref) and the alternative (IC50alt) substances could be determined. When the cellular response to the alternative and reference substances in the considered assay was not different from the control and not different from each other, the issue of the impact of the substitution of the reference by the alternative substance is meaningless (Scheme 4a). The DiP was defined as non-applicable (N/A) and was not used in the subsequent steps of scoring. In some other cases, arbitrary values had to be applied. More complex situations were reached when only one of the substances had an effect and not the other. If no IC50ref was obtained in the investigated concentration range, all alternative substances for which a IC50 could be determined were thus more toxic than the reference. No DiP can be calculated but its value was arbitrary set at -100. Conversely, it may happen that a IC50 could be determined for the reference but not the alternative substance. This meant that the alternative was less toxic than the reference substance, which corresponds to an improvement of toxicological response by the use of alternative, and the DiP value was arbitrary set at +100.

Eq. (4) was applied to experiments carried out at specific concentrations.

$$ DiP = 100 \times \frac{Xref - Xalt}{Xref - Xsolv} \qquad (4) $$

with Xref, Xalt and Xsolv the respective response of the cell to the reference and alternative substances, and the solvent control in the considered assay.

The results of the statistical analysis were used to refine the determination of the DiP (Scheme 4b). The calculations relied first on the comparison of the effect of the considered reference substance (Xref)
<caption>**Table 4**</caption>

Toxicity scores for A-Parts and leachates. The value reported for individual assays are normalized with respect to the positive controls. When assays were performed on both HaCaT and Caco-2 cells, values were averaged. The final score in each pillar was calculated by averaging the normalized data in each assay. Results are expressed as % of the positive controls of the assays. Score visualization / formatting corresponds to the thresholds shown in Supplementary material Table S6 (dark green: negligible; light green: moderate; yellow: significant; red: strong).

<table><thead><tr><th rowspan="2"></th><th colspan="5">A-Parts</th><th colspan="5">Leachates</th></tr><tr><th>AP-CL</th><th>AP1</th><th>AP2</th><th>AP3</th><th>AP4</th><th>Leach-CL</th><th>Leach1</th><th>Leach2</th><th>Leach3</th><th>Leach4</th></tr></thead><tbody><tr><th colspan="11">Human health</th></tr><tr><td>cytotoxicity</td><td>2.3</td><td>2.4</td><td>2.1</td><td>2.2</td><td>2.3</td><td>0.08</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>Oxidative stress</td><td>14.4</td><td>11.0</td><td>0</td><td>4.7</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>epigenetics</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>n.d.</td><td>n.d.</td><td>n.d.</td><td>n.d.</td><td>n.d.</td></tr><tr><td>score</td><td>5.6</td><td>4.5</td><td>0.7</td><td>2.3</td><td>0.8</td><td>0.04</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><th colspan="11">Genotoxicity</th></tr><tr><td>53BP1</td><td>35.7</td><td>48.3</td><td>30.9</td><td>31.4</td><td>33.4</td><td>0</td><td>0.91</td><td>0.96</td><td>2.30</td><td>1.74</td></tr><tr><td>Comet</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>-2.3</td><td>-2.3</td><td>-2.4</td><td>-1.0</td></tr><tr><td>score</td><td>17.8</td><td>24.1</td><td>15.5</td><td>15.7</td><td>16.7</td><td>0</td><td>-0.7</td><td>-0.7</td><td>-0.06</td><td>0.35</td></tr><tr><th colspan="11">Endocrine disruption</th></tr><tr><td>AR agonist</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>ERα agonist</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.227</td><td>0</td><td>0</td><td>0.226</td><td>0</td></tr><tr><td>AR antagonist</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>ERα antagonist</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.008</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>score</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.059</td><td>0</td><td>0</td><td>0.056</td><td>0</td></tr><tr><th colspan="11">Aquatic toxicity</th></tr><tr><td>Zebra Fish</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>Daphnia</td><td>1.8</td><td>2.5</td><td>1.0</td><td>1.7</td><td>1.1</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr><tr><td>score</td><td>0.9</td><td>1.3</td><td>0.5</td><td>0.8</td><td>0.5</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr></tbody></table>

<figure><img src="image_15.png" /></figure>

**Scheme 3.** Principle of the calculation of performance scores. In a first step DiP were calculated for each substance and each assay by normalization with respect to the reference substances. The DiP for reference compounds is always 0 by definition. For assays performed on HaCaT and Caco-2 cells, values were averaged. DiP of the different assays were then averaged within each pillar. The latter value was used to categorize all alternative substances in each pillar using thresholds shown in Supplementary material Table S6.

with the solvent control (Xsolv), and then on the comparison of each alternative substance (Xalt) with the reference substance of their campaign (Xref). Several combinations have to be considered. DiP could be calculated with Eq. (4) only when Xref was statistically different from Xsolv, and Xalt statistically different from Xref. In contrast, DiP was not defined, and referred to as non-applicable (N/A), when none of the tested differences were statistically significant. In others cases, Eq. (4)

could ne be calculated and arbitrary values had to be applied to DiP. First, DiP was set at 0 (no difference between the reference and the alternative substances) when Xalt was not different from Xref, and either Xref or Xalt were statistically different from Xsolv. A second more complex situation where DiP was arbitrary set was when no difference was found between Xsolv and Xref, but a statistically significant difference between Xalt and Xref was observed. This meant that the reference
<figure><img src="image_16.png" /><figcaption>**Scheme 4.** Principles of the determination of the DiP values. a) in experiments providing IC50 values calculations or application of arbitrary values depended on the possibility of determining IC50 for either reference (IC50ref) or alternative substances (IC50alt); b) for experiments at specific concentrations, results were first dependent on the statistical significance of differences between the raw data of either the reference or alternatives substances (Xref and Xalt, respectively) on the one hand, and the solvent control of the assay (Xsolv) on the other hand. Statistical significance of the difference between Xalt and Xref was also taken into account.</figcaption></figure>

<caption>**Table 5**</caption>

Categorization of the performance of substances in the four pillars. The raw data of each toxicological assay were normalized for all alternative substances with respect to the reference substances (hardeners vs MDA, A-Parts vs AP-Cl, Leachates vs Leach-Cl). Eqs. (3) and (4) were used, or the DiP values were arbitrary set depending on the results of the statistical analysis. The colour codes correspond to the categories defined in Supplementary data Table S6. (dark green: strong improvement; light green: significant improvement; yellow: moderate improvement; red: deterioration).

<table><thead><tr><th>Campaign</th><th>Substance</th><th>Human health</th><th>Genotoxicity</th><th>Endocrine disruption</th><th>Aquatic toxicity</th></tr></thead><tbody><tr><td rowspan="4">A-Parts</td><td>AP-1</td><td>1</td><td>1</td><td>N/A</td><td>0</td></tr><tr><td>AP-2</td><td>1</td><td>1</td><td>N/A</td><td>3</td></tr><tr><td>AP-3</td><td>1</td><td>1</td><td>N/A</td><td>1</td></tr><tr><td>AP-4</td><td>1</td><td>2</td><td>N/A</td><td>3</td></tr><tr><td rowspan="2">Hardeners</td><td>4-AFD</td><td>1</td><td>1</td><td>3</td><td>0</td></tr><tr><td>2-AFD</td><td>1</td><td>1</td><td>3</td><td>0</td></tr><tr><td rowspan="4">Leachates</td><td>Leach1</td><td>3</td><td>1</td><td>3</td><td rowspan="4">Not tested</td></tr><tr><td>Leach2</td><td>3</td><td>1</td><td>3</td></tr><tr><td>Leach3</td><td>3</td><td>1</td><td>1</td></tr><tr><td>Leach4</td><td>3</td><td>0</td><td>3</td></tr></tbody></table>

substance had no effect in the considered assay but the alternative substance has a impact on the considered cellular endpoint. Eq. (4) cannot be applied because Xref should be replaced by Xsolv, which would lead to a division by 0. The value of the DiP was then arbitrary set at −100 or +100 whether the response for the alternative was larger or lower than that of the reference substance.

Using these equations and rules, we first determined the DiP values for the different assays applied to the tested substances (Supplementary material Table S7). They were then combined into the different categories for the four hazard pillars, and these final DiP values were used to

assign substances to different hazard performance categories (Table 5) defined by specific thresholds different from one pillar to the other (Supplementary material Table S6). Categories corresponded to alternative substances providing either large, significant or low improvement in toxicity when used as substitute to the reference substance. A last category gathered substances leading to the deterioration of the cellular responses by comparison with reference substances.
## 4. Discussion

The present work had two main objectives. The first was the collection of information on the toxicity of poorly investigated ingredients potentially used in novel processes for the synthesis of epoxy resin-based composites. We showed that toxicological properties of the alternative ingredients investigated by the materials scientists of the project were not obstacles to their use in the synthesis of epoxy vitrimers. The two alternative hardeners 4-AFD and 2-AFD were found to be more cytotoxic than the conventional MDA, although much less toxic than the positive control of the WST-1 assay. In contrast, 4-AFD and 2-AFD induced a lower oxidative stress than MDA, and no significant genotoxicity. They were also devoid of endocrine disruption properties, in contrast to MDA. The alternative flame retardants, tested in the A-Parts, were also less toxic than the reference TCPP. A-Parts are composed of FR and resin and their toxicological impact was mostly mediated by the latter component, tested as a pure product in AP1. The tested FR increased neither the cytotoxicity, the aquatic toxicity, the genotoxic potential nor the endocrine disruption impact of the resin. The alternative FR were found to decrease its oxidative potential, while TCPP increased it. The impact of FR was also reflected by the toxicity of the leachates of composite prepared with 4-AFD. These substances were not cytotoxic, did not induce aquatic toxicity and were not genotoxic. In contrast, the leachate prepared with the composite using TCPP as flame retardant induced a positive response in the endocrine disruption assays related to $Er\alpha$, both in the agonist and antagonist version. Among the alternative FR, only a phosphorous modified epoxy resin used in AP3 exhibited a response in one test, namely the agonist $Er\alpha$ CALUX® assay.

The large amounts of gathered data on numerous substances of different nature allowed us to draw some interesting conclusions on the different assays. Regarding impact on cellular viability and aquatic toxicity, disulfide hardeners were found to be more toxic than the reference product in cell lines, *Daphnia* and ZFE. The consistency between these data on very different biological models provides a strong confidence in the ranking of the compounds. Regarding viability assessment, we observed a possible artifact in the WST-1 assay for disulfide derivatives. Another key observation was made on genotoxicity. A-Parts were the only products inducing a strong increase in DNA damage, but only by 53BP1 measurements and not in the Comet assay. We could explain this result by the formation of DNA adducts. The results emphasize that the Comet assay reveals only a fraction of the genotoxic insult and is not a method for assessing "primary DNA damage" as sometimes reported. Our results provided also some insights on endocrine disruption assessment. Only three of the tested substances were found to exhibit endocrine disruption properties, and two of them were leachates. The latter substances were neither cytotoxic nor genotoxic and did not induce oxidative stress. This example emphasizes the need for endocrine disruption screening even for compounds that seem to be poorly toxic. Finally, we did not detect any modulation of the average DNA cytosine methylation status of the genome by any of the tested substances. This suggests this global marker may not be sensitive enough. Analysis of the DNA methylation at the sequence level in key parts of genes, like the promoter regions, is likely a more relevant approach.

We then leveraged the hazard data gathered for the different substances in an innovative scoring strategy. The extensive characterization of the toxicological properties of chemical substances leads to the production of large amounts of data of different natures because of the variety of investigated endpoints. For specific purposes, it may be relevant to combine these data into a few single scores that are easier to handle. Scoring and categorization strategies have already been developed for nanomaterials. They mostly aimed to link physicochemical parameters and toxicity (Arts et al., 2015; Di Battista et al., 2024; Tsiliki et al., 2022). More complex scoring systems have been built where safety is one component among others (Arias et al., 2024; Wohlleben et al., 2024). All the previously developed scoring strategies rely on the

regulatory toxicological endpoints and the CLP classification (Classification, Labelling, Packaging). As there is not enough regulatory toxicological information on new alternative substances, we developed a scoring system suitable for evaluating them considering toxicological information obtained from *in vitro* methods that can be used at the early pre-regulatory stages of the innovation. We actually developed two different scores. The first one assessed the individual toxicity of each tested substance and aimed mostly to rapidly share toxicological results with non-specialists, such as the material scientists of the project. The second was designed to be used in a digital SSRbD infrastructure comparing the performances of different synthesis routes. In both cases, results obtained with different assays were normalized and average in four pillars. This strategy provided a strong flexibility to the scoring system since results obtained by other techniques or on other biological models can be combined without limitations.

The toxicity score aimed to combine in a simple way the large amount of information on each substance. It was basically based on a normalization of the experimental results using the negative solvent controls and the positive controls for each assay. With the exception of cell death that cannot be larger than 100%, the maximal response of each toxicological assay is not known. Use of positive controls which induce strong and consistent responses represents a useful way to compensate for this uncertainty. In the present scoring system, normalization with respect of the positive controls also provided values which were not expressed in arbitrary unit but in percentage of the response for positive controls. With the limitation of a dependence on the concentration of the positive control used, this permits to rapidly define whether the tested substances are poorly or highly toxic. Unfortunately, requirement of a positive control is not compatible with all techniques. For example, the cytokine measurements performed in the project could not be included as the multiplex approach applied would require the inclusion of a positive control for each cytokine measured. When positive controls were properly selected for the specific assays, the developed toxicity score could be readily calculated and was easy to interpret.

The toxicity scores nicely reflected the ranking of the different alternative and reference substances. For hardeners, MDA exhibited the largest toxicity score in both human health and, more noticeable, in endocrine disruption potential. In genotoxicity, 4-AFD exhibited the largest score. The value was yet low and 4-AFD was categorized as moderately genotoxic. As far as aquatic toxicity was concerned, both 4-AFD and 2-AFD exhibited a largest score than MDA. However, the toxic concentrations for the two latter compounds are not environmentally relevant. Both alternative hardeners appeared thus to be interesting alternative to MDA. A-Parts were found to all have the same low scores in human health and aquatic toxicity. Their score for endocrine disruption was null. In contrast, the genotoxicity score corresponded to the "significant effect" category for all A-Parts. Consequently, use of alternative or reference A-Parts was not different in terms of genotoxicity. This conclusion could yet be modulated by the toxicity scores of leachates. Indeed, only the reference Leach-Cl (prepared with AP-Cl) and Leach3 (prepared with AP3) were endocrine disruptors. The scores of all leachates in human health, genotoxicity and aquatic toxicity were very low. It may thus be concluded that TCCP, the flame retardant present in AP-Cl, should be substituted, preferably not by the phosphorous modified epoxy resin found in AP3.

The second designed score, the performance score, followed a formalism already used for other aspects of the characterization of the innovative materials developed in the project. It aimed to assess changes in the toxicological impact of a process when conventional ingredients were replaced with alternative substances. The calculation of the performance score had to be adapted to account for the specificities of hazard assessment, which raised several methodological issues. In particular, not all substances induced a response in the *in vitro* assays used, as reflected by the statistical analysis. Consequently, calculation of the performance score was not always possible, and arbitrary values had
to be applied in some cases. Despite this complexity, application of the performance score to the experimental results allowed us the investigated substances to be categorized according to their ability to reduce the toxicological impact of the process.

The performance categorization led to conclusions similar to those based on the toxicity scores. For hardeners, a deterioration in aquatic toxicity was observed when MDA was replaced by either 4-AFD or 2-AFD, while a moderate improvement was found for human toxicity and genotoxicity. More importantly, a strong improvement was observed for endocrine disruption when MDA was substituted. The performance score therefore supported the selection of 4-AFD and 2-AFD as relevant alternatives. Performance categorization also showed that leachates of final composites produced by alternative synthesis routes performed better than the reference in terms of human health. A similar trend was observed for endocrine disruption, with the exception of AP3, which was categorized only as moderately improving because it showed activity in the ERα agonist test. Regarding genotoxicity, alternative leachates did not induce either a significant or a strong improvement. This can be explained by the fact that none of the leachates, including the reference, exhibited genotoxicity.

A more complex situation was observed for A-Parts. Only moderate improvements were identified for the human health and genotoxicity pillars, reflecting similar cellular responses to all A-Parts in the applied assays. In contrast, aquatic toxicity scores ranged from deterioration to major improvement. These results were unexpected, as all A-Parts exhibited similarly low toxicity. However, the differences of results between the reference and alternatives substances were statistically significant for Daphnia immobilization and DiP could be calculated. A wide range of DiP values, ranging between –36 and 99%, were obtained for the alternative A-Parts. Consequently, these substances were classified in drastically different performance categories. These results were actually not highly relevant because A-Parts were only moderately cytotoxic in Daphnia. When aquatic toxicity was not considered, the remaining performance scores for alternative A-Parts supported the conclusion that their toxicity was comparable to that of the reference containing TCPP. This example illustrates that the performance score has to be analyzed with the raw data or the toxicity scores in mind.

## 5. Conclusions

The present work nicely illustrates the contribution of hazard assessment to industrial challenges in the field of materials in a SSRbD context. The developed experimental workflow, that involved the study of analogous substances in campaigns, the inclusion of a reference substance, the use of solvent and positive controls in all assays, and a rigorous statistical analysis plan was found to be very relevant. Constant exchanges of information between toxicologists and material scientists during the whole project were also key to the success of the work. In addition to the collection of new toxicological information on poorly studied substances, the formalization of the hazard assessment results in the toxicity and performance scores is another strongly positive outcome of the work. Scoring strategies are not common in the field of chemical toxicity and the approach designed in this project could receive many applications.

### CRediT authorship contribution statement

**Marion Berenguer:** Writing – review & editing, Writing – original draft, Methodology, Investigation, Formal analysis, Conceptualization.
**David Béal:** Writing – review & editing, Investigation. **Justine Bétemps:** Writing – review & editing, Investigation. **Jade Boudard:** Writing – review & editing, Investigation. **Jean-Luc Ravanat:** Writing – review & editing, Investigation. **Manon C. Bouwmeester:** Writing – review & editing, Methodology, Investigation, Formal analysis. **Yvonne C.M. Staal:** Writing – review & editing, Methodology, Investigation, Formal analysis. **Virginia Cazzagon:** Writing – review & editing,

Methodology, Formal analysis. **Ana Candalija:** Writing – review & editing, Methodology, Investigation, Formal analysis. **Ruben Martinez:** Writing – review & editing, Methodology, Investigation, Formal analysis. **Nina Hambruch:** Writing – review & editing, Methodology, Investigation, Formal analysis. **Arrate Huegun:** Writing – review & editing, Investigation. **Valeria Berner:** Writing – review & editing, Methodology. **Carl-Christoph Höhne:** Writing – review & editing, Investigation. **Delphine Tissier:** Writing – review & editing, Methodology, Investigation. **Sebastien Artous:** Writing – review & editing, Methodology. **Jean Breton:** Writing – review & editing, Project administration, Methodology, Investigation, Formal analysis, Conceptualization. **Thierry Douki:** Writing – review & editing, Writing – original draft, Validation, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization.

### Declaration of competing interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

Institutions of all authors reports financial support was provided by European Union. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

### Acknowledgments

This project has received the funding from the European Union's Horizon Europe research and innovation program under grant no. 101057901. YS and MB thank Eline Groeneveld (RIVM) and Edwin Zwart (RIVM) for their dedicated work in conducting and analyzing the zebrafish experiments.

## Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.tiv.2026.106214.

### Data availability

Data will be made available on request.

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