# Exploring BPA alternatives – Environmental levels and toxicity review

Ondrej Adamovsky, Ksenia Groh, Anna Bialk-Bielińska, Beate Escher, R. Beaudouin, Liadys Mora Lagares, Knut Erik Tollefsen, Martina Fenske, Ewa Mulkiewicz, Nicolas Creusot, et al.

<figure><img src="image_1.png" /></figure>

## To cite this version:

Ondrej Adamovsky, Ksenia Groh, Anna Bialk-Bielińska, Beate Escher, R. Beaudouin, et al., Exploring BPA alternatives – Environmental levels and toxicity review. Environment International, 2024, 189, pp.108728. 10.1016/j.envint.2024.108728. hal-04614227

HAL Id: hal-04614227

https://hal.science/hal-04614227

Submitted on 17 Jun 2024

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<figure><img src="image_2.png" /></figure>
# Exploring BPA alternatives – Environmental levels and toxicity review

Ondrej Adamovsky, Ksenia Groh, Anna Bialk-Bielińska, Beate Escher, R. Beaudouin, Liadys Mora Lagares, Knut Erik Tollefsen, Martina Fenske, Ewa Mulkiewicz, Nicolas Creusot, et al.

<figure><img src="image_1.png" /></figure>

## To cite this version:

Ondrej Adamovsky, Ksenia Groh, Anna Bialk-Bielińska, Beate Escher, R. Beaudouin, et al., Exploring BPA alternatives – Environmental levels and toxicity review. Environment International, 2024, 189 (10), pp.108728. 10.1016/j.envint.2024.108728. hal-04614227

HAL Id: hal-04614227

https://hal.science/hal-04614227v1

Submitted on 17 Jun 2024

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_2.png" /></figure>
Review article

<figure><img src="image_3.png" /></figure>

Exploring BPA alternatives – Environmental levels and toxicity review

Ondrej Adamovsky a,*, Ksenia J. Groh b, Anna Białk-Bielińska c, Beate I. Escher d, R. Beaudouin e,
Liadys Mora Lagares f, Knut Erik Tollefsen g,aa, Martina Fenske h, Ewa Mulkiewicz c,
Nicolas Creusot i, Anita Sosnowska j, Susana Loureiro k, Jonny Beyer g, Guillermo Repetto l,
Alja Štern m, Isabel Lopes k, Marta Monteiro k, Andrea Zikova-Kloas n,o, Tina Eleršek m,
Marjan Vračko f, Szymon Zdybel j, Tomasz Puzyn j, Weronika Koczur c, Jane Ebsen Morthorst p,
Henrik Holbech p, Gunnar Carlsson q, Stefan Örn q, Óscar Herrero r, Ayesha Siddique s,
Matthias Liess s,t, Georg Braun d, Vanessa Srebny d, Bojana Žegura m, Nathalie Hinfrey u,
François Brion u, Dries Knapen v, Ellen Vandeputte v, Evelyn Stinckens v, Lucia Vergauwen v,
Lars Behrendt w, Maria João Silva x,y, Ludek Blaha a, Katerina Kyriakopoulou z,*

a RECETOX, Faculty of Science, Masaryk University, Kotlarska 2, 602 00 Brno, Czech Republic
b Eawag, Swiss Federal Institute of Aquatic Science and Technology, Ueberlandstrasse 133, 8600 Duebendorf, Switzerland
c Department of Environmental Analysis, Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland
d Department of Cell Toxicology, Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany
e Experimental Toxicology and Modeling Unit, INERIS, UMR-I 02 SEBIO, Verneuil en Halatte 65550, France
f Theory Department, Laboratory for Cheminformatics, National Institute of Chemistry, 1000 Ljubljana, Slovenia
g Norwegian Institute for Water Research (NIVA), Økernveien 94, N-0579 Oslo, Norway
h Department of Biochemistry and Ecotoxicology, Federal Institute of Hydrology (BfG), Am Mainzer Tor 1, 56068 Koblenz, Germany
i INRAE, French National Research Institute for Agriculture, Food & Environment, UR1454 EABX, Bordeaux Metabolome, MetaboHub, Gazinet Cestas, France
j Laboratory of Environmental Chemoinformatics, Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland
k CESAM and Department of Biology, University of Aveiro, 3810-193 Aveiro, Portugal
l Area of Toxicology, Universidad Pablo de Olavide, 41013-Sevilla, Spain
m National Institute of Biology, Department of Genetic Toxicology and Cancer Biology, Večna pot 121, 1000 Ljubljana, Slovenia
n Testing and Assessment Strategies Pesticides, German Federal Institute for Risk Assessment, Max-Dohnr-Str. 8-10, 10589 Berlin, Germany
o Ecotoxicological Laboratory, German Environment Agency, Schichauweg 58, 12307 Berlin, Germany
p Department of Biology, University of Southern Denmark, DK-5230 Odense M, Denmark
q Department of Biomedical Sciences and Veterinary Public Health, Swedish University of Agricultural Sciences, SE-750 07 Uppsala, Sweden
r Molecular Entomology, Biomarkers and Environmental Stress Group, Faculty of Science, Universidad Nacional de Educación a Distancia (UNED), 28232 Las Rozas de Madrid, Spain
s System Ecotoxicology, Helmholtz Centre for Environmental Research-UFZ, Permoserstrasse 15 04318 Leipzig, Germany
t RWTH Aachen University, Institute for Environmental Research (Biology V), Worringerweg 1, 52074 Aachen, Germany
u Ecotoxicology of Substances and Environments, Ineris, Verneuil-en-Halatte, France
v Zebrafishlab, Veterinary Physiology and Biochemistry, Department of Veterinary Sciences, University of Antwerp, Wilrijk, Belgium
w Science for Life Laboratory, Department of Organismal Biology, Program of Environmental Toxicology, Uppsala University, 75236 Uppsala, Sweden
x Department of Human Genetics, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
y Center for Toxicogenomics and Human Health (ToxOmics), NOVA Medical School-FCM, UNL, Lisbon, Portugal
z Laboratory of Environmental Control of Pesticides, Benaki Phytopathological Institute, 8th Stefanou Delta str., 14561, Kifissia, Attica, Greece
aa Norwegian University of Life Sciences (NMBU), Po.Box 5003, N-1432 Ås, Norway

ARTICLE INFO

Keywords:

BPA alternatives
Biological activity
In silico
Invertebrates
Vertebrates

A B S T R A C T

Bisphenol A alternatives are manufactured as potentially less harmful substitutes of bisphenol A (BPA) that offer similar functionality. These alternatives are already in the market, entering the environment and thus raising ecological concerns. However, it can be expected that levels of BPA alternatives will dominate in the future, they are limited information on their environmental safety. The EU PARC project highlights BPA alternatives as priority chemicals and consolidates information on BPA alternatives, with a focus on environmental relevance

<footnote>a RECETOX, Faculty of Science, Masaryk University, Kotlarska 2, 602 00 Brno, Czech Republic</footnote>

<footnote>b Eawag, Swiss Federal Institute of Aquatic Science and Technology, Ueberlandstrasse 133, 8600 Duebendorf, Switzerland</footnote>

<footnote>c Department of Environmental Analysis, Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland</footnote>

<footnote>d Department of Cell Toxicology, Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany</footnote>

<footnote>e Experimental Toxicology and Modeling Unit, INERIS, UMR-I 02 SEBIO, Verneuil en Halatte 65550, France</footnote>

<footnote>f Theory Department, Laboratory for Cheminformatics, National Institute of Chemistry, 1000 Ljubljana, Slovenia</footnote>

<footnote>g Norwegian Institute for Water Research (NIVA), Økernveien 94, N-0579 Oslo, Norway</footnote>

<footnote>h Department of Biochemistry and Ecotoxicology, Federal Institute of Hydrology (BfG), Am Mainzer Tor 1, 56068 Koblenz, Germany</footnote>

<footnote>i INRAE, French National Research Institute for Agriculture, Food & Environment, UR1454 EABX, Bordeaux Metabolome, MetaboHub, Gazinet Cestas, France</footnote>

<footnote>j Laboratory of Environmental Chemoinformatics, Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland</footnote>

<footnote>k CESAM and Department of Biology, University of Aveiro, 3810-193 Aveiro, Portugal</footnote>

<footnote>l Area of Toxicology, Universidad Pablo de Olavide, 41013-Sevilla, Spain</footnote>

<footnote>m National Institute of Biology, Department of Genetic Toxicology and Cancer Biology, Večna pot 121, 1000 Ljubljana, Slovenia</footnote>

<footnote>n Testing and Assessment Strategies Pesticides, German Federal Institute for Risk Assessment, Max-Dohnr-Str. 8-10, 10589 Berlin, Germany</footnote>

<footnote>o Ecotoxicological Laboratory, German Environment Agency, Schichauweg 58, 12307 Berlin, Germany</footnote>

<footnote>p Department of Biology, University of Southern Denmark, DK-5230 Odense M, Denmark</footnote>

<footnote>q Department of Biomedical Sciences and Veterinary Public Health, Swedish University of Agricultural Sciences, SE-750 07 Uppsala, Sweden</footnote>

<footnote>r Molecular Entomology, Biomarkers and Environmental Stress Group, Faculty of Science, Universidad Nacional de Educación a Distancia (UNED), 28232 Las Rozas de Madrid, Spain</footnote>

<footnote>s System Ecotoxicology, Helmholtz Centre for Environmental Research-UFZ, Permoserstrasse 15 04318 Leipzig, Germany</footnote>

<footnote>t RWTH Aachen University, Institute for Environmental Research (Biology V), Worringerweg 1, 52074 Aachen, Germany</footnote>

<footnote>u Ecotoxicology of Substances and Environments, Ineris, Verneuil-en-Halatte, France</footnote>

<footnote>v Zebrafishlab, Veterinary Physiology and Biochemistry, Department of Veterinary Sciences, University of Antwerp, Wilrijk, Belgium</footnote>

<footnote>w Science for Life Laboratory, Department of Organismal Biology, Program of Environmental Toxicology, Uppsala University, 75236 Uppsala, Sweden</footnote>

<footnote>x Department of Human Genetics, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal</footnote>

<footnote>y Center for Toxicogenomics and Human Health (ToxOmics), NOVA Medical School-FCM, UNL, Lisbon, Portugal</footnote>

<footnote>z Laboratory of Environmental Control of Pesticides, Benaki Phytopathological Institute, 8th Stefanou Delta str., 14561, Kifissia, Attica, Greece</footnote>

<footnote>aa Norwegian University of Life Sciences (NMBU), Po.Box 5003, N-1432 Ås, Norway</footnote>

<footnote>* Corresponding authors.</footnote>

<footnote>E-mail addresses: ondrej.adamovsky@recetox.muni.cz (O. Adamovsky), k.kyriakopoulou@bpi.gr (K. Kyriakopoulou).</footnote>
Review article

<figure><img src="image_3.png" /></figure>

Exploring BPA alternatives – Environmental levels and toxicity review

Ondrej Adamovsky a,*, Ksenia J. Groh b, Anna Białk-Bielińska c, Beate I. Escher d, R. Beaudouin e,
Liadys Mora Lagares f, Knut Erik Tollefsen g,aa, Martina Fenske h, Ewa Mulkiewicz c,
Nicolas Creusot i, Anita Sosnowska j, Susana Loureiro k, Jonny Beyer g, Guillermo Repetto l,
Alja Štern m, Isabel Lopes k, Marta Monteiro k, Andrea Zikova-Kloas n,o, Tina Eleršek m,
Marjan Vračko f, Szymon Zdybel j, Tomasz Puzyn j, Weronika Koczur c, Jane Ebsen Morthorst p,
Henrik Holbech p, Gunnar Carlsson q, Stefan Örn q, Óscar Herrero r, Ayesha Siddique s,
Matthias Liess s,t, Georg Braun d, Vanessa Srebny d, Bojana Žegura m, Nathalie Hinfrey u,
François Brion u, Dries Knapen v, Ellen Vandeputte v, Evelyn Stinckens v, Lucia Vergauwen v,
Lars Behrendt w, Maria João Silva x,y, Ludek Blaha a, Katerina Kyriakopoulou z,*

a RECETOX, Faculty of Science, Masaryk University, Kotlarska 2, 602 00 Brno, Czech Republic
b Eawag, Swiss Federal Institute of Aquatic Science and Technology, Ueberlandstrasse 133, 8600 Duebendorf, Switzerland
c Department of Environmental Analysis, Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland
d Department of Cell Toxicology, Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany
e Experimental Toxicology and Modeling Unit, INERIS, UMR-I 02 SEBIO, Verneuil en Halatte 65550, France
f Theory Department, Laboratory for Cheminformatics, National Institute of Chemistry, 1000 Ljubljana, Slovenia
g Norwegian Institute for Water Research (NIVA), Økernveien 94, N-0579 Oslo, Norway
h Department of Biochemistry and Ecotoxicology, Federal Institute of Hydrology (BfG), Am Mainzer Tor 1, 56068 Koblenz, Germany
i INRAE, French National Research Institute for Agriculture, Food & Environment, UR1454 EABX, Bordeaux Metabolome, MetaboHub, Gazinet Cestas, France
j Laboratory of Environmental Chemoinformatics, Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland
k CESAM and Department of Biology, University of Aveiro, 3810-193 Aveiro, Portugal
l Area of Toxicology, Universidad Pablo de Olavide, 41013-Sevilla, Spain
m National Institute of Biology, Department of Genetic Toxicology and Cancer Biology, Večna pot 121, 1000 Ljubljana, Slovenia
n Testing and Assessment Strategies Pesticides, German Federal Institute for Risk Assessment, Max-Dohnr-Str. 8-10, 10589 Berlin, Germany
o Ecotoxicological Laboratory, German Environment Agency, Schichauweg 58, 12307 Berlin, Germany
p Department of Biology, University of Southern Denmark, DK-5230 Odense M, Denmark
q Department of Biomedical Sciences and Veterinary Public Health, Swedish University of Agricultural Sciences, SE-750 07 Uppsala, Sweden
r Molecular Entomology, Biomarkers and Environmental Stress Group, Faculty of Science, Universidad Nacional de Educación a Distancia (UNED), 28232 Las Rozas de Madrid, Spain
s System Ecotoxicology, Helmholtz Centre for Environmental Research-UFZ, Permoserstrasse 15 04318 Leipzig, Germany
t RWTH Aachen University, Institute for Environmental Research (Biology V), Worringerweg 1, 52074 Aachen, Germany
u Ecotoxicology of Substances and Environments, Ineris, Verneuil-en-Halatte, France
v Zebrafishlab, Veterinary Physiology and Biochemistry, Department of Veterinary Sciences, University of Antwerp, Wilrijk, Belgium
w Science for Life Laboratory, Department of Organismal Biology, Program of Environmental Toxicology, Uppsala University, 75236 Uppsala, Sweden
x Department of Human Genetics, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
y Center for Toxicogenomics and Human Health (ToxOmics), NOVA Medical School-FCM, UNL, Lisbon, Portugal
z Laboratory of Environmental Control of Pesticides, Benaki Phytopathological Institute, 8th Stefanou Delta str., 14561, Kifissia, Attica, Greece
aa Norwegian University of Life Sciences (NMBU), Po.Box 5003, N-1432 Ås, Norway

ARTICLE INFO

Keywords:

BPA alternatives

Biological activity

In silico

Invertebrates

Vertebrates

A B S T R A C T

Bisphenol A alternatives are manufactured as potentially less harmful substitutes of bisphenol A (BPA) that offer similar functionality. These alternatives are already in the market, entering the environment and thus raising ecological concerns. However, it can be expected that levels of BPA alternatives will dominate in the future, they are limited information on their environmental safety. The EU PARC project highlights BPA alternatives as priority chemicals and consolidates information on BPA alternatives, with a focus on environmental relevance

<footnote>a RECETOX, Faculty of Science, Masaryk University, Kotlarska 2, 602 00 Brno, Czech Republic</footnote>

<footnote>b Eawag, Swiss Federal Institute of Aquatic Science and Technology, Ueberlandstrasse 133, 8600 Duebendorf, Switzerland</footnote>

<footnote>c Department of Environmental Analysis, Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland</footnote>

<footnote>d Department of Cell Toxicology, Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany</footnote>

<footnote>e Experimental Toxicology and Modeling Unit, INERIS, UMR-I 02 SEBIO, Verneuil en Halatte 65550, France</footnote>

<footnote>f Theory Department, Laboratory for Cheminformatics, National Institute of Chemistry, 1000 Ljubljana, Slovenia</footnote>

<footnote>g Norwegian Institute for Water Research (NIVA), Økernveien 94, N-0579 Oslo, Norway</footnote>

<footnote>h Department of Biochemistry and Ecotoxicology, Federal Institute of Hydrology (BfG), Am Mainzer Tor 1, 56068 Koblenz, Germany</footnote>

<footnote>i INRAE, French National Research Institute for Agriculture, Food & Environment, UR1454 EABX, Bordeaux Metabolome, MetaboHub, Gazinet Cestas, France</footnote>

<footnote>j Laboratory of Environmental Chemoinformatics, Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland</footnote>

<footnote>k CESAM and Department of Biology, University of Aveiro, 3810-193 Aveiro, Portugal</footnote>

<footnote>l Area of Toxicology, Universidad Pablo de Olavide, 41013-Sevilla, Spain</footnote>

<footnote>m National Institute of Biology, Department of Genetic Toxicology and Cancer Biology, Večna pot 121, 1000 Ljubljana, Slovenia</footnote>

<footnote>n Testing and Assessment Strategies Pesticides, German Federal Institute for Risk Assessment, Max-Dohnr-Str. 8-10, 10589 Berlin, Germany</footnote>

<footnote>o Ecotoxicological Laboratory, German Environment Agency, Schichauweg 58, 12307 Berlin, Germany</footnote>

<footnote>p Department of Biology, University of Southern Denmark, DK-5230 Odense M, Denmark</footnote>

<footnote>q Department of Biomedical Sciences and Veterinary Public Health, Swedish University of Agricultural Sciences, SE-750 07 Uppsala, Sweden</footnote>

<footnote>r Molecular Entomology, Biomarkers and Environmental Stress Group, Faculty of Science, Universidad Nacional de Educación a Distancia (UNED), 28232 Las Rozas de Madrid, Spain</footnote>

<footnote>s System Ecotoxicology, Helmholtz Centre for Environmental Research-UFZ, Permoserstrasse 15 04318 Leipzig, Germany</footnote>

<footnote>t RWTH Aachen University, Institute for Environmental Research (Biology V), Worringerweg 1, 52074 Aachen, Germany</footnote>

<footnote>u Ecotoxicology of Substances and Environments, Ineris, Verneuil-en-Halatte, France</footnote>

<footnote>v Zebrafishlab, Veterinary Physiology and Biochemistry, Department of Veterinary Sciences, University of Antwerp, Wilrijk, Belgium</footnote>

<footnote>w Science for Life Laboratory, Department of Organismal Biology, Program of Environmental Toxicology, Uppsala University, 75236 Uppsala, Sweden</footnote>

<footnote>x Department of Human Genetics, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal</footnote>

<footnote>y Center for Toxicogenomics and Human Health (ToxOmics), NOVA Medical School-FCM, UNL, Lisbon, Portugal</footnote>

<footnote>z Laboratory of Environmental Control of Pesticides, Benaki Phytopathological Institute, 8th Stefanou Delta str., 14561, Kifissia, Attica, Greece</footnote>

<footnote>aa Norwegian University of Life Sciences (NMBU), Po.Box 5003, N-1432 Ås, Norway</footnote>

<footnote>* Corresponding authors.</footnote>

<footnote>E-mail addresses: ondrej.adamovsky@recetox.muni.cz (O. Adamovsky), k.kyriakopoulou@bpi.gr (K. Kyriakopoulou).</footnote>
and on the identification of the research gaps. The review highlighted aspects and future perspectives. In brief, an extension of environmental monitoring is crucial, extending it to cover BPA alternatives to track their levels and facilitate the timely implementation of mitigation measures. The biological activity has been studied for BPA alternatives, but in a non-systematic way and prioritized a limited number of chemicals. For several BPA alternatives, the data has already provided substantial evidence regarding their potential harm to the environment. We stress the importance of conducting more comprehensive assessments that go beyond the traditional reproductive studies and focus on overlooked relevant endpoints. Future research should also consider mixture effects, realistic environmental concentrations, and the long-term consequences on biota and ecosystems.

# 1. Introduction

Bisphenol A (BPA) has garnered significant attention due to its endocrine disruption activity and adverse health effects on humans (Rubin, 2011) and other organisms even in environmentally realistic concentrations (Kudlak et al., 2022; Ji et al., 2013). However, so far due to the lack of appropriate studies and knowledge there is no evidence of effects at ecosystem level. Research has shown that BPA can act as an endocrine disruptor, interfering with hormone signaling pathways in the body, which was associated with a range of health concerns, including reproductive disorders, developmental abnormalities and metabolic changes among others (Pelch et al., 2019). While regulatory measures have been put in place to limit the exposure to BPA, the potential risks associated with its toxicity continue to be an area of ongoing research and concern for human and environmental health. In response to proposed and existing regulatory restrictions, manufacturers of BPA-containing products sought out potentially less harmful substitutes that offer similar functionality. These chemicals are commonly known as BPA alternatives. These alternatives were perceived as safer options and believed to have a more favorable toxicity profile. However, later studies have shown that many BPA alternatives may possess similar endocrine-disruptive or other adverse properties, suggesting that there is a lack of information for assessing their safety (Schaffert et al., 2021). Despite existing and ongoing research efforts on BPA alternatives, there is a significant research need to better understand the toxicity of these alternatives and to identify and develop safer materials for use in consumer products. The goal is to ensure that the replacements for BPA do not compromise human health or the environment while maintaining the necessary functionalities that consumers rely on.

Many of these BPA alternative substances are already on the market and are frequently found in the environment, although the information about their bioactivity is scattered and likely incomplete. Human activities, such as industrial processes, product manufacturing, and improper disposal, contribute to the release of BPA alternatives into the environment. Once released, these chemicals can enter the ecosystem through various pathways, such as industrial discharges, wastewater treatment plants, and leaching from landfills. The available monitoring studies show the presence of BPA alternatives in the environment and raise concerns about their potential ecological impacts. European Agencies [e.g. European Chemicals Agency (ECHA), European Food Safety Authority (EFSA)] recognized the increasing concerns about BPA and its alternatives, therefore scientists have prioritized research on BPA alternatives, and recently, the PARC project (Partnership for the Assessment of Risks from Chemicals) has also recognized the importance of this issue (Marx-Stoelting et al., 2023). In line with PARC's objectives, our aim is to consolidate existing information on the scope of the BPA alternatives problem by gaining a comprehensive understanding of their detectable levels in the environment. Furthermore, our review outlines existing methodologies and approaches employed to assess the bioactivity of BPA alternatives which use existing databases and *in silico* tools as well as invertebrate and vertebrate models that are relevant to the natural environment. By doing so, we aim to identify any research gaps that may be of significance to environmental toxicologists, industry scientists, and regulators. Additionally, gaining mechanistic insights into the disruptive effects of BPA alternatives will aid in selecting

chemicals that are suitable for the development of new toxicity assessment methods, which is one of the key priorities for PARC. Finally, the identification of knowledge gaps on the potential toxicity of BPA alternatives in different organisms' categories will reveal the need to focus on additional endpoints other than the ones already investigated.

# 2. Methodology

## 2.1. Studies on environmental levels

In the present review we performed a literature search for the identification of the most relevant studies with monitoring data of bisphenol's mixtures in different environmental compartments. The literature search was carried out in 2023 and followed the general principles of the European Food Safety Authority (EFSA) Guidance for systematic literature review (EFSA, 2010). The main objective of this literature review was the collection of monitoring data for bisphenols in different environmental compartments, i.e., water (surface fresh water and sea water), soil and sediment, across Europe.

Considering the overall objectives of the literature review, specific inclusion and exclusion criteria were set and followed for the screening of the identified references and the identification of the most relevant studies to be reviewed in detail (Table 1).

## 2.2. In silico approaches and toxicity studies

### 2.2.1. Chemical identifiers

The full names, long and short abbreviations of BPA and 25 BPA alternatives together with their chemical identifiers (DTXSID, CASRN) and molecular weights are given in Table 1.

### 2.2.2. Physicochemical properties

The octanol-water partition coefficient of the neutral species (logK<sub>ow</sub>) were collected from literature. Wherever possible, experimental values were preferred, however, if not available, estimates were recorded from the four prediction models in the Chemistry Dashboard (US EPA, 2023) and the predictions from KOWWIN v1.67 from ChemsPIDer (2023) and an average of the predicted logK<sub>ow</sub> were used for the

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

Inclusion/exclusion criteria for literature search for the collection of monitoring data of bisphenols.

<table><thead><tr><th>Language</th><th>IN</th><th>English</th></tr></thead><tbody><tr><td>Type of studies</td><td>IN</td><td>Monitoring studies in different environmental compartments</td></tr><tr><td></td><td>OUT</td><td>Studies regarding method validation (unless real samples are analyzed)</td></tr><tr><td>Location</td><td>IN</td><td>European countries</td></tr><tr><td></td><td>OUT</td><td>USA, Asian and other non-EU countries</td></tr><tr><td>Type of monitoring data</td><td>IN</td><td>Monitoring data for BPA alternatives</td></tr><tr><td></td><td>OUT</td><td>Monitoring data only for BPA</td></tr><tr><td>Analyzed matrices</td><td>IN</td><td>Water, surface water, groundwater, seawater, freshwater, sediment, soil</td></tr><tr><td></td><td>OUT</td><td>Air, wastewater, biological fluids (samples from biomonitoring studies), sewage sludge, sewage treatment plants, urban run-off, drinking water stored in bottles</td></tr></tbody></table>
and on the identification of the research gaps. The review highlighted aspects and future perspectives. In brief, an extension of environmental monitoring is crucial, extending it to cover BPA alternatives to track their levels and facilitate the timely implementation of mitigation measures. The biological activity has been studied for BPA alternatives, but in a non-systematic way and prioritized a limited number of chemicals. For several BPA alternatives, the data has already provided substantial evidence regarding their potential harm to the environment. We stress the importance of conducting more comprehensive assessments that go beyond the traditional reproductive studies and focus on overlooked relevant endpoints. Future research should also consider mixture effects, realistic environmental concentrations, and the long-term consequences on biota and ecosystems.

# 1. Introduction

Bisphenol A (BPA) has garnered significant attention due to its endocrine disruption activity and adverse health effects on humans (Rubin, 2011) and other organisms even in environmentally realistic concentrations (Kudlak et al., 2022; Ji et al., 2013). However, so far due to the lack of appropriate studies and knowledge there is no evidence of effects at ecosystem level. Research has shown that BPA can act as an endocrine disruptor, interfering with hormone signaling pathways in the body, which was associated with a range of health concerns, including reproductive disorders, developmental abnormalities and metabolic changes among others (Pelch et al., 2019). While regulatory measures have been put in place to limit the exposure to BPA, the potential risks associated with its toxicity continue to be an area of ongoing research and concern for human and environmental health. In response to proposed and existing regulatory restrictions, manufacturers of BPA-containing products sought out potentially less harmful substitutes that offer similar functionality. These chemicals are commonly known as BPA alternatives. These alternatives were perceived as safer options and believed to have a more favorable toxicity profile. However, later studies have shown that many BPA alternatives may possess similar endocrine-disruptive or other adverse properties, suggesting that there is a lack of information for assessing their safety (Schaffert et al., 2021). Despite existing and ongoing research efforts on BPA alternatives, there is a significant research need to better understand the toxicity of these alternatives and to identify and develop safer materials for use in consumer products. The goal is to ensure that the replacements for BPA do not compromise human health or the environment while maintaining the necessary functionalities that consumers rely on.

Many of these BPA alternative substances are already on the market and are frequently found in the environment, although the information about their bioactivity is scattered and likely incomplete. Human activities, such as industrial processes, product manufacturing, and improper disposal, contribute to the release of BPA alternatives into the environment. Once released, these chemicals can enter the ecosystem through various pathways, such as industrial discharges, wastewater treatment plants, and leaching from landfills. The available monitoring studies show the presence of BPA alternatives in the environment and raise concerns about their potential ecological impacts. European Agencies [e.g. European Chemicals Agency (ECHA), European Food Safety Authority (EFSA)] recognized the increasing concerns about BPA and its alternatives, therefore scientists have prioritized research on BPA alternatives, and recently, the PARC project (Partnership for the Assessment of Risks from Chemicals) has also recognized the importance of this issue (Marx-Stoelting et al., 2023). In line with PARC's objectives, our aim is to consolidate existing information on the scope of the BPA alternatives problem by gaining a comprehensive understanding of their detectable levels in the environment. Furthermore, our review outlines existing methodologies and approaches employed to assess the bioactivity of BPA alternatives which use existing databases and *in silico* tools as well as invertebrate and vertebrate models that are relevant to the natural environment. By doing so, we aim to identify any research gaps that may be of significance to environmental toxicologists, industry scientists, and regulators. Additionally, gaining mechanistic insights into the disruptive effects of BPA alternatives will aid in selecting

chemicals that are suitable for the development of new toxicity assessment methods, which is one of the key priorities for PARC. Finally, the identification of knowledge gaps on the potential toxicity of BPA alternatives in different organisms' categories will reveal the need to focus on additional endpoints other than the ones already investigated.

# 2. Methodology

## 2.1. Studies on environmental levels

In the present review we performed a literature search for the identification of the most relevant studies with monitoring data of bisphenol's mixtures in different environmental compartments. The literature search was carried out in 2023 and followed the general principles of the European Food Safety Authority (EFSA) Guidance for systematic literature review (EFSA, 2010). The main objective of this literature review was the collection of monitoring data for bisphenols in different environmental compartments, i.e., water (surface fresh water and sea water), soil and sediment, across Europe.

Considering the overall objectives of the literature review, specific inclusion and exclusion criteria were set and followed for the screening of the identified references and the identification of the most relevant studies to be reviewed in detail (Table 1).

## 2.2. *In silico* approaches and toxicity studies

### 2.2.1. Chemical identifiers

The full names, long and short abbreviations of BPA and 25 BPA alternatives together with their chemical identifiers (DTXSID, CASRN) and molecular weights are given in Table 1.

### 2.2.2. Physicochemical properties

The octanol-water partition coefficient of the neutral species (logK<sub>ow</sub>) were collected from literature. Wherever possible, experimental values were preferred, however, if not available, estimates were recorded from the four prediction models in the Chemistry Dashboard (US EPA, 2023) and the predictions from KOWWIN v1.67 from ChemsPIDer (2023) and an average of the predicted logK<sub>ow</sub> were used for the

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

Inclusion/exclusion criteria for literature search for the collection of monitoring data of bisphenols.

<table><thead><tr><th>Language</th><th>IN</th><th>English</th></tr></thead><tbody><tr><td>Type of studies</td><td>IN</td><td>Monitoring studies in different environmental compartments</td></tr><tr><td></td><td>OUT</td><td>Studies regarding method validation (unless real samples are analyzed)</td></tr><tr><td>Location</td><td>IN</td><td>European countries</td></tr><tr><td></td><td>OUT</td><td>USA, Asian and other non-EU countries</td></tr><tr><td>Type of monitoring data</td><td>IN</td><td>Monitoring data for BPA alternatives</td></tr><tr><td></td><td>OUT</td><td>Monitoring data only for BPA</td></tr><tr><td>Analyzed matrices</td><td>IN</td><td>Water, surface water, groundwater, seawater, freshwater, sediment, soil</td></tr><tr><td></td><td>OUT</td><td>Air, wastewater, biological fluids (samples from biomonitoring studies), sewage sludge, sewage treatment plants, urban run-off, drinking water stored in bottles</td></tr></tbody></table>
prediction of the liposome-water partition constants.

The acidity constants pKa for bisphenol S (BPS) and tetrabromobisphenol A (TBBPA) were measured using a Sirius T3 titrator (Niu et al. 2022) and the remaining compounds were predicted with ACD/Percepta (2015), using the GALAS algorithm. The fraction of neutral species αneutral was calculated with eq. (1) for monoprotic acids and according to Escher et al. 2020 for diprotic acids (Escher et al., 2020).

$$ \alpha_{\text{neutral}} = \frac{1}{1 + 10^{\text{pH} - \text{p}K_a}} \qquad (1) $$

The logKow of all neutral species was converted to the liposome-water partition constant log Klipw with the Quantitative Structure-Activity Relationship (QSAR) established by Endo et al. (eq. (2)).

$$ \log K_{\text{lipw}} = 1.01 \times \log K_{\text{ow}} + 0.12 \quad \text{for} \quad -1 < \log K_{\text{ow}} < 8 \qquad (2) $$

The Klipw relates to the neutral species, but some of the BPA alternatives are partially ionized. The Dlipw(pH 7.4) is considered a better predictor of uptake into cells and organisms than the ionization-corrected Kow (Escher et al. 2020a). The Dlipw(pH 7.4) was estimated with an equation from Escher et al. (2020a).

$$ D_{\text{lipw}}(\text{pH}7.4) = K_{\text{lipw}}(\text{neutral species}) \times [\alpha_{\text{neutral}} + 0.1 \times (1 - \alpha_{\text{neutral}})] \qquad (3) $$

### 2.2.3. In vitro bioassay data

All concentration-response data for in vitro cell-based bioassays were downloaded from the cHTS database included in CurveSurfer which is part of the Integrated Chemical Environment (ICE) on the National Toxicology Program (NTP) of the U.S. Department of Health and Human Services (Abendini et al. 2021). Only cell-based assays from Tox21 and Attagene (ATG) assays were included in the analysis. The code for the R-script used to filter the Tox21 data, fit the corresponding concentration-response curves and calculate EC₁₀ values is described in detail by Braun and Escher (2023) and is published on GitHub (https://github.com/braungeorg/NeuroMixPrioritization.git). R version 4.1.3 has to be used in combination with RStudio version 2021.9.2.382. The following improvements have been added to the R-script: Instead of using the relative AC₅₀ value as threshold for testing for acceptable data point distributions of the concentration response curves (CRC), the EC₁₀, where 10% stands for 10% of the maximum effect, was used. For the Tox21 assays the maximum was 1 (100%). The assays from Attagene did not have a typical response maximum of 100% but were recorded as a log2-fold response induction, which had to be converted first to % by deriving the experimental maximum of 3.5 of all Attagene assays from the 95% quantile of all maxima. Therefore, the maximum was set to 3.5 for all ATG assays and the EC₁₀ refers to a log2-fold response induction value of 0.35.

### 2.2.4. Baseline toxicity prediction

Baseline toxicity is the minimal toxicity that any chemical exhibits. For human cell lines the IC₁₀ baseline can be predicted from the Dlipw(pH 7.4) with the QSAR given by eq. (4) established in our lab (Lee et al. 2021). Most baseline toxicity QSARs are linear with hydrophobicity but the baseline toxicity QSAR for cell lines is based on nominal concentrations and the bend in the QSAR is caused by binding of hydrophobic chemicals to medium components.

$$ IC_{10, \text{baseline}}(M) = \frac{1}{10^{1.23 + 4.97 \times (1 - e^{-0.236 \times D_{\text{lipw}}})}} \qquad (4) $$

### 2.2.5. Evaluation of specificity of effects

By comparing the prediction for baseline toxicity, expressed as inhibitory concentration IC₁₀ for 10% cytotoxicity, with experimental EC₁₀ one can identify which effects are caused by baseline toxicity and which effects are specific. The reporter gene will then give information about what type of specific effect is relevant. The specificity ratio

SRbaseline is a measure for how much more potent than baseline toxicity and therefore how specific a chemical is. It can be calculated with eq. (5) (Escher et al. 2020b).

$$ \text{Specificity Ratio SR}_{\text{baseline}} = \frac{IC_{10, \text{baseline}}}{EC_{10}} \qquad (5) $$

For those assays that also have cytotoxicity measured, the toxic ratio TR (Maeder et al. 2004) as the ratio between the baseline toxicity prediction IC₁₀, baseline and the experimental cytotoxicity IC₁₀ (eq. (6)) can be defined.

$$ \text{Toxic Ratio TR} = \frac{IC_{10, \text{baseline}}}{IC_{10}} \qquad (6) $$

## 2.3. Microbial organisms as single species or microbiomes

The literature review was performed on Web of Science by using “all fields” research with the following word sequence: (“BPA” OR “BPA alternatives” OR “BPA substitutes”) AND (“microbes” OR “microbiomes” OR “microbial organism” OR “microbial communities”). From this search, additional cited articles (not found in WoS) were examined for their relevance to the topic.

## 2.4. Studies investigating invertebrate models

### 2.4.1. Terrestrial and aquatic insects studies

The literature search for toxicity data of bisphenols and its alternatives to insects was performed by combining the search terms “insects” or “terrestrial insects” and “bisphenols” or “BPA alternatives”. The search was carried out in Scopus database.

### 2.4.2. Gastropods (Molluscs) studies

The following alternatives have been included in the literature search (mollus* AND bisphenol/ isopropylidenediphenol/ pergafast/ BADGE/ BPS/ BPF/ BPE/ BPAP/ BPAF/ BPZ/ TBBPA).

### 2.4.3. Ascidian studies

The literature search for toxicity data in Ciona and ascidians of bisphenols and its alternatives was performed in the Web of Science (WoS) database by applying sequences of search terms separated by with Boolean operators (i.e., AND, OR, NOT or AND NOT). Searches were done in a broad manner by engaging the “Topic” domains in the “All Databases” option and the “All fields” domains in the “WoS Core Collection” option. Search terms identifying ascidians were: “Ciona” OR “Phallusia” OR “ascidian*” OR “tunicate*”). As search terms for chemicals the chemical identifiers listed in Table 2 were used (popular names, IUPAC-names, abbreviations, short abbreviations, and the CAS Registry Numbers). Star-mark (*) was used to avoid singular/plural issues. All articles that were returned based on the above search criterions were filtered by relevance-assessing the title, abstract and whole paper (when accessible). Articles that were found to be not relevant were removed. Articles remaining after filtering (both regular articles and reviews) were examined and data/information were harvested and further processed/analyzed for this study.

### 2.4.4. Crustaceans studies

The literature search for toxicity data of bisphenols and its alternatives to crustacean such as Daphnia magna and Artemia species was performed by combining the search terms “Daphnia magna” or “D. magna”, “Artemia”, “Artemia salina”, “bisphenol” bisphenol A”, “BPA”, “BPA alternatives”, “BPA analogues”, “BPA substitutes”, “toxicity”, “ecotoxicity” with the Boolean operators “AND” or “OR”. of a sequence of words that were associated with Boolean operators.

### 2.4.5. Nematoda studies

To obtain an overview of already conducted studies on BPA and BPA
prediction of the liposome-water partition constants.

The acidity constants pKa for bisphenol S (BPS) and tetrabromobisphenol A (TBBPA) were measured using a Sirius T3 titrator (Niu et al. 2022) and the remaining compounds were predicted with ACD/Percepta (2015), using the GALAS algorithm. The fraction of neutral species αneutral was calculated with eq. (1) for monoprotic acids and according to Escher et al. 2020 for diprotic acids (Escher et al., 2020).

$$ \alpha_{\text{neutral}} = \frac{1}{1 + 10^{\text{pH} - \text{p}K_a}} \qquad (1) $$

The logKow of all neutral species was converted to the liposome-water partition constant log Klipw with the Quantitative Structure-Activity Relationship (QSAR) established by Endo et al. (eq. (2)).

$$ \log K_{\text{lipw}} = 1.01 \times \log K_{\text{ow}} + 0.12 \quad \text{for} \quad -1 < \log K_{\text{ow}} < 8 \qquad (2) $$

The Klipw relates to the neutral species, but some of the BPA alternatives are partially ionized. The Dlipw(pH 7.4) is considered a better predictor of uptake into cells and organisms than the ionization-corrected Kow (Escher et al. 2020a). The Dlipw(pH 7.4) was estimated with an equation from Escher et al. (2020a).

$$ D_{\text{lipw}}(\text{pH}7.4) = K_{\text{lipw}}(\text{neutral species}) \times [\alpha_{\text{neutral}} + 0.1 \times (1 - \alpha_{\text{neutral}})] \qquad (3) $$

### 2.2.3. In vitro bioassay data

All concentration-response data for in vitro cell-based bioassays were downloaded from the cHTS database included in CurveSurfer which is part of the Integrated Chemical Environment (ICE) on the National Toxicology Program (NTP) of the U.S. Department of Health and Human Services (Abendini et al. 2021). Only cell-based assays from Tox21 and Attagene (ATG) assays were included in the analysis. The code for the R-script used to filter the Tox21 data, fit the corresponding concentration-response curves and calculate EC₁₀ values is described in detail by Braun and Escher (2023) and is published on GitHub (https://github.com/braungeorg/NeuroMixPrioritization.git). R version 4.1.3 has to be used in combination with RStudio version 2021.9.2.382. The following improvements have been added to the R-script: Instead of using the relative AC₅₀ value as threshold for testing for acceptable data point distributions of the concentration response curves (CRC), the EC₁₀, where 10% stands for 10% of the maximum effect, was used. For the Tox21 assays the maximum was 1 (100%). The assays from Attagene did not have a typical response maximum of 100% but were recorded as a log2-fold response induction, which had to be converted first to % by deriving the experimental maximum of 3.5 of all Attagene assays from the 95% quantile of all maxima. Therefore, the maximum was set to 3.5 for all ATG assays and the EC₁₀ refers to a log2-fold response induction value of 0.35.

### 2.2.4. Baseline toxicity prediction

Baseline toxicity is the minimal toxicity that any chemical exhibits. For human cell lines the IC₁₀ baseline can be predicted from the Dlipw(pH 7.4) with the QSAR given by eq. (4) established in our lab (Lee et al. 2021). Most baseline toxicity QSARs are linear with hydrophobicity but the baseline toxicity QSAR for cell lines is based on nominal concentrations and the bend in the QSAR is caused by binding of hydrophobic chemicals to medium components.

$$ IC_{10, \text{baseline}}(M) = \frac{1}{10^{1.23 + 4.97 \times (1 - e^{-0.236 \times D_{\text{lipw}}})}} \qquad (4) $$

### 2.2.5. Evaluation of specificity of effects

By comparing the prediction for baseline toxicity, expressed as inhibitory concentration IC₁₀ for 10% cytotoxicity, with experimental EC₁₀ one can identify which effects are caused by baseline toxicity and which effects are specific. The reporter gene will then give information about what type of specific effect is relevant. The specificity ratio

SRbaseline is a measure for how much more potent than baseline toxicity and therefore how specific a chemical is. It can be calculated with eq. (5) (Escher et al. 2020b).

$$ \text{Specificity Ratio SR}_{\text{baseline}} = \frac{IC_{10, \text{baseline}}}{EC_{10}} \qquad (5) $$

For those assays that also have cytotoxicity measured, the toxic ratio TR (Maeder et al. 2004) as the ratio between the baseline toxicity prediction IC₁₀, baseline and the experimental cytotoxicity IC₁₀ (eq. (6)) can be defined.

$$ \text{Toxic Ratio TR} = \frac{IC_{10, \text{baseline}}}{IC_{10}} \qquad (6) $$

## 2.3. Microbial organisms as single species or microbiomes

The literature review was performed on Web of Science by using “all fields” research with the following word sequence: (“BPA” OR “BPA alternatives” OR “BPA substitutes”) AND (“microbes” OR “microbiomes” OR “microbial organism” OR “microbial communities”). From this search, additional cited articles (not found in WoS) were examined for their relevance to the topic.

## 2.4. Studies investigating invertebrate models

### 2.4.1. Terrestrial and aquatic insects studies

The literature search for toxicity data of bisphenols and its alternatives to insects was performed by combining the search terms “insects” or “terrestrial insects” and “bisphenols” or “BPA alternatives”. The search was carried out in Scopus database.

### 2.4.2. Gastropods (Molluscs) studies

The following alternatives have been included in the literature search (mollus* AND bisphenol/ isopropylidenediphenol/ pergafast/ BADGE/ BPS/ BPF/ BPE/ BPAP/ BPAF/ BPZ/ TBBPA).

### 2.4.3. Ascidian studies

The literature search for toxicity data in Ciona and ascidians of bisphenols and its alternatives was performed in the Web of Science (WoS) database by applying sequences of search terms separated by with Boolean operators (i.e., AND, OR, NOT or AND NOT). Searches were done in a broad manner by engaging the “Topic” domains in the “All Databases” option and the “All fields” domains in the “WoS Core Collection” option. Search terms identifying ascidians were: “Ciona” OR “Phallusia” OR “ascidian*” OR “tunicate*”). As search terms for chemicals the chemical identifiers listed in Table 2 were used (popular names, IUPAC-names, abbreviations, short abbreviations, and the CAS Registry Numbers). Star-mark (*) was used to avoid singular/plural issues. All articles that were returned based on the above search criterions were filtered by relevance-assessing the title, abstract and whole paper (when accessible). Articles that were found to be not relevant were removed. Articles remaining after filtering (both regular articles and reviews) were examined and data/information were harvested and further processed/analyzed for this study.

### 2.4.4. Crustaceans studies

The literature search for toxicity data of bisphenols and its alternatives to crustacean such as Daphnia magna and Artemia species was performed by combining the search terms “Daphnia magna” or “D. magna”, “Artemia”, “Artemia salina”, “bisphenol” bisphenol A”, “BPA”, “BPA alternatives”, “BPA analogues”, “BPA substitutes”, “toxicity”, “ecotoxicity” with the Boolean operators “AND” or “OR”. of a sequence of words that were associated with Boolean operators.

### 2.4.5. Nematoda studies

To obtain an overview of already conducted studies on BPA and BPA
<caption>**Table 2**</caption>

Chemical identifiers and physicochemical properties of the BPA alternatives. Octanol-water partition constant of the neutral species, logK<sub>ow</sub>; acidity constant pK<sub>a</sub>. Thereof derived speciation and liposome-water distribution ratios logD<sub>lipw</sub>(pH 7.4). IC<sub>10,baseline</sub> predicted with the baseline toxicity QSAR from Lee et al. 2021 (Lee et al., 2021).

<table><thead><tr><th>IUPAC-Name</th><th>Abbreviation</th><th>Short<br>abbreviation</th><th>MW (g/<br>mol)</th><th>CASRN</th><th>logK<sub>ow</sub><br>[L/L]</th><th>pK<sub>a</sub><br>(acid)</th><th>pK<sub>a</sub><br>(acid)</th><th>Fraction<br>neutral species<br>(pH 7.4)</th><th>log D<sub>lipw</sub><br>(pH 7.4)</th><th>IC<sub>10,<br>baseline</sub><br>(M)</th></tr></thead><tbody><tr><td>4,4'-Sulfonyldiphenol</td><td>Bisphenol S</td><td>BPS</td><td>250.27</td><td>80-09-1</td><td>1.30</td><td>7.26</td><td>7.92</td><td>36%</td><td>1.05</td><td>4.74E-03</td></tr><tr><td>2,2,4,4-Tetramethyl-1,3-<br>cyclobutanediol (racemate)</td><td>r-TMCD</td><td>rTMCD</td><td>144.21</td><td>3010-96-6</td><td>1.30</td><td>15.4</td><td>-</td><td>100%</td><td>1.43</td><td>2.21E-03</td></tr><tr><td>cis-2,2,4,4-Tetramethyl-1,3-<br>cyclobutanediol</td><td>c-TMCD</td><td>cTMCD</td><td>144.21</td><td>3039-96-1</td><td>1.30</td><td>15.4</td><td>-</td><td>100%</td><td>1.43</td><td>2.21E-03</td></tr><tr><td>2,4'-Dihydroxydiphenyl sulfone</td><td>2,4-BPS</td><td>24BPS</td><td>250.27</td><td>5397-34-2</td><td>1.42</td><td>7.9</td><td>9.1</td><td>76%</td><td>1.44</td><td>2.17E-03</td></tr><tr><td>Benzyl 4-hydroxybenzoate</td><td>Benzylparaben</td><td>BzPB</td><td>228.25</td><td>94-18-8</td><td>3.56</td><td>8.5</td><td>-</td><td>93%</td><td>3.69</td><td>7.63E-05</td></tr><tr><td>4-[[4-(Allyloxy)phenyl]sulfonyl]<br>phenol</td><td>BPS-MAE</td><td>BPS-MAE</td><td>290.33</td><td>97042-18-7</td><td>2.92</td><td>8</td><td>-</td><td>80%</td><td>2.98</td><td>1.81E-04</td></tr><tr><td>N-(p-toluenesulfonyl)-N'-[3-(p-<br>toluenesulfonyloxy)phenyl]urea</td><td>Pergafast 201</td><td>Pergafast</td><td>460.52</td><td>232938-43-1</td><td>4.19</td><td>3.70</td><td>-</td><td>0%</td><td>3.35</td><td>1.13E-04</td></tr><tr><td>4-[(4-Isopropoxyphenyl)sulfonyl]<br>phenol</td><td>D-8</td><td>D8</td><td>292.35</td><td>95235-30-6</td><td>2.96</td><td>8.00</td><td>-</td><td>80%</td><td>3.02</td><td>1.73E-04</td></tr><tr><td>Bis(4-hydroxyphenyl)methane</td><td>Bisphenol F</td><td>BPF</td><td>200.23</td><td>620-92-8</td><td>2.91</td><td>9.7</td><td>10.50</td><td>100%</td><td>3.06</td><td>1.64E-04</td></tr><tr><td>4-[4-(benzyloxy)benzenesulfonyl]<br>phenol</td><td>BPS-MPE</td><td>BPS-MPE</td><td>340.39</td><td>63134-33-8</td><td>4.18</td><td>6.3</td><td>-</td><td>7%</td><td>3.56</td><td>8.82E-05</td></tr><tr><td>1,1-Bis(4-hydroxyphenyl)ethane</td><td>Bisphenol E</td><td>BPE</td><td>214.26</td><td>2081-08-5</td><td>3.12</td><td>9.7</td><td>10.50</td><td>100%</td><td>3.27</td><td>1.25E-04</td></tr><tr><td>4,4'-Bis(p-tolylsulfonylureido)<br>diphenylmethane</td><td>BTUM</td><td>BTUM</td><td>592.69</td><td>151882-81-4</td><td>5.21</td><td>3.90</td><td>4.60</td><td>0%</td><td>4.38</td><td>3.69E-05</td></tr><tr><td>4,4'-Thiodiphenol</td><td>BPT</td><td>BPT</td><td>218.27</td><td>2664-63-3</td><td>3.34</td><td>9.7</td><td>10.50</td><td>100%</td><td>3.49</td><td>9.56E-05</td></tr><tr><td>5,5-Dimethyl-3,7-dioxa-1,9(2)-bis<br>(oxirana)-4,6(2,4)-<br>dibenzenanonaphane</td><td>BADGE</td><td>BADGE</td><td>340.42</td><td>1675-54-3</td><td>3.71</td><td>-</td><td>-</td><td>100%</td><td>3.86</td><td>6.28E-05</td></tr><tr><td>Benzeneacetic acid, 4-hydroxy-<br>alpha-(4-hydroxyphenyl)-, methyl<br>ester</td><td>Bz</td><td>Bz</td><td>258.27</td><td>5129-00-0</td><td>2.73</td><td>9.3</td><td>10.10</td><td>99%</td><td>2.87</td><td>2.11E-04</td></tr><tr><td>4,4'-(Propane-2,2-diyl)diphenol</td><td>Bisphenol A</td><td>BPA</td><td>228.29</td><td>80-05-7</td><td>3.32</td><td>9.7</td><td>10.5</td><td>100%</td><td>3.65</td><td>7.95E-05</td></tr><tr><td>4,4'-(1-Phenylethylidene)bisphenol</td><td>Bisphenol AP</td><td>BPAP</td><td>290.36</td><td>1571-75-1</td><td>4.43</td><td>9.70</td><td>10.50</td><td>100%</td><td>4.59</td><td>3.04E-05</td></tr><tr><td>4,4'-(Butane-2,2-diyl)diphenol</td><td>Bisphenol B</td><td>BPB</td><td>242.32</td><td>77-40-7</td><td>3.95</td><td>9.7</td><td>10.50</td><td>100%</td><td>4.10</td><td>4.87E-05</td></tr><tr><td>3,3'-Dimethylbisphenol A</td><td>Bisphenol C</td><td>BPC</td><td>256.35</td><td>79-97-0</td><td>4.32</td><td>9.7</td><td>10.5</td><td>100%</td><td>4.48</td><td>3.35E-05</td></tr><tr><td>4,4'-(1,1,1,3,3,3-<br>Hexafluoropropane-2,2-diyl)<br>diphenol</td><td>Bisphenol AF</td><td>BPAF</td><td>336.23</td><td>1478-61-1</td><td>3.70</td><td>8.7</td><td>9.50</td><td>95%</td><td>3.83</td><td>6.48E-05</td></tr><tr><td>1,1'-Bis(4-hydroxyphenyl)<br>cyclohexane</td><td>Bisphenol Z</td><td>BPZ</td><td>268.36</td><td>843-55-0</td><td>4.54</td><td>9.7</td><td>10.50</td><td>100%</td><td>4.70</td><td>2.74E-05</td></tr><tr><td>4,4'-[1,4-Phenylenebis(1-<br>methylethylidene)] bis-phenol</td><td>Bisphenol P</td><td>BPP</td><td>346.47</td><td>2167-51-3</td><td>6.10</td><td>9.7</td><td>10.30</td><td>100%</td><td>6.28</td><td>8.50E-06</td></tr><tr><td>2,2-Bis(4-hydroxy-3-<br>isopropylphenyl)propane</td><td>Bisphenol G</td><td>BPG</td><td>312.45</td><td>127-54-8</td><td>6.04</td><td>10.5</td><td>11.3</td><td>100%</td><td>6.22</td><td>8.79E-06</td></tr><tr><td>3,3',5,5'-Tetrabromobisphenol A</td><td>TBBPA</td><td>TBBPA</td><td>543.88</td><td>79-94-7</td><td>6.99</td><td>7.7</td><td>8.50</td><td>65%</td><td>7.01</td><td>5.62E-06</td></tr><tr><td>2,2-Bis(2-hydroxy-5-biphenyl)l<br>propane</td><td>BisOPP-A</td><td>BPPH</td><td>380.49</td><td>24038-68-4</td><td>6.59</td><td>9.7</td><td>10.5</td><td>100%</td><td>6.77</td><td>6.39E-06</td></tr><tr><td>2,2',6,6'-Tetrachlorobisphenol A</td><td>TCBPA</td><td>TCBPA</td><td>366.06</td><td>79-95-8</td><td>6.19</td><td>7.7</td><td>8.50</td><td>65%</td><td>6.21</td><td>8.87E-06</td></tr></tbody></table>

Source and the detailed predictions for logK<sub>ow</sub> are given in the Supp.ninfo 3, Table SI-1

alternatives in the nematode *Caenorhabditis elegans* (C. elegans), an initial literature search was performed on the ZB MED Search Portal for Life Sciences LIVIVO. LIVIVO uses a semantic, index-based search engine and searches through library catalogues, publisher directories and other key life science databases such as MEDLINE (PubMed), AGRICOLA and AGRIS (https://www.livivo.de/app/misc/help/about, last accessed 16 Nov. 2023). The search was performed by combining the search terms “Caenorhabditis elegans” or “C. elegans”, “nematodes”, “bisphenol***” bisphenol a”, “BPA”, “BPA-alternative”, “BPA-analogues”, “BPA substitutes”, “BPE”, “BPS”, “BPF”, “BPZ”, “TBBPA”, “BPAP”, “BPAF”, “TCBPA”, “toxicity”, “neurotoxicity”, “reproduction” with the Boolean operators “AND” or “OR”. The LIVIVO search engine accounts automatically for synonyms, different word variations, abbreviations and translates key terms in multiple languages. The search results were automatically ranked by relevance (mainly according to frequency and position of search terms) and in a second step, manually prioritized based on the content of the abstracts. The total number of relevant hits

was > 50 and therefore a subsequent manual perusal of all publications manageable. Relevant data and information on in particular toxicity, biological effects, sensitivity of life stages, mechanisms of toxicity and exposure conditions were extracted and evaluated for the present review.

### 2.4.6. *Cnidaria studies*

The literature search for toxicity data of bisphenols and its alternatives to freshwater cnidarians was performed through the use of a sequence of words that were associated with Boolean operators. The following word sequence was used and applied to All Fields in Web of Knowledge: (“bisphenol***” OR “BPA alternative”) AND (“freshwater cnidaria” OR “hydrozoa” OR “hydroids” OR “hydra”).

### 2.5. *Studies with vertebrates*

To collect the available data regarding the biological activity of BPA
<caption>**Table 2**</caption>

Chemical identifiers and physicochemical properties of the BPA alternatives. Octanol-water partition constant of the neutral species, logK<sub>ow</sub>; acidity constant pK<sub>a</sub>. Thereof derived speciation and liposome-water distribution ratios logD<sub>lipw</sub>(pH 7.4). IC<sub>10,baseline</sub> predicted with the baseline toxicity QSAR from Lee et al. 2021 (Lee et al., 2021).

<table><thead><tr><th>IUPAC-Name</th><th>Abbreviation</th><th>Short<br>abbreviation</th><th>MW (g/<br>mol)</th><th>CASRN</th><th>logK<sub>ow</sub><br>[L/L]</th><th>pK<sub>a</sub><br>(acid)</th><th>pK<sub>a</sub><br>(acid)</th><th>Fraction<br>neutral species<br>(pH 7.4)</th><th>log D<sub>lipw</sub><br>(pH 7.4)</th><th>IC<sub>10,<br>baseline</sub><br>(M)</th></tr></thead><tbody><tr><td>4,4'-Sulfonyldiphenol</td><td>Bisphenol S</td><td>BPS</td><td>250.27</td><td>80-09-1</td><td>1.30</td><td>7.26</td><td>7.92</td><td>36%</td><td>1.05</td><td>4.74E-03</td></tr><tr><td>2,2,4,4-Tetramethyl-1,3-<br>cyclobutanediol (racemate)</td><td>r-TMCD</td><td>rTMCD</td><td>144.21</td><td>3010-96-6</td><td>1.30</td><td>15.4</td><td>-</td><td>100%</td><td>1.43</td><td>2.21E-03</td></tr><tr><td>cis-2,2,4,4-Tetramethyl-1,3-<br>cyclobutanediol</td><td>c-TMCD</td><td>cTMCD</td><td>144.21</td><td>3039-96-1</td><td>1.30</td><td>15.4</td><td>-</td><td>100%</td><td>1.43</td><td>2.21E-03</td></tr><tr><td>2,4'-Dihydroxydiphenyl sulfone</td><td>2,4-BPS</td><td>24BPS</td><td>250.27</td><td>5397-34-2</td><td>1.42</td><td>7.9</td><td>9.1</td><td>76%</td><td>1.44</td><td>2.17E-03</td></tr><tr><td>Benzyl 4-hydroxybenzoate</td><td>Benzylparaben</td><td>BzPB</td><td>228.25</td><td>94-18-8</td><td>3.56</td><td>8.5</td><td>-</td><td>93%</td><td>3.69</td><td>7.63E-05</td></tr><tr><td>4-[[4-(Allyloxy)phenyl]sulfonyl]<br>phenol</td><td>BPS-MAE</td><td>BPS-MAE</td><td>290.33</td><td>97042-18-7</td><td>2.92</td><td>8</td><td>-</td><td>80%</td><td>2.98</td><td>1.81E-04</td></tr><tr><td>N-(p-toluenesulfonyl)-N'-[3-(p-<br>toluenesulfonyloxy)phenyl]urea</td><td>Pergafast 201</td><td>Pergafast</td><td>460.52</td><td>232938-43-1</td><td>4.19</td><td>3.70</td><td>-</td><td>0%</td><td>3.35</td><td>1.13E-04</td></tr><tr><td>4-((4-Isopropoxyphenyl)sulfonyl)<br>phenol</td><td>D-8</td><td>D8</td><td>292.35</td><td>95235-30-6</td><td>2.96</td><td>8.00</td><td>-</td><td>80%</td><td>3.02</td><td>1.73E-04</td></tr><tr><td>Bis(4-hydroxyphenyl)methane</td><td>Bisphenol F</td><td>BPF</td><td>200.23</td><td>620-92-8</td><td>2.91</td><td>9.7</td><td>10.50</td><td>100%</td><td>3.06</td><td>1.64E-04</td></tr><tr><td>4-[4-(benzyloxy)benzenesulfonyl]<br>phenol</td><td>BPS-MPE</td><td>BPS-MPE</td><td>340.39</td><td>63134-33-8</td><td>4.18</td><td>6.3</td><td>-</td><td>7%</td><td>3.56</td><td>8.82E-05</td></tr><tr><td>1,1-Bis(4-hydroxyphenyl)ethane</td><td>Bisphenol E</td><td>BPE</td><td>214.26</td><td>2081-08-5</td><td>3.12</td><td>9.7</td><td>10.50</td><td>100%</td><td>3.27</td><td>1.25E-04</td></tr><tr><td>4,4'-Bis(p-tolylsulfonylureido)<br>diphenylmethane</td><td>BTUM</td><td>BTUM</td><td>592.69</td><td>151882-81-4</td><td>5.21</td><td>3.90</td><td>4.60</td><td>0%</td><td>4.38</td><td>3.69E-05</td></tr><tr><td>4,4'-Thiodiphenol</td><td>BPT</td><td>BPT</td><td>218.27</td><td>2664-63-3</td><td>3.34</td><td>9.7</td><td>10.50</td><td>100%</td><td>3.49</td><td>9.56E-05</td></tr><tr><td>5,5-Dimethyl-3,7-dioxa-1,9(2)-bis<br>(oxidirna)-4,6(2,4)-<br>dibenzenanonaphane</td><td>BADGE</td><td>BADGE</td><td>340.42</td><td>1675-54-3</td><td>3.71</td><td>-</td><td>-</td><td>100%</td><td>3.86</td><td>6.28E-05</td></tr><tr><td>Benzeneacetic acid, 4-hydroxy-<br>alpha-(4-hydroxyphenyl)-, methyl<br>ester</td><td>Bz</td><td>Bz</td><td>258.27</td><td>5129-00-0</td><td>2.73</td><td>9.3</td><td>10.10</td><td>99%</td><td>2.87</td><td>2.11E-04</td></tr><tr><td>4,4'-(Propane-2,2-diyl)diphenol</td><td>Bisphenol A</td><td>BPA</td><td>228.29</td><td>80-05-7</td><td>3.32</td><td>9.7</td><td>10.5</td><td>100%</td><td>3.65</td><td>7.95E-05</td></tr><tr><td>4,4'-(1-Phenylethylidene)bisphenol</td><td>Bisphenol AP</td><td>BPAP</td><td>290.36</td><td>1571-75-1</td><td>4.43</td><td>9.70</td><td>10.50</td><td>100%</td><td>4.59</td><td>3.04E-05</td></tr><tr><td>4,4'-(Butane-2,2-diyl)diphenol</td><td>Bisphenol B</td><td>BPB</td><td>242.32</td><td>77-40-7</td><td>3.95</td><td>9.7</td><td>10.50</td><td>100%</td><td>4.10</td><td>4.87E-05</td></tr><tr><td>3,3'-Dimethylbisphenol A</td><td>Bisphenol C</td><td>BPC</td><td>256.35</td><td>79-97-0</td><td>4.32</td><td>9.7</td><td>10.5</td><td>100%</td><td>4.48</td><td>3.35E-05</td></tr><tr><td>4,4'-(1,1,1,3,3,3-<br>Hexafluoropropane-2,2-diyl)<br>diphenol</td><td>Bisphenol AF</td><td>BPAF</td><td>336.23</td><td>1478-61-1</td><td>3.70</td><td>8.7</td><td>9.50</td><td>95%</td><td>3.83</td><td>6.48E-05</td></tr><tr><td>1,1'-Bis(4-hydroxyphenyl)<br>cyclohexane</td><td>Bisphenol Z</td><td>BPZ</td><td>268.36</td><td>843-55-0</td><td>4.54</td><td>9.7</td><td>10.50</td><td>100%</td><td>4.70</td><td>2.74E-05</td></tr><tr><td>4,4'-[1,4-Phenylenebis(1-<br>methylethylidene)] bis-phenol</td><td>Bisphenol P</td><td>BPP</td><td>346.47</td><td>2167-51-3</td><td>6.10</td><td>9.7</td><td>10.30</td><td>100%</td><td>6.28</td><td>8.50E-06</td></tr><tr><td>2,2-Bis(4-hydroxy-3-<br>isopropylphenyl)propane</td><td>Bisphenol G</td><td>BPG</td><td>312.45</td><td>127-54-8</td><td>6.04</td><td>10.5</td><td>11.3</td><td>100%</td><td>6.22</td><td>8.79E-06</td></tr><tr><td>3,3',5,5'-Tetrabromobisphenol A</td><td>TBBPA</td><td>TBBPA</td><td>543.88</td><td>79-94-7</td><td>6.99</td><td>7.7</td><td>8.50</td><td>65%</td><td>7.01</td><td>5.62E-06</td></tr><tr><td>2,2-Bis(2-hydroxy-5-biphenyl)l<br>propane</td><td>BisOPP-A</td><td>BPPH</td><td>380.49</td><td>24038-68-4</td><td>6.59</td><td>9.7</td><td>10.5</td><td>100%</td><td>6.77</td><td>6.39E-06</td></tr><tr><td>2,2',6,6'-Tetrachlorobisphenol A</td><td>TCBPA</td><td>TCBPA</td><td>366.06</td><td>79-95-8</td><td>6.19</td><td>7.7</td><td>8.50</td><td>65%</td><td>6.21</td><td>8.87E-06</td></tr></tbody></table>

Source and the detailed predictions for logK<sub>ow</sub> are given in the Supp.ninfo 3, Table SI-1

alternatives in the nematode *Caenorhabditis elegans* (C. elegans), an initial literature search was performed on the ZB MED Search Portal for Life Sciences LIVIVO. LIVIVO uses a semantic, index-based search engine and searches through library catalogues, publisher directories and other key life science databases such as MEDLINE (PubMed), AGRICOLA and AGRIS (https://www.livivo.de/app/misc/help/about, last accessed 16 Nov. 2023). The search was performed by combining the search terms “Caenorhabditis elegans” or “C. elegans”, “nematodes”, “bisphenol*” bisphenol a”, “BPA”, “BPA-alternative”, “BPA-analogues”, “BPA substitutes”, “BPE”, “BPS”, “BPF”, “BPZ”, “TBBPA”, “BPAP”, “BPAF”, “TCBPA”, “toxicity”, “neurotoxicity”, “reproduction” with the Boolean operators “AND” or “OR”. The LIVIVO search engine accounts automatically for synonyms, different word variations, abbreviations and translates key terms in multiple languages. The search results were automatically ranked by relevance (mainly according to frequency and position of search terms) and in a second step, manually prioritized based on the content of the abstracts. The total number of relevant hits

was > 50 and therefore a subsequent manual perusal of all publications manageable. Relevant data and information on in particular toxicity, biological effects, sensitivity of life stages, mechanisms of toxicity and exposure conditions were extracted and evaluated for the present review.

### 2.4.6. *Cnidaria studies*

The literature search for toxicity data of bisphenols and its alternatives to freshwater cnidarians was performed through the use of a sequence of words that were associated with Boolean operators. The following word sequence was used and applied to All Fields in Web of Knowledge: (“bisphenol*” OR “BPA alternative”) AND (“freshwater cnidaria” OR “hydrozoa” OR “hydroids” OR “hydra”).

### 2.5. *Studies with vertebrates*

To collect the available data regarding the biological activity of BPA
alternatives, we combined the following search strings joined by term "AND". For chemicals we searched for: i) general term bisphenol; ii) full chemical name (i.e. pergafast 201, bisphenol Z, bisphenol E, bisphenol P, bisphenol AP, bisphenol PH, bisphenol S, BPF); iii) their established abbreviations (i.e. BPZ, BPE, BPP, BPAP, BPPH BPS-MPE, BPS, BPPH, BADGE), or iv) their aliases (e.g. for BPS-MAE, we also searched for 4-((4-(Allyloxy)phenyl)sulfonyl) phenol, 4-(4-prop-2-enoxyphenyl)sulfonylphenol, 4-allyloxy-4'-hydroxy-diphenylsulfone)). Using the Web of Knowledge, we combined the chemical name with "fish" or "zebrafish" or "danio" or "amphibia" or "frog" or "xenopus". For specific endpoints, we also employed US EPA ECOTOX tool (https://cfpub.epa.gov/ecotox) (Olker et al., 2022), that is able to identify and visualize studies that focused on specific chemicals (bisphenols) and specific model organisms (e.g. fish models).

### 3. Occurrence of BPA alternatives in environmental compartments across Europe

In the last decades there have been growing concerns regarding the possible adverse effects of BPA to humans' and animals' health. These concerns, in addition to tight restrictions placed on BPA in many countries, have led to the development of alternative chemicals [e.g. bisphenol Z (BPZ), bisphenol E (BPE), bisphenol S-MAE (BPS-MAE), bisphenol P (BPP), bisphenol AP (BPAP), bisphenol B (BPB), bisphenol C (BPC), bisphenol S (BPS), bisphenol F (BPF), bisphenol AF (BPAF)]. As a result, these emerging environmental contaminants can now be found worldwide in various environmental compartments including water, sediment, sludge, soil, indoor dust and air. Furthermore, the use of BPA alternatives is expected to increase in the upcoming years due to proposals by EFSA and European Chemicals Agency (ECHA) to reduce the use of BPA and several other bisphenols with known adverse effects on humans and the environment.

Regarding their properties, most bisphenols are characterized as toxic (or very toxic) to aquatic organisms and have been shown to exhibit adverse effects on the endocrine, reproductive, metabolic and immune system in different species. Some of them are also persistent, mobile or bioaccumulative and are characterized as PBT/vPvB or PMT/vPvM. This information is summarized in a report regarding the "assessment of regulatory needs" published by ECHA in December 2021 (Echa, 2021).

Furthermore, considering the potential for widespread use of several bisphenols, the exposure of organisms to bisphenol mixtures in different environmental compartments (i.e., surface and sea water, sediment, soil) is very likely to occur. Therefore, in the frame of this review, data regarding the occurrence of bisphenol mixtures (BPA and other bisphenols) in the above-mentioned environmental compartments were collected in order to identify the most frequently co-occurring

bisphenols in the environment as well as their environmentally relevant concentrations.

#### 3.1. BPA alternatives in freshwater

The occurrence of BPA and BPA alternatives in water samples has been investigated in several studies. Specifically, BPA, BPB, BPE and BPS were identified at levels up to 4.42, 3.66, 2.77 and 9.13 µg/L, respectively (Caban and Stepnowski, 2020; Cunha et al., 2022; Russo et al., 2021; Liess et al., 2021.), while BPF, BPC, BPG, BPAF, BPM/BPP were identified at lower levels (up to 0.317, 0.012, 0.0209, 0.205, 0.06 µg/L, respectively) and BPZ, BPAP, BFDGE and TBBPA were not identified at detectable levels (Cunha et al., 2022; Ballesteros-Gómez et al., 2007; Fromme et al., 2002; Ruiz et al., 2007; Sauer et al., 2021; Ben Sghaier et al., 2017). In addition, exceptionally high BADGE levels (i.e., up to 28 µg/L) were identified in water samples collected from a lagoon in Campania in Southern Italy (Russo et al., 2021). The levels of BPA and its alternatives in European waters are summarized in Fig. 1 and Fig. 2, respectively. The detailed monitoring data retrieved by the identified studies are presented in the supplemental material S1.

#### 3.2. BPA alternatives in sediment

In contrast to the water column, the occurrence of BPA and BPA alternatives in sediment samples has been less investigated so far. In sediment samples, BPA was found at higher levels than all other detected bisphenols. BPA was detected in countries across Europe (Germany, Italy, Portugal and the UK) at levels up to 190 ng/g dw (Cunha et al., 2022; Russo et al., 2021; Fromme et al., 2002; Wilkinson et al., 2018). BPAF and BADGE were also detected at high levels (up to 155 and 61 ng/g dw respectively) in sediment samples collected from a lagoon in Campania in Southern Italy, while BPAF was also detected in samples collected from Portugal (Cunha et al., 2022; Russo et al., 2021). BPS, BPB and BPF were detected at significant levels in different countries (Portugal, UK, Italy and Germany), while other bisphenols such as BPZ, BPAP, BPE and BPP were not identified at detectable levels (Cunha et al., 2022; Russo et al., 2021; Fromme et al., 2002; Sauer et al., 2021; Wilkinson et al., 2018). The levels of BPA and its alternatives in sediment are summarized in Fig. 3. The detailed monitoring data retrieved by the identified studies are presented in the supplemental material S1.

#### 3.3. BPA alternatives in terrestrial ecosystems

Bisphenol based substances can occur in agricultural soils due to practices of soil amendment with biosolids or irrigation with wastewater. In agricultural soils, BPA concentrations range between 0.55 and 147 µg/kg dry weight (Careghini et al., 2015). Only a limited number of

<figure><img src="image_4.png" /><figcaption>**Fig. 1.** Overview of the concentration levels of BPA in European water samples (rivers, estuaries, lakes, ponds and retention tanks). The detailed monitoring data retrieved by the identified studies are presented in the supplemental material S1. Values of 0.00 imply concentrations below the detection limit (LOD).</figcaption></figure>
alternatives, we combined the following search strings joined by term "AND". For chemicals we searched for: i) general term bisphenol; ii) full chemical name (i.e. pergafast 201, bisphenol Z, bisphenol E, bisphenol P, bisphenol AP, bisphenol PH, bisphenol S, BPF); iii) their established abbreviations (i.e. BPZ, BPE, BPP, BPAP, BPPH BPS-MPE, BPS, BPPH, BADGE), or iv) their aliases (e.g. for BPS-MAE, we also searched for 4-((4-(Allyloxy)phenyl)sulfonyl) phenol, 4-(4-prop-2-enoxyphenyl)sulfonylphenol, 4-allyloxy-4'-hydroxy-diphenylsulfone)). Using the Web of Knowledge, we combined the chemical name with "fish" or "zebrafish" or "danio" or "amphibia" or "frog" or "xenopus". For specific endpoints, we also employed US EPA ECOTOX tool (https://cfpub.epa.gov/ecotox) (Olker et al., 2022), that is able to identify and visualize studies that focused on specific chemicals (bisphenols) and specific model organisms (e.g. fish models).

### 3. Occurrence of BPA alternatives in environmental compartments across Europe

In the last decades there have been growing concerns regarding the possible adverse effects of BPA to humans' and animals' health. These concerns, in addition to tight restrictions placed on BPA in many countries, have led to the development of alternative chemicals [e.g. bisphenol Z (BPZ), bisphenol E (BPE), bisphenol S-MAE (BPS-MAE), bisphenol P (BPP), bisphenol AP (BPAP), bisphenol B (BPB), bisphenol C (BPC), bisphenol S (BPS), bisphenol F (BPF), bisphenol AF (BPAF)]. As a result, these emerging environmental contaminants can now be found worldwide in various environmental compartments including water, sediment, sludge, soil, indoor dust and air. Furthermore, the use of BPA alternatives is expected to increase in the upcoming years due to proposals by EFSA and European Chemicals Agency (ECHA) to reduce the use of BPA and several other bisphenols with known adverse effects on humans and the environment.

Regarding their properties, most bisphenols are characterized as toxic (or very toxic) to aquatic organisms and have been shown to exhibit adverse effects on the endocrine, reproductive, metabolic and immune system in different species. Some of them are also persistent, mobile or bioaccumulative and are characterized as PBT/vPvB or PMT/vPvM. This information is summarized in a report regarding the "assessment of regulatory needs" published by ECHA in December 2021 (Echa, 2021).

Furthermore, considering the potential for widespread use of several bisphenols, the exposure of organisms to bisphenol mixtures in different environmental compartments (i.e., surface and sea water, sediment, soil) is very likely to occur. Therefore, in the frame of this review, data regarding the occurrence of bisphenol mixtures (BPA and other bisphenols) in the above-mentioned environmental compartments were collected in order to identify the most frequently co-occurring

bisphenols in the environment as well as their environmentally relevant concentrations.

#### 3.1. BPA alternatives in freshwater

The occurrence of BPA and BPA alternatives in water samples has been investigated in several studies. Specifically, BPA, BPB, BPE and BPS were identified at levels up to 4.42, 3.66, 2.77 and 9.13 µg/L, respectively (Caban and Stepnowski, 2020; Cunha et al., 2022; Russo et al., 2021; Liess et al., 2021.), while BPF, BPC, BPG, BPAF, BPM/BPP were identified at lower levels (up to 0.317, 0.012, 0.0209, 0.205, 0.06 µg/L, respectively) and BPZ, BPAP, BFDGE and TBBPA were not identified at detectable levels (Cunha et al., 2022; Ballesteros-Gómez et al., 2007; Fromme et al., 2002; Ruiz et al., 2007; Sauer et al., 2021; Ben Sghaier et al., 2017). In addition, exceptionally high BADGE levels (i.e., up to 28 µg/L) were identified in water samples collected from a lagoon in Campania in Southern Italy (Russo et al., 2021). The levels of BPA and its alternatives in European waters are summarized in Fig. 1 and Fig. 2, respectively. The detailed monitoring data retrieved by the identified studies are presented in the supplemental material S1.

#### 3.2. BPA alternatives in sediment

In contrast to the water column, the occurrence of BPA and BPA alternatives in sediment samples has been less investigated so far. In sediment samples, BPA was found at higher levels than all other detected bisphenols. BPA was detected in countries across Europe (Germany, Italy, Portugal and the UK) at levels up to 190 ng/g dw (Cunha et al., 2022; Russo et al., 2021; Fromme et al., 2002; Wilkinson et al., 2018). BPAF and BADGE were also detected at high levels (up to 155 and 61 ng/g dw respectively) in sediment samples collected from a lagoon in Campania in Southern Italy, while BPAF was also detected in samples collected from Portugal (Cunha et al., 2022; Russo et al., 2021). BPS, BPB and BPF were detected at significant levels in different countries (Portugal, UK, Italy and Germany), while other bisphenols such as BPZ, BPAP, BPE and BPP were not identified at detectable levels (Cunha et al., 2022; Russo et al., 2021; Fromme et al., 2002; Sauer et al., 2021; Wilkinson et al., 2018). The levels of BPA and its alternatives in sediment are summarized in Fig. 3. The detailed monitoring data retrieved by the identified studies are presented in the supplemental material S1.

#### 3.3. BPA alternatives in terrestrial ecosystems

Bisphenol based substances can occur in agricultural soils due to practices of soil amendment with biosolids or irrigation with wastewater. In agricultural soils, BPA concentrations range between 0.55 and 147 µg/kg dry weight (Careghini et al., 2015). Only a limited number of

<figure><img src="image_4.png" /><figcaption>**Fig. 1.** Overview of the concentration levels of BPA in European water samples (rivers, estuaries, lakes, ponds and retention tanks). The detailed monitoring data retrieved by the identified studies are presented in the supplemental material S1. Values of 0.00 imply concentrations below the detection limit (LOD).</figcaption></figure>
<figure><img src="image_5.png" /><figcaption>**Fig. 2.** Overview of the concentration levels of bisphenols (other than BPA) in European water samples (rivers, estuaries and lakes). The detailed monitoring data retrieved by the identified studies are presented in the supplemental material S1. Values of 0.00 imply concentrations below 0.004 µg/L.</figcaption></figure>

<figure><img src="image_6.png" /><figcaption>**Fig. 3.** Overview of the concentration levels of BPA and its alternatives in the sediment samples across Europe. The detailed monitoring data retrieved by the identified studies are presented in the supplemental material S1. Values of 0.00 imply concentrations below the detection limit (LOD).</figcaption></figure>

studies have investigated levels of BPA alternatives in terrestrial samples. So far, one unique study has been identified reporting the analysis of various bisphenols in environmental samples from soil (Pérez et al., 2017). This study was conducted in Spain and a comparison of the levels of bisphenols identified in soil samples from agricultural and industrial areas was carried out. The results revealed that only BPA and BPF were identified at levels 17.2–126.2 and 4.8–127.2 ng/d dw, respectively, in soil samples from industrial areas, and 1.1–55.9 and up to 15.3 ng/d dw in soil samples from agricultural areas (see supplementary material S1). All other analyzed bisphenols (BPB, BPP, BPS, BPZ, BPAF, BPAB) were not found at detectable levels.

### 3.4. Conclusion

BPA and BPA alternatives are ubiquitous chemicals found in all studied environmental compartments. Although BPA is currently regulated and its use is restricted in many products, its levels continue to dominate in comparison with its alternatives in environmental samples of water and sediment. The broad use of BPA and its alternatives in consumer products has led to its widespread distribution in aquatic and terrestrial ecosystems, where it can accumulate and persist for extended periods. Similar to BPA, its alternatives have been detected in environmental samples, raising questions about their potential health and ecological impacts. Therefore, the future monitoring and surveillance of water, sediment and soil quality should be enhanced to include

measurements of BPA alternatives to monitor their levels and ensure development of timely mitigation strategies. The fact that only a limited number of monitoring studies for bisphenols other than BPA were identified to be conducted in Europe, even though their use is constantly increasing as they are used as alternatives to BPA, reinforce the need for further and extended monitoring activities in different environmental compartments. Finally, further study is needed in order to investigate the possible adverse effects of bisphenols on organisms belonging in different taxa when they will be exposed to environmentally relevant concentrations (as revealed by monitoring studies) of mixtures of bisphenols. The results of this “retrospective risk assessment” could be exploited to highlight the possible need for mitigation strategies at European level.

Considering the different emissions of bisphenols, from dental treatment, pesticides, thermal papers, food containers, lacquers or paints, their co-occurrence with analogues or other substances is likely, leading to several challenges regarding waste treatment, fate into environmental compartments and consequent effects.

### 4. Predictive models, and bioactivity of BPA alternatives

Understanding the toxicity of BPA and its alternatives is of paramount importance due to their widespread use and presence in the environment. The ecotoxicity of BPA alternatives has become a subject of increasing concern. As these alternatives, such as BPS and BPF, are
<figure><img src="image_5.png" /><figcaption>**Fig. 2.** Overview of the concentration levels of bisphenols (other than BPA) in European water samples (rivers, estuaries and lakes). The detailed monitoring data retrieved by the identified studies are presented in the supplemental material S1. Values of 0.00 imply concentrations below 0.004 µg/L.</figcaption></figure>

<figure><img src="image_6.png" /><figcaption>**Fig. 3.** Overview of the concentration levels of BPA and its alternatives in the sediment samples across Europe. The detailed monitoring data retrieved by the identified studies are presented in the supplemental material S1. Values of 0.00 imply concentrations below the detection limit (LOD).</figcaption></figure>

studies have investigated levels of BPA alternatives in terrestrial samples. So far, one unique study has been identified reporting the analysis of various bisphenols in environmental samples from soil (Pérez et al., 2017). This study was conducted in Spain and a comparison of the levels of bisphenols identified in soil samples from agricultural and industrial areas was carried out. The results revealed that only BPA and BPF were identified at levels 17.2–126.2 and 4.8–127.2 ng/d dw, respectively, in soil samples from industrial areas, and 1.1–55.9 and up to 15.3 ng/d dw in soil samples from agricultural areas (see supplementary material S1). All other analyzed bisphenols (BPB, BPP, BPS, BPZ, BPAF, BPAB) were not found at detectable levels.

### 3.4. Conclusion

BPA and BPA alternatives are ubiquitous chemicals found in all studied environmental compartments. Although BPA is currently regulated and its use is restricted in many products, its levels continue to dominate in comparison with its alternatives in environmental samples of water and sediment. The broad use of BPA and its alternatives in consumer products has led to its widespread distribution in aquatic and terrestrial ecosystems, where it can accumulate and persist for extended periods. Similar to BPA, its alternatives have been detected in environmental samples, raising questions about their potential health and ecological impacts. Therefore, the future monitoring and surveillance of water, sediment and soil quality should be enhanced to include

measurements of BPA alternatives to monitor their levels and ensure development of timely mitigation strategies. The fact that only a limited number of monitoring studies for bisphenols other than BPA were identified to be conducted in Europe, even though their use is constantly increasing as they are used as alternatives to BPA, reinforce the need for further and extended monitoring activities in different environmental compartments. Finally, further study is needed in order to investigate the possible adverse effects of bisphenols on organisms belonging in different taxa when they will be exposed to environmentally relevant concentrations (as revealed by monitoring studies) of mixtures of bisphenols. The results of this “retrospective risk assessment” could be exploited to highlight the possible need for mitigation strategies at European level.

Considering the different emissions of bisphenols, from dental treatment, pesticides, thermal papers, food containers, lacquers or paints, their co-occurrence with analogues or other substances is likely, leading to several challenges regarding waste treatment, fate into environmental compartments and consequent effects.

### 4. Predictive models, and bioactivity of BPA alternatives

Understanding the toxicity of BPA and its alternatives is of paramount importance due to their widespread use and presence in the environment. The ecotoxicity of BPA alternatives has become a subject of increasing concern. As these alternatives, such as BPS and BPF, are
being widely used as replacements for BPA, it is crucial to assess their potential impact on the environment. Ecotoxicity studies aim to evaluate the effects of these alternatives on organisms, including both the in-vertebrates and vertebrates. Understanding the ecotoxicity of BPA alternatives is essential for identifying any potential risks they may pose to aquatic life, ecological balance, and overall environmental health. It provides valuable insights for regulators, policymakers, and manufacturers to make informed decisions that prioritize the development and use of safer alternatives, ultimately safeguarding our ecosystems and biodiversity. With respect to priorities in PARC, collected information regarding the bioactivity of BPA alternatives will form a basis for selection of suitable BPA alternatives that will serve as model chemicals for development of new approach methodologies (NAMs). With respect to NAMs, in silico approaches have emerged as valuable tools in the evaluation of ecotoxicity, offering efficient and cost-effective tools for predicting and assessing the potential ecological impact of chemicals. By utilizing computer models and algorithms, in silico approaches enable the analysis of large chemical datasets, predicting various ecotoxicological endpoints, such as toxicity to aquatic organisms or bio-accumulation potential. These methods leverage available data on chemical structure, physicochemical properties, and biological activity to generate predictive models and provide valuable insights into the potential hazards of chemicals. Within this chapter, we have provided a

comprehensive summary of the current advancements in both *in silico* approaches and *in vivo* models utilized for screening, prioritization, and toxicological evaluation of these chemicals.

## 4.1. The role of physicochemical properties for the toxicity analysis of BPA alternatives

The hydrophobicity of BPA alternatives expressed as $logK_{ow}$ of the neutral species ranges from $1.3 < logK_{ow} < 7.15$ (Fig. 4a) and covers almost six orders of magnitude. BPA itself has an experimental $logK_{ow}$ of 3.32, which is very close to the median of the distribution of 3.64. Few experimental $logK_{ow}$ values were available for the BPA alternatives. The common prediction models (ACD, OPERA, Episuite) yielded estimates that varied up to two orders of magnitude magnitude (Supp.info 3, Table SI-1). In Table 2 and Fig. 4a the mean of the predictions was included as no preference could be given to any of the prediction models. As hydrophobicity is one main driver of toxicity, it is vital that more reliable $logK_{ow}$ become available, ideally experimental values.

BPA is a diprotic acid due to the two phenolic groups with $pK_a$-values of 9.7 and 10.5, which means that BPA is present in its neutral form at pH 7.4 ($α_{neutral}$ (pH 7.4) = 1), which is the pH in standard cell assays. BPS is much more acidic due to the sulfonyl group and is 49% negatively charged at pH 7.4 and 15% is even double negatively charged (Table 2).

<figure><img src="image_7.png" /><figcaption>**Fig. 4.** The main physicochemical properties of BPA alternatives: (a) Octanol-water partition constant of the neutral species $logK_{ow}$ plotted against the acidity constants $pK_a$; (b) Baseline toxicity QSAR for generic cell lines (Lee et al., 2021) and predictions of baseline cytotoxicity inhibitory concentrations $IC_{10}$ baseline for all BPA alternatives (Table 2); (c) Experimental $EC_{10}$ for BPA and three exemplary BPA alternatives in the Tox21 cell-based bioassays (data in Supp.info 3, Table S2). (d) Specificity ratios $SR_{baseline}$ calculated from the $IC_{10, baseline}$ (Supp. info, Table S3) and the $EC_{10}$ in Fig. 4c (data in Supp. info 3, Table S3).</figcaption></figure>
being widely used as replacements for BPA, it is crucial to assess their potential impact on the environment. Ecotoxicity studies aim to evaluate the effects of these alternatives on organisms, including both the in-vertebrates and vertebrates. Understanding the ecotoxicity of BPA alternatives is essential for identifying any potential risks they may pose to aquatic life, ecological balance, and overall environmental health. It provides valuable insights for regulators, policymakers, and manufacturers to make informed decisions that prioritize the development and use of safer alternatives, ultimately safeguarding our ecosystems and biodiversity. With respect to priorities in PARC, collected information regarding the bioactivity of BPA alternatives will form a basis for selection of suitable BPA alternatives that will serve as model chemicals for development of new approach methodologies (NAMs). With respect to NAMs, in silico approaches have emerged as valuable tools in the evaluation of ecotoxicity, offering efficient and cost-effective tools for predicting and assessing the potential ecological impact of chemicals. By utilizing computer models and algorithms, in silico approaches enable the analysis of large chemical datasets, predicting various ecotoxicological endpoints, such as toxicity to aquatic organisms or bio-accumulation potential. These methods leverage available data on chemical structure, physicochemical properties, and biological activity to generate predictive models and provide valuable insights into the potential hazards of chemicals. Within this chapter, we have provided a

comprehensive summary of the current advancements in both *in silico* approaches and *in vivo* models utilized for screening, prioritization, and toxicological evaluation of these chemicals.

## 4.1. The role of physicochemical properties for the toxicity analysis of BPA alternatives

The hydrophobicity of BPA alternatives expressed as $logK_{ow}$ of the neutral species ranges from $1.3 < logK_{ow} < 7.15$ (Fig. 4a) and covers almost six orders of magnitude. BPA itself has an experimental $logK_{ow}$ of 3.32, which is very close to the median of the distribution of 3.64. Few experimental $logK_{ow}$ values were available for the BPA alternatives. The common prediction models (ACD, OPERA, Episuite) yielded estimates that varied up to two orders of magnitude magnitude (Supp.info 3, Table SI-1). In Table 2 and Fig. 4a the mean of the predictions was included as no preference could be given to any of the prediction models. As hydrophobicity is one main driver of toxicity, it is vital that more reliable $logK_{ow}$ become available, ideally experimental values.

BPA is a diprotic acid due to the two phenolic groups with $pK_a$-values of 9.7 and 10.5, which means that BPA is present in its neutral form at pH 7.4 ($α_{neutral}$ (pH 7.4) = 1), which is the pH in standard cell assays. BPS is much more acidic due to the sulfonyl group and is 49% negatively charged at pH 7.4 and 15% is even double negatively charged (Table 2).

<figure><img src="image_7.png" /><figcaption>**Fig. 4.** The main physicochemical properties of BPA alternatives: (a) Octanol-water partition constant of the neutral species $logK_{ow}$ plotted against the acidity constants $pK_a$; (b) Baseline toxicity QSAR for generic cell lines (Lee et al., 2021) and predictions of baseline cytotoxicity inhibitory concentrations $IC_{10}$ baseline for all BPA alternatives (Table 2); (c) Experimental $EC_{10}$ for BPA and three exemplary BPA alternatives in the Tox21 cell-based bioassays (data in Supp.info 3, Table S2). (d) Specificity ratios $SR_{baseline}$ calculated from the $IC_{10, baseline}$ (Supp. info, Table S3) and the $EC_{10}$ in Fig. 4c (data in Supp. info 3, Table S3).</figcaption></figure>
TCBPA and TBBPA have similar speciation but are located at the other end of the hydrophobicity scale (logKow 6.19 and 6.99 (Fig. 4)). Most of the BPA alternatives have one or two phenolic groups but almost none are deprotonated at pH 7.4. In some cases, the phenols are substituted by ethers (e.g., BADGE, Table 1), and these alternatives are also neutral. BTUM is a special case as it does not contain any phenolic groups but two sulfonamide groups, which are N-acidic groups, with pKa-values of 4.9 and 4.6, which means that BTUM is double deprotonated and anionic at pH 7.4 (Table 1). BPS-MPE has only one phenolic group but has a higher acidity of this phenolic group (lower pKa) due to the electron-withdrawal from the sulfonyl group and is therefore almost completely anionic (α<sub>anion</sub> (pH 7.4) = 0.93).

In summary, both, the logK<sub>ow</sub> and pK<sub>a</sub> values of the BPA alternatives vary over 6 to 10 log-units (Fig. 4a), which means that already based on the physicochemical properties we can expect a high diversity in environmental fate and toxicity. This does not even consider the stability of the BPA alternatives, which in addition needs to be considered.

## 4.2. Prediction of baseline toxicity of BPA alternatives

As many BPA alternatives are deprotonated, their affinity to biological membranes is not directly correlated to the logK<sub>ow</sub>. Baseline toxicity prediction models for partially or fully charged chemicals have typically the affinity to biological membranes expressed as logD<sub>lipw</sub> as hydrophobicity descriptor (Escher et al., 2020). Fig. 4b depicts a generic baseline toxicity model for human cell assays (eq. (4)) developed by Lee et al. 2021 (Lee et al., 2021). The predicted baseline cytotoxicity IC10, baseline ranged from 5.6 µM for TBBPA to 2.2 mM for BPS (Table 2). BPA and BPC lie in the middle with IC<sub>10, baseline</sub> of 79 and 34 µM, respectively. Overall, the potency predicted with IC<sub>10, baseline</sub> already ranges by a factor of 386 between BPA and its alternatives.

## 4.3. *In vitro* cell-based bioassays for mode-of-action analysis

Experimental reporter gene assays data from Tox21 were available for BPA and 15 BPA alternatives (Table S2). The distribution of experimental effect data is depicted in Fig. 1c on the example of BPS, BPA, BPC and TCBPA. On first view, BPS, TCBPA, BPA and BPC appear having similar potency in the micromolar effect concentration range (Fig. 1c), but if the EC<sub>10</sub> are compared to the associated predicted baseline toxicity (SR<sub>baseline</sub>) distinct differences become apparent (Fig. 1d).

The SR<sub>baseline</sub> (Fig. 1d) is clearly highest for both, BPA and BPS. BPA was tested highly specific in bioassays indicative of the activation of the estrogen receptor (ER) with SR<sub>baseline</sub> up to 2300. Despite its lower overall potency, the SR<sub>baseline</sub> of BPS was up to 4 times higher than of BPA. This means that with respect to its intrinsic effect BPS is rather similar to BPA even if estrogen-specific effects are only triggered at higher nominal concentrations due to the lower hydrophobicity of BPS. This conclusion needs to be treated with certain caution due to the high variability of hydrophobicity prediction models for BPS. A SR of 10 represents the threshold between specific and highly specific effects Fig. 4d (Escher et al., 2020). A compound activating a response below 10 is considered behaving as baseline toxicant. TCBPA is of similar potency expressed as EC<sub>10</sub> as BPA Fig. 4c), however, it has a SR<sub>baseline</sub> below 10 in most assays in our dataset. Therefore, we can conclude it is acting like a baseline toxicant meaning that TCBPA activates the ER but at concentrations where nonspecific toxicity occurs.

The black filled circles in Fig. 4d are endpoints related to activation of the ER or indirect effects on ER. ER-related endpoints are most active with highest SR<sub>baseline</sub> for BPA and BPS but are at SR<sub>baseline</sub> < 10 for TCBPA and BPC. The TOX21_ERa_LUC VM7 assay (formerly called TOX21_ERa_LUC BG1, (Brennan et al., 2016) was identified as the most sensitive estrogen receptor reporter gene assay (Dreier et al., 2015) and is highlighted in Fig. 4c and d with a cross through the circle. It is indeed also one of the most sensitive assays for BPA alternatives with exception of the TCBPA, which confirms that the bulky TCBPA is a poor activator

of ER, which had already been shown previously (Pelch et al., 2019). The activation of nuclear receptors with SR<sub>baseline</sub> close to 1 is likely to be an artifact and caused by the cytotoxicity burst. The term "cytotoxicity burst" describes the phenomenon of enhanced non- specific activation of stress responses and even nuclear receptor binding that occur close to cell death (Escher et al., 2020; Judson et al., 2016; Fay et al., 2018).

It is somewhat puzzling on first sight that also ER antagonism seems to play a role at rather low concentration (Fig. 4c). However, the SR<sub>baseline</sub> analysis clearly indicates that this effect is not specific and is likely to also be an artifact of the cytotoxicity burst (Fig. 4d). With this knowledge in mind, we can interpret the effect data in the *in vitro* assays from a different viewpoint: Specific effects matter more if they have a SR<sub>baseline</sub> > 10. Apart from the large number of estrogenicity assays with SR<sub>baseline</sub> > 10, the antagonistic mode of androgen receptor (AR) assays were also active with SR<sub>baseline</sub> of 33 for BPA, 39 for BPC and 128 for BPS. Activation of ER is commonly accompanied by antagonism of AR (Pelch et al., 2019).

The vitamin D receptor (assay ATG_VDRE_CIS_up) was activated with a SR<sub>baseline</sub> of 22 by BPA, 8 by BPC and 5625 by BPS. The pregnane X receptor (PXR) and constitutive androstane receptor (CAR), both of which are regulators of xenobiotic metabolism, were also activated by BPA but not by any other BPA alternatives. Most notably, the TOX21_MMP assays (MMP stands for mitochondrial membrane potential, (Attene-Ramos et al., 2013) also captured the specific mitochondrial toxicity of BPA alternatives. BPA is known to exert mitochondrial toxicity (Khan et al., 2016), and the SR<sub>baseline</sub> of 60 by BPA, 56 by TCBPA and 15 by BPC (Supp.info 3, Table SI-3) indicate that these analogs are also mitochondrial toxicants, while BPS was not active in TOX21_MMP (Supp.info 3, Table SI-2).

For the analysis in Fig. 4c and 4d we just selected BPA and 3 of the 15 BPA alternatives, where we found data for *in vitro* bioassays to illustrate important differences. An overview about the analysis of the effects of all BPA alternatives in *in vitro* reporter gene assays is given in the Supplementary information.

Cytotoxicity data is rather scarce in the *in vitro* database and available only for 14 compounds and fewer assays (Supp. info 2, Fig.SI-2). Of the reported IC<sub>10</sub> for cytotoxicity, BPS-MPE and TBBPA have the highest TR > 1000 and BCP, BPAB, BzPB, BPA, BPZ, BPPH, TCBPA and BPAF were mere baseline toxicants with TR < 10 (Supp. info 2, Fig.SI-2). Only for three chemicals (BPZ, BPPH, BPC), both receptor-activation and cytotoxicity were available. Therefore, no direct comparison was possible for the larger chemical set, and we analyzed cytotoxicity (Supp. info 2, Fig. SI-2) and reporter gene activation (Supp. info 2, Fig. SI-3) independently.

BPA was one of the most active chemicals (but also one that was tested in most bioassays) but the SR<sub>baseline</sub> was in most assays higher for BPS than BPA. Some alternatives, especially the hydrophobic ones (BPPH, TCBPA, BPS-MPE) often had lower SR<sub>baseline</sub>, despite overall rather high potency. This analysis clearly demonstrated the importance to evaluate not only the absolute potency differences but consider the potency also in relation to the degree (SR<sub>baseline</sub>) and type of specificity (affected endpoint). To differentiate between specific and non-specific effects is vital for risk assessment (Fay et al., 2018) because non-specific effects will occur for all endpoints, albeit at high nominal concentrations and can be confidently predicted by baseline toxicity models across cells but also all across aquatic species. To know which specific effects are relevant is also important. BPA and many of its alternatives are estrogenic but we also find other relevant endpoints related to xenobiotic metabolism and mitochondrial toxicity, which can guide ecotoxicity testing.

## 4.4. Predictive models for ecotoxicity of bisphenols alternatives

Two phases can be distinguished in the dose-response relationship of a chemical in an organism: the toxicokinetic (TK), that is the fate of the
TCBPA and TBBPA have similar speciation but are located at the other end of the hydrophobicity scale (logKow 6.19 and 6.99 (Fig. 4)). Most of the BPA alternatives have one or two phenolic groups but almost none are deprotonated at pH 7.4. In some cases, the phenols are substituted by ethers (e.g., BADGE, Table 1), and these alternatives are also neutral. BTUM is a special case as it does not contain any phenolic groups but two sulfonamide groups, which are N-acidic groups, with pKa-values of 4.9 and 4.6, which means that BTUM is double deprotonated and anionic at pH 7.4 (Table 1). BPS-MPE has only one phenolic group but has a higher acidity of this phenolic group (lower pKa) due to the electron-withdrawal from the sulfonyl group and is therefore almost completely anionic (α<sub>anion</sub> (pH 7.4) = 0.93).

In summary, both, the logK<sub>ow</sub> and pK<sub>a</sub> values of the BPA alternatives vary over 6 to 10 log-units (Fig. 4a), which means that already based on the physicochemical properties we can expect a high diversity in environmental fate and toxicity. This does not even consider the stability of the BPA alternatives, which in addition needs to be considered.

## 4.2. Prediction of baseline toxicity of BPA alternatives

As many BPA alternatives are deprotonated, their affinity to biological membranes is not directly correlated to the logK<sub>ow</sub>. Baseline toxicity prediction models for partially or fully charged chemicals have typically the affinity to biological membranes expressed as logD<sub>lipw</sub> as hydrophobicity descriptor (Escher et al., 2020). Fig. 4b depicts a generic baseline toxicity model for human cell assays (eq. (4)) developed by Lee et al. 2021 (Lee et al., 2021). The predicted baseline cytotoxicity IC10, baseline ranged from 5.6 µM for TBBPA to 2.2 mM for BPS (Table 2). BPA and BPC lie in the middle with IC<sub>10, baseline</sub> of 79 and 34 µM, respectively. Overall, the potency predicted with IC<sub>10, baseline</sub> already ranges by a factor of 386 between BPA and its alternatives.

## 4.3. *In vitro* cell-based bioassays for mode-of-action analysis

Experimental reporter gene assays data from Tox21 were available for BPA and 15 BPA alternatives (Table S2). The distribution of experimental effect data is depicted in Fig. 1c on the example of BPS, BPA, BPC and TCBPA. On first view, BPS, TCBPA, BPA and BPC appear having similar potency in the micromolar effect concentration range (Fig. 1c), but if the EC<sub>10</sub> are compared to the associated predicted baseline toxicity (SR<sub>baseline</sub>) distinct differences become apparent (Fig. 1d).

The SR<sub>baseline</sub> (Fig. 1d) is clearly highest for both, BPA and BPS. BPA was tested highly specific in bioassays indicative of the activation of the estrogen receptor (ER) with SR<sub>baseline</sub> up to 2300. Despite its lower overall potency, the SR<sub>baseline</sub> of BPS was up to 4 times higher than of BPA. This means that with respect to its intrinsic effect BPS is rather similar to BPA even if estrogen-specific effects are only triggered at higher nominal concentrations due to the lower hydrophobicity of BPS. This conclusion needs to be treated with certain caution due to the high variability of hydrophobicity prediction models for BPS. A SR of 10 represents the threshold between specific and highly specific effects Fig. 4d (Escher et al., 2020). A compound activating a response below 10 is considered behaving as baseline toxicant. TCBPA is of similar potency expressed as EC<sub>10</sub> as BPA Fig. 4c), however, it has a SR<sub>baseline</sub> below 10 in most assays in our dataset. Therefore, we can conclude it is acting like a baseline toxicant meaning that TCBPA activates the ER but at concentrations where nonspecific toxicity occurs.

The black filled circles in Fig. 4d are endpoints related to activation of the ER or indirect effects on ER. ER-related endpoints are most active with highest SR<sub>baseline</sub> for BPA and BPS but are at SR<sub>baseline</sub> < 10 for TCBPA and BPC. The TOX21_ERa_LUC VM7 assay (formerly called TOX21_ERa_LUC BG1, (Brennan et al., 2016) was identified as the most sensitive estrogen receptor reporter gene assay (Dreier et al., 2015) and is highlighted in Fig. 4c and d with a cross through the circle. It is indeed also one of the most sensitive assays for BPA alternatives with exception of the TCBPA, which confirms that the bulky TCBPA is a poor activator

of ER, which had already been shown previously (Pelch et al., 2019). The activation of nuclear receptors with SR<sub>baseline</sub> close to 1 is likely to be an artifact and caused by the cytotoxicity burst. The term "cytotoxicity burst" describes the phenomenon of enhanced non- specific activation of stress responses and even nuclear receptor binding that occur close to cell death (Escher et al., 2020; Judson et al., 2016; Fay et al., 2018).

It is somewhat puzzling on first sight that also ER antagonism seems to play a role at rather low concentration (Fig. 4c). However, the SR<sub>baseline</sub> analysis clearly indicates that this effect is not specific and is likely to also be an artifact of the cytotoxicity burst (Fig. 4d). With this knowledge in mind, we can interpret the effect data in the *in vitro* assays from a different viewpoint: Specific effects matter more if they have a SR<sub>baseline</sub> > 10. Apart from the large number of estrogenicity assays with SR<sub>baseline</sub> > 10, the antagonistic mode of androgen receptor (AR) assays were also active with SR<sub>baseline</sub> of 33 for BPA, 39 for BPC and 128 for BPS. Activation of ER is commonly accompanied by antagonism of AR (Pelch et al., 2019).

The vitamin D receptor (assay ATG_VDRE_CIS_up) was activated with a SR<sub>baseline</sub> of 22 by BPA, 8 by BPC and 5625 by BPS. The pregnane X receptor (PXR) and constitutive androstane receptor (CAR), both of which are regulators of xenobiotic metabolism, were also activated by BPA but not by any other BPA alternatives. Most notably, the TOX21_MMP assays (MMP stands for mitochondrial membrane potential, (Attene-Ramos et al., 2013) also captured the specific mitochondrial toxicity of BPA alternatives. BPA is known to exert mitochondrial toxicity (Khan et al., 2016), and the SR<sub>baseline</sub> of 60 by BPA, 56 by TCBPA and 15 by BPC (Supp.info 3, Table SI-3) indicate that these analogs are also mitochondrial toxicants, while BPS was not active in TOX21_MMP (Supp.info 3, Table SI-2).

For the analysis in Fig. 4c and 4d we just selected BPA and 3 of the 15 BPA alternatives, where we found data for *in vitro* bioassays to illustrate important differences. An overview about the analysis of the effects of all BPA alternatives in *in vitro* reporter gene assays is given in the Supplementary information.

Cytotoxicity data is rather scarce in the *in vitro* database and available only for 14 compounds and fewer assays (Supp. info 2, Fig.SI-2). Of the reported IC<sub>10</sub> for cytotoxicity, BPS-MPE and TBBPA have the highest TR > 1000 and BCP, BPAB, BzPB, BPA, BPZ, BPPH, TCBPA and BPAF were mere baseline toxicants with TR < 10 (Supp. info 2, Fig.SI-2). Only for three chemicals (BPZ, BPPH, BPC), both receptor-activation and cytotoxicity were available. Therefore, no direct comparison was possible for the larger chemical set, and we analyzed cytotoxicity (Supp. info 2, Fig. SI-2) and reporter gene activation (Supp. info 2, Fig. SI-3) independently.

BPA was one of the most active chemicals (but also one that was tested in most bioassays) but the SR<sub>baseline</sub> was in most assays higher for BPS than BPA. Some alternatives, especially the hydrophobic ones (BPPH, TCBPA, BPS-MPE) often had lower SR<sub>baseline</sub>, despite overall rather high potency. This analysis clearly demonstrated the importance to evaluate not only the absolute potency differences but consider the potency also in relation to the degree (SR<sub>baseline</sub>) and type of specificity (affected endpoint). To differentiate between specific and non-specific effects is vital for risk assessment (Fay et al., 2018) because non-specific effects will occur for all endpoints, albeit at high nominal concentrations and can be confidently predicted by baseline toxicity models across cells but also all across aquatic species. To know which specific effects are relevant is also important. BPA and many of its alternatives are estrogenic but we also find other relevant endpoints related to xenobiotic metabolism and mitochondrial toxicity, which can guide ecotoxicity testing.

## 4.4. Predictive models for ecotoxicity of bisphenols alternatives

Two phases can be distinguished in the dose-response relationship of a chemical in an organism: the toxicokinetic (TK), that is the fate of the
compound in the organism including absorption, distribution, metabolism and excretion (ADME), and the toxicodynamics (TD), that is the expression of the toxicity/effect of the substance at the site of action.

The simplest approaches to predict TK or TD are based on steady-state assumptions (e.g. quantitative structure-relationship models (QSAR)) which reflect the equilibrium between accumulation of a compound and its elimination from all exposure routes. In some cases, the steady-state assumption may not hold, particularly in environmental conditions under which chemical occurrence and exposure may vary considerably.

Therefore, in order to review the models developed to predict TK and TD of bisphenol derivatives, we structured this chapter in two main parts: the first part presents static models assuming a steady state and the second part presents dynamic models (i.e., those where temporal variation of exposure or effects is explicitly taken into account). Further, commercially available software TEST, VEGA, OPERA, ECOSAR, and the OECD QSAR toolbox were checked for the availability of implemented predictive models for estimating the ecotoxicity of compounds. A list of all the available models that incorporated either BPA or BPA alternatives in their training set was compiled (Supp. info 4, Tab.S2.1). Moreover, we carried out a comparative analysis of the predictions between the VEGA and TEST software and checked how the predictions differed within one software.

### 4.4.1. QSAR model: Models assuming steady state

Currently, many available scientific papers are focused on QSAR models for predicting toxicity for a wide group of compounds, such as contaminants of emerging concern (CEC) (Onlü and Saçan, 2018) or ionizable organic chemicals (IOC) (Klüver et al., 2019). In contrast, no specific models for predicting ecotoxicological properties have been dedicated only to bisphenols and their derivatives.

Usually, available models are focused on compounds from the different chemical groups and contain in the training set only single bisphenols (e.g., BPA, BPAF, and BPS). The variety of relevant ecotoxicological endpoints in published models is also severely limited and is not always consistent with risk assessment requirements. Supp. info 4 (Tab. S2.1) presents gathered available models developed for predicting ecotoxicological endpoints containing bisphenols and their derivatives in the training set. There are models that focus on establishing the ecotoxicity for different species separately (e.g. Danio rerio and Ozyrias latipes), but also models that cover simultaneously different taxonomic groups (e.g algae, daphnid, and fish) – multispecies models. The most often included in the training set are BPA, TBBPA, and BPF. Each of these models could be applied for predicting the ecotoxicity of bisphenols derivatives, however, in practice, it requires evaluating if the model is scientifically valid and fulfills OECD recommendations for developing and validating the QSAR models. Moreover, the introduction of the properly derived structure of the compounds (molecular descriptors used in the models) and assessing if obtained predictions are within the space of the applicability domains (AD) of the models are needed, which requires specialized knowledge in the field of computational chemistry.

### 4.4.2. Comparison of available tools for predicting ecotoxicity of bisphenols

The other source of predictive models available within the public domain is open-source tools, like e.g., TEST, VEGA, OPERA and the OECD QSAR toolbox. These tools have implemented different models that can be used for estimating the ecotoxicity of compounds (Supp. info 4, Tab. S2.1 and S2.2). Predictions of an endpoint values are based here on the structural similarity between the compounds of interest and a training set on which the model was developed. In some cases, it may be that the predictive ability of such models for the chemicals of interest is not appropriate, and predictions can fall outside the model's applicability domain (AD), making them less reliable. Further, in each of these software tools, implemented models were developed using different compounds for training and validation, even within the same endpoint.

In Task 5.2.2 of PARC there was a need to verify whether the

available tools could be used to predict the ecotoxicity of BPA alternatives. In the first step, the acute toxicity of *Daphnia magna* was analyzed. Two models for estimating EC₅₀ were available in the VEGA. The predictions for 16 BPA alternatives established in PARC derived from the VEGA tool were analyzed and compared to the experimental data whenever possible (Table 3). Here, the 'prediction' and 'reliability' were considered. 'Prediction' means how well the model predicted the result, relative to the training set. If there is a good prediction, it means that there were chemical compounds in the training set with a similar structure to the predicted compound. In contrast, 'reliability' refers to the validation of the predictions made, i.e. whether the prediction is reliable, or more precisely whether it is within the AD. Almost all prediction results obtained using two different acute toxicity models for *Daphnia magna* 48 h (EC₅₀) were found to be both not very accurate, due to the lack of similar molecules in the training set, and unreliable (out of AD). The exception is one prediction made for BPZ (CAS: 843–55-0) based on experimental data implemented in the software. This means that by possessing experimental ecotoxicity data for the group of compounds in question, accurate and reliable predictions can be made, but currently the detailed data necessary are mostly lacking.

In the next step, LC₅₀ values for *Daphnia magna* predicted using TEST and VEGA software were analyzed (Table 4). There are apparent differences between the predictions obtained for acute toxicity, depending on the model and software used. In the TEST software for each modeling method, good predictions were obtained for two compounds, BPAP (Bisphenol AP, CAS: 1571–75-1) and BPE (CAS: 2081–08-5). This means that the training sets used in the models contained structurally similar compounds. Between themselves, these compounds are also similar, differing only in the substitution of the central carbon atom. In BPE, the hydrogen atom on the central carbon atom was substituted with benzene in the case of Bisphenol AP. On the other hand, applying the VEGA the predictions for the previously mentioned bisphenol pair are incorrect and out of the AD. This may mean that for both models presented in the VEGA software, there are no structurally similar compounds to BPAP and BPE used for training the models. In contrast, the models considered in VEGA contained chemical compounds similar to the three compounds considered as alternatives: 2,2,4,4-Tetramethylcyclobutane-1,3-diol (CAS: 3010–96-6), 4,4'-Thiodiphenol (CAS: 2664–63-3) and 2,4'-Dihydroxydiphenyl sulfone (CAS: 5397–34-2). In each of the models used, regardless of the software (with a few exceptions), the predictions obtained do not fall within the AD. This is a result of the lack of bisphenols in the training sets, as well as the lack of experimental data for compounds similar to bisphenols.

Summarizing, available tools for predicting activity/physicochemical properties are beneficial in the primary assessment of chemicals, however, they do not cover BPA alternatives in case of acute toxicity to *Daphnia magna*. Evaluation of the applicability of other ecotoxicity models implemented in those tools in terms of their reliability for bisphenols alternatives alternatives were recently conducted in Lagares et al. 2023 (Mora Lagares and Vračko, 2023). However, it is already evident that there is a very high demand for *in silico* methods covering the whole group of bisphenols and their derivatives (also including bisphenol alternatives) with regard to the endpoints importance also from the regulatory point of view.

### 4.4.3. Dynamic models

#### 4.4.3.1. Toxicokinetic models.
Dynamic toxicokinetic models were developed to support NAM using zebrafish eleutheroembryo (Siméon et al., 2020). Indeed, analytical methods are still missing to measure organ concentrations. Therefore, physiologically based toxicokinetic (PBTK) modelling may overcome current limitations to help understand the relationship between toxic effects and internal exposure in various organs. A model was specifically developed to simulate the toxicokinetics of BPA, BPAF, BPF, and BPS through the eleutheroembryo
compound in the organism including absorption, distribution, metabolism and excretion (ADME), and the toxicodynamics (TD), that is the expression of the toxicity/effect of the substance at the site of action.

The simplest approaches to predict TK or TD are based on steady-state assumptions (e.g. quantitative structure-relationship models (QSAR)) which reflect the equilibrium between accumulation of a compound and its elimination from all exposure routes. In some cases, the steady-state assumption may not hold, particularly in environmental conditions under which chemical occurrence and exposure may vary considerably.

Therefore, in order to review the models developed to predict TK and TD of bisphenol derivatives, we structured this chapter in two main parts: the first part presents static models assuming a steady state and the second part presents dynamic models (i.e., those where temporal variation of exposure or effects is explicitly taken into account). Further, commercially available software TEST, VEGA, OPERA, ECOSAR, and the OECD QSAR toolbox were checked for the availability of implemented predictive models for estimating the ecotoxicity of compounds. A list of all the available models that incorporated either BPA or BPA alternatives in their training set was compiled (Supp. info 4, Tab.S2.1). Moreover, we carried out a comparative analysis of the predictions between the VEGA and TEST software and checked how the predictions differed within one software.

### 4.4.1. QSAR model: Models assuming steady state

Currently, many available scientific papers are focused on QSAR models for predicting toxicity for a wide group of compounds, such as contaminants of emerging concern (CEC) (Onlü and Saçan, 2018) or ionizable organic chemicals (IOC) (Klüver et al., 2019). In contrast, no specific models for predicting ecotoxicological properties have been dedicated only to bisphenols and their derivatives.

Usually, available models are focused on compounds from the different chemical groups and contain in the training set only single bisphenols (e.g., BPA, BPAF, and BPS). The variety of relevant ecotoxicological endpoints in published models is also severely limited and is not always consistent with risk assessment requirements. Supp. info 4 (Tab. S2.1) presents gathered available models developed for predicting ecotoxicological endpoints containing bisphenols and their derivatives in the training set. There are models that focus on establishing the ecotoxicity for different species separately (e.g. Danio rerio and Ozyrias latipes), but also models that cover simultaneously different taxonomic groups (e.g algae, daphnid, and fish) – multispecies models. The most often included in the training set are BPA, TBBPA, and BPF. Each of these models could be applied for predicting the ecotoxicity of bisphenols derivatives, however, in practice, it requires evaluating if the model is scientifically valid and fulfills OECD recommendations for developing and validating the QSAR models. Moreover, the introduction of the properly derived structure of the compounds (molecular descriptors used in the models) and assessing if obtained predictions are within the space of the applicability domains (AD) of the models are needed, which requires specialized knowledge in the field of computational chemistry.

### 4.4.2. Comparison of available tools for predicting ecotoxicity of bisphenols

The other source of predictive models available within the public domain is open-source tools, like e.g., TEST, VEGA, OPERA and the OECD QSAR toolbox. These tools have implemented different models that can be used for estimating the ecotoxicity of compounds (Supp. info 4, Tab. S2.1 and S2.2). Predictions of an endpoint values are based here on the structural similarity between the compounds of interest and a training set on which the model was developed. In some cases, it may be that the predictive ability of such models for the chemicals of interest is not appropriate, and predictions can fall outside the model's applicability domain (AD), making them less reliable. Further, in each of these software tools, implemented models were developed using different compounds for training and validation, even within the same endpoint.

In Task 5.2.2 of PARC there was a need to verify whether the

available tools could be used to predict the ecotoxicity of BPA alternatives. In the first step, the acute toxicity of *Daphnia magna* was analyzed. Two models for estimating EC₅₀ were available in the VEGA. The predictions for 16 BPA alternatives established in PARC derived from the VEGA tool were analyzed and compared to the experimental data whenever possible (Table 3). Here, the ‘prediction’ and ‘reliability’ were considered. ‘Prediction’ means how well the model predicted the result, relative to the training set. If there is a good prediction, it means that there were chemical compounds in the training set with a similar structure to the predicted compound. In contrast, ‘reliability’ refers to the validation of the predictions made, i.e. whether the prediction is reliable, or more precisely whether it is within the AD. Almost all prediction results obtained using two different acute toxicity models for *Daphnia magna* 48 h (EC₅₀) were found to be both not very accurate, due to the lack of similar molecules in the training set, and unreliable (out of AD). The exception is one prediction made for BPZ (CAS: 843–55-0) based on experimental data implemented in the software. This means that by possessing experimental ecotoxicity data for the group of compounds in question, accurate and reliable predictions can be made, but currently the detailed data necessary are mostly lacking.

In the next step, LC₅₀ values for *Daphnia magna* predicted using TEST and VEGA software were analyzed (Table 4). There are apparent differences between the predictions obtained for acute toxicity, depending on the model and software used. In the TEST software for each modeling method, good predictions were obtained for two compounds, BPAP (Bisphenol AP, CAS: 1571–75-1) and BPE (CAS: 2081–08-5). This means that the training sets used in the models contained structurally similar compounds. Between themselves, these compounds are also similar, differing only in the substitution of the central carbon atom. In BPE, the hydrogen atom on the central carbon atom was substituted with benzene in the case of Bisphenol AP. On the other hand, applying the VEGA the predictions for the previously mentioned bisphenol pair are incorrect and out of the AD. This may mean that for both models presented in the VEGA software, there are no structurally similar compounds to BPAP and BPE used for training the models. In contrast, the models considered in VEGA contained chemical compounds similar to the three compounds considered as alternatives: 2,2,4,4-Tetramethylcyclobutane-1,3-diol (CAS: 3010–96-6), 4,4'-Thiodiphenol (CAS: 2664–63-3) and 2,4'-Dihydroxydiphenyl sulfone (CAS: 5397–34-2). In each of the models used, regardless of the software (with a few exceptions), the predictions obtained do not fall within the AD. This is a result of the lack of bisphenols in the training sets, as well as the lack of experimental data for compounds similar to bisphenols.

Summarizing, available tools for predicting activity/physicochemical properties are beneficial in the primary assessment of chemicals, however, they do not cover BPA alternatives in case of acute toxicity to *Daphnia magna*. Evaluation of the applicability of other ecotoxicity models implemented in those tools in terms of their reliability for bisphenols alternatives alternatives were recently conducted in Lagares et al. 2023 (Mora Lagares and Vračko, 2023). However, it is already evident that there is a very high demand for *in silico* methods covering the whole group of bisphenols and their derivatives (also including bisphenol alternatives) with regard to the endpoints importance also from the regulatory point of view.

### 4.4.3. Dynamic models

#### 4.4.3.1. Toxicokinetic models.
Dynamic toxicokinetic models were developed to support NAM using zebrafish eleutheroembryo (Siméon et al., 2020). Indeed, analytical methods are still missing to measure organ concentrations. Therefore, physiologically based toxicokinetic (PBTK) modelling may overcome current limitations to help understand the relationship between toxic effects and internal exposure in various organs. A model was specifically developed to simulate the toxicokinetics of BPA, BPAF, BPF, and BPS through the eleutheroembryo
<table><caption>**Table 3**
Comparison of the acute toxicity (*Daphnia magna*) predictions for 16 bisphenols alternatives using VEGA software (Martin, 2020; Benfenati et al., 2013).</caption><thead><tr><th rowspan="2">IUPAC – Compound Name</th><th rowspan="2">Molecule CAS</th><th rowspan="2">Experimental data*<br>EC<sub>50</sub><br>[mg/L]</th><th colspan="2">VEGA</th></tr><tr><th>Daphnia magna<br>Acute (EC<sub>50</sub>) Toxicity<br>model (IRFMN)<br>Predicted [mg/L]</th><th>Daphnia magna Acute<br>(EC<sub>50</sub>) Toxicity model<br>(IRFMN/Combase)<br>Predicted [mg/L]</th></tr></thead><tbody><tr><td>2,2-Bis(2-hydroxy-5-biphenylyl)propane</td><td>24038-68-4</td><td>N/A</td><td>0.4695</td><td>P R</td><td>0.0769</td><td>P R</td></tr><tr><td>4-[4-(benzyloxy)benzenesulfonyl]phenol</td><td>63134-33-8</td><td>N/A</td><td>15.02</td><td>P R</td><td>0.1522</td><td>P R</td></tr><tr><td>4-[(4-Isopropoxyphenyl)sulfonyl]phenol</td><td>95235-30-6</td><td>N/A</td><td>20.07</td><td>P R</td><td>0.1045</td><td>P R</td></tr><tr><td>4-[4-(Allyloxy)phenyl]sulfonyl]phenol</td><td>97042-18-7</td><td>13.5</td><td>22.01</td><td>P R</td><td>0.0702</td><td>P R</td></tr><tr><td>4,4'-[1-Phenylethylidene]bisphenol</td><td>1571-75-1</td><td>N/A</td><td>6.76</td><td>P R</td><td>0.0333</td><td>P R</td></tr><tr><td>1,1-Bis(4-hydroxyphenyl)ethane</td><td>2081-08-5</td><td>N/A</td><td>16.07</td><td>P R</td><td>0.1688</td><td>P R</td></tr><tr><td>4,4'-[1,4-Phenylenebis[1-<br>methylethylidene]] bis-phenol</td><td>2167-51-3</td><td>N/A</td><td>0.8283</td><td>P R</td><td>0.0056</td><td>P R</td></tr><tr><td>1,1'-Bis(4-hydroxyphenyl)cyclohexane</td><td>843-55-0</td><td>1.8</td><td>6.11</td><td>P R</td><td>0.0091</td><td>P R</td></tr><tr><td>Benzyl 4-hydroxybenzoate</td><td>94-18-8</td><td>6</td><td>1.58</td><td>P R</td><td>2.05</td><td>P R</td></tr><tr><td>2,2,4,4-Tetramethyl-1,3-cyclobutanediol<br>(racemate)</td><td>3010-96-6</td><td>106</td><td>85.02</td><td>P R</td><td>1.48</td><td>P R</td></tr><tr><td>Benzeneacetic acid, 4-hydroxy-alpha-[4-<br>hydroxyphenyl]-, methyl ester</td><td>5129-00-0</td><td>N/A</td><td>28.9</td><td>P R</td><td>0.27</td><td>P R</td></tr><tr><td>4,4'-Thiodiphenol</td><td>2664-63-3</td><td>N/A</td><td>34.63</td><td>P R</td><td>0.0553</td><td>P R</td></tr><tr><td>N-(p-toluenesulfonyl)-N'-[3-(p-<br>toluenesulfonyloxy)phenyl]urea</td><td>232938-43-1</td><td>56</td><td>0.0022</td><td>P R</td><td>0.0488</td><td>P R</td></tr><tr><td>4,4'-Bis(p-<br>tolylsulfonylureido)diphenylmethane</td><td>151882-81-4</td><td>N/A</td><td>0.2701</td><td>P R</td><td>1.05</td><td>P R</td></tr><tr><td>2,4'-Dihydroxydiphenyl sulfone</td><td>5397-34-2</td><td>N/A</td><td>10.48</td><td>P R</td><td>0.6772</td><td>P R</td></tr><tr><td>2,2',6,6'-Tetrachlorobisphenol A</td><td>79-95-8</td><td>N/A</td><td>0.5831</td><td>P R</td><td>0.0015</td><td>P R</td></tr></tbody></table>

tissues while considering the body and organ growth (Billat et al., 2023). This model was developed using data retrieved by an extensive literature search and very few datasets were found to support the model development for the BPA alternatives.

To dynamically assess exposure and bioaccumulation, the simplest

models are based on a one-compartment assumption, according to which the chemical concentration is the same throughout the organism. This model is suitable for compounds that distribute rapidly throughout the body (Grech et al., 2017). This approach has been mainly applied on BPA for various aquatic organisms: in freshwater clam (Heinonen et al.,

<footnote>*Experimental data were collected using QSAR TOOLBOX,</footnote>

<footnote>P – Prediction: Good (Green color), Unfavorable (Red color),</footnote>

<footnote>R – Reliability of the prediction (AD): Green (In AD), Orange (Possibly Out of AD), Red (Out of AD).</footnote>
<table><caption>**Table 3**
Comparison of the acute toxicity (*Daphnia magna*) predictions for 16 bisphenols alternatives using VEGA software (Martin, 2020; Benfenati et al., 2013).</caption><thead><tr><th rowspan="2">IUPAC – Compound Name</th><th rowspan="2">Molecule CAS</th><th rowspan="2">Experimental data*<br>EC<sub>50</sub><br>[mg/L]</th><th colspan="2">VEGA</th></tr><tr><th>Daphnia magna<br>Acute (EC<sub>50</sub>) Toxicity<br>model (IRFMN)<br>Predicted [mg/L]</th><th>Daphnia magna Acute<br>(EC<sub>50</sub>) Toxicity model<br>(IRFMN/Combase)<br>Predicted [mg/L]</th></tr></thead><tbody><tr><td>2,2-Bis(2-hydroxy-5-biphenylyl)propane</td><td>24038-68-4</td><td>N/A</td><td>0.4695</td><td>P R</td></tr><tr><td>4-[4-(benzyloxy)benzenesulfonyl]phenol</td><td>63134-33-8</td><td>N/A</td><td>15.02</td><td>P R</td></tr><tr><td>4-[(4-Isopropoxyphenyl)sulfonyl]phenol</td><td>95235-30-6</td><td>N/A</td><td>20.07</td><td>P R</td></tr><tr><td>4-[4-(Allyloxy)phenyl]sulfonyl]phenol</td><td>97042-18-7</td><td>13.5</td><td>22.01</td><td>P R</td></tr><tr><td>4,4'-[1-Phenylethylidene]bisphenol</td><td>1571-75-1</td><td>N/A</td><td>6.76</td><td>P R</td></tr><tr><td>1,1-Bis(4-hydroxyphenyl)ethane</td><td>2081-08-5</td><td>N/A</td><td>16.07</td><td>P R</td></tr><tr><td>4,4'-[1,4-Phenylenebis[1-<br>methylethylidene]] bis-phenol</td><td>2167-51-3</td><td>N/A</td><td>0.8283</td><td>P R</td></tr><tr><td>1,1'-Bis(4-hydroxyphenyl)cyclohexane</td><td>843-55-0</td><td>1.8</td><td>6.11</td><td>P R</td></tr><tr><td>Benzyl 4-hydroxybenzoate</td><td>94-18-8</td><td>6</td><td>1.58</td><td>P R</td></tr><tr><td>2,2,4,4-Tetramethyl-1,3-cyclobutanediol<br>(racemate)</td><td>3010-96-6</td><td>106</td><td>85.02</td><td>P R</td></tr><tr><td>Benzeneacetic acid, 4-hydroxy-alpha-[4-<br>hydroxyphenyl]-, methyl ester</td><td>5129-00-0</td><td>N/A</td><td>28.9</td><td>P R</td></tr><tr><td>4,4'-Thiodiphenol</td><td>2664-63-3</td><td>N/A</td><td>34.63</td><td>P R</td></tr><tr><td>N-(p-toluenesulfonyl)-N'-[3-(p-<br>toluenesulfonyloxy)phenyl]urea</td><td>232938-43-1</td><td>56</td><td>0.0022</td><td>P R</td></tr><tr><td>4,4'-Bis(p-<br>tolylsulfonylureido)diphenylmethane</td><td>151882-81-4</td><td>N/A</td><td>0.2701</td><td>P R</td></tr><tr><td>2,4'-Dihydroxydiphenyl sulfone</td><td>5397-34-2</td><td>N/A</td><td>10.48</td><td>P R</td></tr><tr><td>2,2',6,6'-Tetrachlorobisphenol A</td><td>79-95-8</td><td>N/A</td><td>0.5831</td><td>P R</td></tr></tbody></table>

tissues while considering the body and organ growth (Billat et al., 2023). This model was developed using data retrieved by an extensive literature search and very few datasets were found to support the model development for the BPA alternatives.

To dynamically assess exposure and bioaccumulation, the simplest

models are based on a one-compartment assumption, according to which the chemical concentration is the same throughout the organism. This model is suitable for compounds that distribute rapidly throughout the body (Grech et al., 2017). This approach has been mainly applied on BPA for various aquatic organisms: in freshwater clam (Heinonen et al.,

<footnote>*Experimental data were collected using QSAR TOOLBOX,</footnote>

<footnote>P – Prediction: Good (Green color), Unfavorable (Red color),</footnote>

<footnote>R – Reliability of the prediction (AD): Green (In AD), Orange (Possibly Out of AD), Red (Out of AD).</footnote>
<table><caption>**Table 4**
Predictions made in selected software for bisphenol alternatives (Martin, 2020; Benfenati et al., 2013).</caption><thead><tr><th rowspan="2">IUPAC -<br>Compound<br>Name</th><th rowspan="2">Molecule<br>[CAS]</th><th rowspan="2">Experimental<br>Value</th><th colspan="6">TEST Daphnia magna LC<sub>50</sub> (48h)<br>[-log10(mol/L)]</th><th colspan="2">VEGA Daphnia magna LC<sub>50</sub> 48h Predicted<br>[-log(mol/L)]</th></tr><tr><th>LC<sub>50</sub><br>-<br>log10/<br>mol/L</th><th>Consensus Model</th><th>Hierarchical<br>Clustering</th><th>Single Model</th><th>Group Contribution<br>Model</th><th>Nearest Neighbor<br>Model</th><th>(EPA)</th><th>(DEMETRA)</th></tr></thead><tbody><tr><td>2,2-Bis(2-<br>hydroxy-5-<br>biphenyl)prop-<br>ane</td><td>24038-<br>68-4</td><td>N/A</td><td>6.99</td><td>7</td><td>7.2</td><td>7.97</td><td>5.81</td><td>5.55</td><td>4.5</td><td></td></tr><tr><td>4-[4-<br>(benzyl)benz-<br>enesulfonyl]phe-<br>nol</td><td>63134-<br>33-8</td><td>N/A</td><td>5.37</td><td>5.62</td><td>5.86</td><td>4.98</td><td>5.01</td><td>4.88</td><td>4.72</td><td></td></tr><tr><td>4-[4-<br>isopropoxyphen-<br>yl)sulfonyl]phen-<br>ol</td><td>95235-<br>30-6</td><td>N/A</td><td>4.74</td><td>4.79</td><td>5.41</td><td>4.32</td><td>4.45</td><td>4.46</td><td>4.03</td><td></td></tr><tr><td>4-[4-<br>(Allyloxy)phenyl]<br>sulfonyl]phenol</td><td>97042-<br>18-7</td><td>N/A</td><td>4.99</td><td>4.94</td><td>5.31</td><td>4.72</td><td>N/A</td><td>4.4</td><td>4.08</td><td></td></tr><tr><td>4,4'-[1-<br>Phenylethyliden<br>e]bisphenol</td><td>1571-<br>75-1</td><td>N/A</td><td>5.45</td><td>5.6</td><td>5.75</td><td>5.09</td><td>5.34</td><td>4.67</td><td>3.74</td><td></td></tr><tr><td>1,1-Bis(4-<br>hydroxyphenyl)le-<br>thane</td><td>2081-<br>08-5</td><td>N/A</td><td>4.8</td><td>4.6</td><td>4.96</td><td>5.43</td><td>4.25</td><td>3.66</td><td>3.46</td><td></td></tr><tr><td>4,4'-[1,4-<br>Phenylenebis[1-<br>methylthyliden<br>e]]bis phenol</td><td>2167-<br>51-3</td><td>N/A</td><td>5.82</td><td>6.32</td><td>6.75</td><td>5.55</td><td>4.65</td><td>5.35</td><td>4.4</td><td></td></tr><tr><td>1,1'-Bis(4-<br>hydroxyphenyl)lc-<br>yclohexane</td><td>843-<br>55-0</td><td>N/A</td><td>5.18</td><td>5.45</td><td>4.99</td><td>4.92</td><td>5.34</td><td>4.3</td><td>3.6</td><td></td></tr><tr><td>Benzyl 4-<br>hydroxybenzoat-<br>e</td><td>94-18-<br>8</td><td>N/A</td><td>4.87</td><td>5.07</td><td>5.09</td><td>4.77</td><td>4.56</td><td>4.76</td><td>4.68</td><td></td></tr><tr><td>2,2,4,4-<br>Tetramethyl-<br>1,3-<br>cyclobutanediol<br>(racemate)</td><td>3010-<br>96-6</td><td>N/A</td><td>2.87</td><td>3.96</td><td>3.42</td><td>3.23</td><td>N/A</td><td>2.53</td><td>4.09</td><td>R</td></tr><tr><td>Benzeneacetic<br>acid, 4-hydroxy-<br>alpha-[4-<br>hydroxyphenyl]-<br>methyl ester</td><td>5129-<br>00-0</td><td>N/A</td><td>4.81</td><td>4.04</td><td>4.89</td><td>5.44</td><td>4.89</td><td>3.86</td><td>3.54</td><td></td></tr><tr><td>4,4'-<br>Thiodiphenol</td><td>2664-<br>63-3</td><td>N/A</td><td>N/A</td><td>N/A</td><td>N/A</td><td>N/A</td><td>N/A</td><td>4.78</td><td>3.9</td><td></td></tr><tr><td>N-(p-<br>toluenesulfonyl)<br>-N'-[3-(p-<br>toluenesulfonyloxy)<br>phenyl]urea</td><td>232938-<br>-43-1</td><td>N/A</td><td>N/A</td><td>N/A</td><td>N/A</td><td>N/A</td><td>N/A</td><td>4.52</td><td>6.11</td><td></td></tr><tr><td>4,4'-Bis(p-<br>tolylsulfonylurei<br>do)diphenylmet-<br>hane</td><td>151882-<br>-81-4</td><td>N/A</td><td>N/A</td><td>N/A</td><td>N/A</td><td>N/A</td><td>N/A</td><td>4.66</td><td>6.97</td><td></td></tr><tr><td>2,4'-<br>Dihydroxydiphe-<br>nyl sulfone</td><td>5397-<br>34-2</td><td>N/A</td><td>4.61</td><td>4.54</td><td>5.15</td><td>4.3</td><td>4.45</td><td>2.6</td><td>3.06</td><td></td></tr><tr><td>2,2',6,6'-<br>Tetrachlorobis-<br>phenol A</td><td>79-95-<br>8</td><td>N/A</td><td>6.55</td><td>7.03</td><td>6.96</td><td>6.77</td><td>4.99</td><td>4.8</td><td>3.83</td><td></td></tr></tbody></table>

P – Prediction: Reliable (Green color), Unreliable (Red color),

R – Reliability of the prediction (AD): Green (In AD), Orange (Possibly Out of AD), Red (Out of AD).

2002), in frogs (Honkanen and Kukkonen, 2006; Koponen et al., 2007)) and in fish (Wang et al., 2020; Honkanen et al., 2004). To our knowledge, only one publication has explored the bioaccumulation of the bisphenol analogues using a simple one-compartment model (Wang et al., 2020). These authors have studied bioconcentration of eight common bisphenol analogues, including bisphenol A, –B, –C, –E, –S, –Z, –AF, and –AP in common carp and calculated bioconcentration factors based on the total bisphenols. These authors suggested that

kidney and liver played important roles in accumulating bisphenols in carp, and kidney made more contribution than liver for most bisphenols. In addition, they concluded that biliary excretion predominated for elimination of most bisphenols while BPA and BPS were excreted mainly through urine (Wang et al., 2020).

In fish, several PBPK models have been used to predict the BPA bioaccumulation (Péry et al., 2014; Grech et al., 2019; Mit et al., 2022). However, only (Mit et al., 2022; Chelcea et al., 2022) are specific to this
<table><caption>**Table 4**

Predictions made in selected software for bisphenol alternatives (Martin, 2020; Benfenati et al., 2013).</caption><thead><tr><th rowspan="2">IUPAC -<br>Compound<br>Name</th><th rowspan="2">Molecule<br>[CAS]</th><th rowspan="2">Experimental<br>Value</th><th colspan="6">TEST Daphnia magna LC<sub>50</sub> (48h)<br>[-log10(mol/L)]</th><th colspan="2">VEGA Daphnia magna LC<sub>50</sub> 48h Predicted<br>[-log(mol/L)]</th></tr><tr><th>LC<sub>50</sub><br>-<br>log10/<br>mol/L</th><th>Consensus Model</th><th>Hierarchical<br>Clustering</th><th>Single Model</th><th>Group Contribution<br>Model</th><th>Nearest Neighbor<br>Model</th><th>(EPA)</th><th>(DEMETRA)</th></tr></thead><tbody><tr><td>2,2-Bis(2-<br>hydroxy-5-<br>biphenyl)prop-<br>ane</td><td>24038-<br>68-4</td><td>N/A</td><td>6.99</td><td>7</td><td>7.2</td><td>7.97</td><td>5.81</td><td>5.55</td><td>4.5</td><td></td></tr><tr><td>4-[4-<br>(benzyl)benz-<br>enesulfonyl)phe-<br>nol</td><td>63134-<br>33-8</td><td>N/A</td><td>5.37</td><td>5.62</td><td>5.86</td><td>4.98</td><td>5.01</td><td>4.88</td><td>4.72</td><td></td></tr><tr><td>4-[4-<br>isopropoxyphen-<br>yl)sulfonyl)phe-<br>nol</td><td>95235-<br>30-6</td><td>N/A</td><td>4.74</td><td>4.79</td><td>5.41</td><td>4.32</td><td>4.45</td><td>4.46</td><td>4.03</td><td></td></tr><tr><td>4-[[4-<br>(Allyloxy)phenyl]<br>sulfonyl)(phenol)</td><td>97042-<br>18-7</td><td>N/A</td><td>4.99</td><td>4.94</td><td>5.31</td><td>4.72</td><td>N/A</td><td>4.4</td><td>4.08</td><td></td></tr><tr><td>4,4'-[1-<br>Phenylethyliden<br>e]bisphenol</td><td>1571-<br>75-1</td><td>N/A</td><td>5.45</td><td>5.6</td><td>5.75</td><td>5.09</td><td>5.34</td><td>4.67</td><td>3.74</td><td></td></tr><tr><td>1,1-Bis(4-<br>hydroxyphenyl)le-<br>thane</td><td>2081-<br>08-5</td><td>N/A</td><td>4.8</td><td>4.6</td><td>4.96</td><td>5.43</td><td>4.25</td><td>3.66</td><td>3.46</td><td></td></tr><tr><td>4,4'-[1,4-<br>Phenylenebis[1-<br>methylthyliden<br>e]]bisphenol</td><td>2167-<br>51-3</td><td>N/A</td><td>5.82</td><td>6.32</td><td>6.75</td><td>5.55</td><td>4.65</td><td>5.35</td><td>4.4</td><td></td></tr><tr><td>1,1'-Bis(4-<br>hydroxyphenyl)c-<br>yclohexane</td><td>843-<br>55-0</td><td>N/A</td><td>5.18</td><td>5.45</td><td>4.99</td><td>4.92</td><td>5.34</td><td>4.3</td><td>3.6</td><td></td></tr><tr><td>Benzyl 4-<br>hydroxybenzoat-<br>e</td><td>94-18-<br>8</td><td>N/A</td><td>4.87</td><td>5.07</td><td>5.09</td><td>4.77</td><td>4.56</td><td>4.76</td><td>4.68</td><td></td></tr><tr><td>2,2,4,4-<br>Tetramethyl-<br>1,3-<br>cyclobutanediol<br>(racemate)</td><td>3010-<br>96-6</td><td>N/A</td><td>2.87</td><td>3.96</td><td>3.42</td><td>3.23</td><td>N/A</td><td>2.53</td><td>4.09</td><td>R</td></tr><tr><td>Benzeneacetic<br>acid, 4-hydroxy-<br>alpha-(4-<br>hydroxyphenyl)-<br>methyl ester</td><td>5129-<br>00-0</td><td>N/A</td><td>4.81</td><td>4.04</td><td>4.89</td><td>5.44</td><td>4.89</td><td>3.86</td><td>3.54</td><td></td></tr><tr><td>4,4'-<br>Thiodiphenol</td><td>2664-<br>63-3</td><td>N/A</td><td>N/A</td><td>N/A</td><td>N/A</td><td>N/A</td><td>N/A</td><td>4.78</td><td>3.9</td><td></td></tr><tr><td>N-(p-<br>toluenesulfonyl)<br>-N'-[3-(p-<br>toluenesulfonyloxy)<br>phenyl]urea</td><td>232938-<br>-43-1</td><td>N/A</td><td>N/A</td><td>N/A</td><td>N/A</td><td>N/A</td><td>N/A</td><td>4.52</td><td>6.11</td><td></td></tr><tr><td>4,4'-Bis(p-<br>tolylsulfonylurei<br>do)diphenylmet-<br>hane</td><td>151882-<br>-81-4</td><td>N/A</td><td>N/A</td><td>N/A</td><td>N/A</td><td>N/A</td><td>N/A</td><td>4.66</td><td>6.97</td><td></td></tr><tr><td>2,4'-<br>Dihydroxydiphe-<br>nyl sulfone</td><td>5397-<br>34-2</td><td>N/A</td><td>4.61</td><td>4.54</td><td>5.15</td><td>4.3</td><td>4.45</td><td>2.6</td><td>3.06</td><td></td></tr><tr><td>2,2',6,6'-<br>Tetrachlorobis-<br>phenol A</td><td>79-95-<br>8</td><td>N/A</td><td>6.55</td><td>7.03</td><td>6.96</td><td>6.77</td><td>4.99</td><td>4.8</td><td>3.83</td><td></td></tr></tbody></table>

P – Prediction: Reliable (Green color), Unreliable (Red color),

R – Reliability of the prediction (AD): Green (In AD), Orange (Possibly Out of AD), Red (Out of AD).

2002), in frogs (Honkanen and Kukkonen, 2006; Koponen et al., 2007)) and in fish (Wang et al., 2020; Honkanen et al., 2004). To our knowledge, only one publication has explored the bioaccumulation of the bisphenol analogues using a simple one-compartment model (Wang et al., 2020). These authors have studied bioconcentration of eight common bisphenol analogues, including bisphenol A, –B, –C, –E, –S, –Z, –AF, and –AP in common carp and calculated bioconcentration factors based on the total bisphenols. These authors suggested that

kidney and liver played important roles in accumulating bisphenols in carp, and kidney made more contribution than liver for most bisphenols. In addition, they concluded that biliary excretion predominated for elimination of most bisphenols while BPA and BPS were excreted mainly through urine (Wang et al., 2020).

In fish, several PBPK models have been used to predict the BPA bioaccumulation (Péry et al., 2014; Grech et al., 2019; Mit et al., 2022). However, only (Mit et al., 2022; Chelcea et al., 2022) are specific to this
compound and explore its ADME process. These two models were
developed based on the experimental data already published and have
also generated new data. (Mit et al., 2022) developed a PBPK model to
explore ADME of the BPA and its main metabolites: BPA-
monoglucuronide and BPA-monosulfate. These authors conclude that
the BPA ADME process was similar between stickleback, zebrafish, and
trout and that plasma or gills could be a non-negligible site of BPA
metabolization. (Chelcea et al., 2022) explored also the toxicokinetic of
bisphenol alternatives. These authors present a new dataset on the dis-
tribution of BPZ in female zebrafish, measured *in vitro* liver metabolism
for 11 alternative bisphenols and adapted a PBPK model for three of
these alternative bisphenols: BPZ, BPAF and TBBPA. This work suggests
that studied bisphenols mainly distribute to the carcass and gonads and
less to the brain. These works based on physiology do not observe a clear
role of urinary excretion for the elimination of bisphenol analogues,
contrary to the study done by (Wang et al., 2020).

4.4.3.2. *Toxicodynamic models.* Improving the environmental risk assessment of bisphenols requires a robust understanding of ecosystem functioning and population dynamics under toxicant stress, which is one of the challenges of ecological modelling (Forbes, 2009; David et al., 2019).

At the organism level, a Dynamic Energy Budget (DEB) model was
developed to simulate the effects of BPA on rainbow trout (Sadoul et al.,
2019). This modeling study utilized original experimental data to
examine various modes of action on DEB parameters. The study in-
dicates an imprinting effect of BPA on energy mobilization from reserves
(Sadoul et al., 2019).

Regarding higher biological levels such as population, community,
and ecosystem, to the best of our knowledge, only two population
models have been developed to assess the effects of BPA. These models
include a stage-structured Lefkovitch matrix model applied to mosqui-
toes (Prud'homme et al. (2017)) and an Individual-based model coupled
with a DEB model applied to a fish (three-spined stickleback) (David
et al., 2019). The population dynamic model for mosquitoes predicts
negligible consequences on the populations under two BPA exposure
scenarios (short and long-term) (Prud'homme et al. (2017)). The fish
model was developed to predict the population-level impacts and,
additionally, to provide insight on the mechanisms of BPA toxicity from
mesosocem data. Modelling results showed that direct BPA effects on fish
mainly explained the impacts on the population structure (David et al.,
2019).

4.4.4. *Conclusions and perspectives*

The review on QSAR highlights two major issues: firstly, the insuf-
ficient representation of bisphenols in the training sets, along with the
scarcity of experimental data for compounds resembling BPs. Secondly,
there is a substantial demand for comprehensive *in silico* methods that
encompass the entire group of bisphenols, including their derivatives
and alternatives. This demand stems from the significance of endpoints,
which also hold regulatory importance.

The dynamic models analyzed in the TK part of this review suggest potential variations in ADME processes among bisphenol analogues, which requires additional research to verify. Regarding the TD aspect, this review emphasizes the necessity for predictive models capable of assessing the impacts of bisphenols across various levels of biological organization, from the organism to the ecosystem.

4.5. Biological activity of bisphenols

BPA and its substitutes can be detected in a wide range of materials that can degrade and release bisphenols into the surrounding environment. Consequently, BPA alternatives have been found in diverse environmental compartments, including the atmosphere, water bodies, soil, and sediment, as discussed in Chapter 3. While the biological effects

of BPA alternatives have been studied in relation to human health, given
their presence in plastics and packaging materials that come into direct
contact with humans, it is equally important to delve into the ecological
impact of these substances in the environment. This includes a focused
investigation of their impact on the environment, particularly on the
various forms of life inhabiting it.

In the upcoming chapters, we methodically outline the existing knowledge regarding the biological effects of BPA alternatives through a wide range of model organisms and conducted exposure experiments. This synthesis aims to provide a thorough comprehension of the influence of BPA alternatives on various organisms, spanning from microbes to vertebrates, in order to assess the toxicity of these compounds and pinpoint areas where further research is needed.

4.5.1. *Microbial organisms as single species or microbiomes*

Microbial communities play a tremendous role in natural (e.g. freshwater ecosystems, soil) and host-associated ecosystems (holobiont). For instance, phototrophic organisms play a critical role in biogeochemical cycles and primary production. While microbial-based bioassays (i.e. as monoculture) have been included in regulatory hazard assessment already for a long time with standardized guidelines at ISO and OECD [e.g. ISO 8692:2012, OECD 201 (Test No. 201, 2006)], the last decade has seen the expanse of microbial ecotoxicology studies investigating the response of free-living or host-associated microbial communities as a whole (i.e. microbiome) (Duperron et al., 2020; Adamovsky et al., 2018; Ghiglione et al., 2016). Altogether, these studies could provide better insight into the potential impairment of ecosystem function and services by chemical contaminants. In this section, we specifically reviewed the effect of BPA and their derivatives on microbes as single species or more free-living complex assemblages (i.e., soil and sediment microbiomes).

4.5.1.1. *Effect on unicellular organisms.* The broadest literature about the effect of BPA on single species microbes is on microalgae in both freshwater and marine ecosystems. Indeed, as recently reviewed (Azizullah et al., 2022), many studies have shown the ability of BPA to impair the growth, photosynthesis, membrane integrity, and cellular shape of these organisms, and lead to oxidative stress. Fortunately, only few of them have reported such an impact at environmentally relevant European concentration (<10 µg/L). For instance, Chae et al. (Chae et al., 2020) highlighted that 7 days exposure of *Chlorophyceae* species to BPA in the ng/L range (from expanded polystyrene leachate) triggers an increase of the photosynthetic yield leading to growth stimulation. Also, Rabet at al. (M'Rabet et al., 2018) reported a decrease of chlorophyll *a* and cell density and of photosynthetic activity (quantum yield) in the marine dinoflagellate *Alexandrium pacificum* following 7 days exposure to 2 and/or 20 µg/L of BPA, respectively. Interestingly, the same authors did not report any effect of BPA on the diatom *Chaetoceros decipiens* following similar exposure regimes, highlighting that single species microalgal assays might not be sufficient to uncover toxicity effects. A potential explanation for this species' lack of sensitivity could relate to microalgae specific bacterial microbiome which might reduce BPA toxicity, e.g. through metabolic degradation (M'Rabet et al., 285 (2021)).

Literature on the effect of BPA derivatives on microorganisms remains very scarce. Czarny-Krzymińska et al. (Czarny-Krzymińska et al., 2022) recently investigated the toxicity of the BPAF, BPG, BPM, BPX, BPA, BPY, BPP on the green algae species, *Chlorella vulgaris* and *Desmodesmus armatus*. Here, effects were observed at quite high concentration (5–100 mg/L) and demonstrated that BPA substitutes were more actively inhibiting growth than BPA (i.e., BPG > BPX > mixture > BPAF > BPA > BPY > BPP) and that the combined exposure to BPA and its structural congeners led to synergistic effect. (Li et al., 2022) evaluated the effect of BPA, BPS and their mixture on the green algae *Chlorella pyrenoidosa* following 6 days exposure in the 1–100 mg/L range. At these
compound and explore its ADME process. These two models were
developed based on the experimental data already published and have
also generated new data. (Mit et al., 2022) developed a PBPK model to
explore ADME of the BPA and its main metabolites: BPA-
monoglucuronide and BPA-monosulfate. These authors conclude that
the BPA ADME process was similar between stickleback, zebrafish, and
trout and that plasma or gills could be a non-negligible site of BPA
metabolization. (Chelcea et al., 2022) explored also the toxicokinetic of
bisphenol alternatives. These authors present a new dataset on the dis-
tribution of BPZ in female zebrafish, measured *in vitro* liver metabolism
for 11 alternative bisphenols and adapted a PBPK model for three of
these alternative bisphenols: BPZ, BPAF and TBBPA. This work suggests
that studied bisphenols mainly distribute to the carcass and gonads and
less to the brain. These works based on physiology do not observe a clear
role of urinary excretion for the elimination of bisphenol analogues,
contrary to the study done by (Wang et al., 2020).

4.4.3.2. *Toxicodynamic models.* Improving the environmental risk assessment of bisphenols requires a robust understanding of ecosystem functioning and population dynamics under toxicant stress, which is one of the challenges of ecological modelling (Forbes, 2009; David et al., 2019).

At the organism level, a Dynamic Energy Budget (DEB) model was
developed to simulate the effects of BPA on rainbow trout (Sadoul et al.,
2019). This modeling study utilized original experimental data to
examine various modes of action on DEB parameters. The study in-
dicates an imprinting effect of BPA on energy mobilization from reserves
(Sadoul et al., 2019).

Regarding higher biological levels such as population, community,
and ecosystem, to the best of our knowledge, only two population
models have been developed to assess the effects of BPA. These models
include a stage-structured Lefkovitch matrix model applied to mosqui-
toes (Prud'homme et al. (2017)) and an Individual-based model coupled
with a DEB model applied to a fish (three-spined stickleback) (David
et al., 2019). The population dynamic model for mosquitoes predicts
negligible consequences on the populations under two BPA exposure
scenarios (short and long-term) (Prud'homme et al. (2017)). The fish
model was developed to predict the population-level impacts and,
additionally, to provide insight on the mechanisms of BPA toxicity from
mesosocem data. Modelling results showed that direct BPA effects on fish
mainly explained the impacts on the population structure (David et al.,
2019).

4.4.4. *Conclusions and perspectives*

The review on QSAR highlights two major issues: firstly, the insuf-
ficient representation of bisphenols in the training sets, along with the
scarcity of experimental data for compounds resembling BPs. Secondly,
there is a substantial demand for comprehensive *in silico* methods that
encompass the entire group of bisphenols, including their derivatives
and alternatives. This demand stems from the significance of endpoints,
which also hold regulatory importance.

The dynamic models analyzed in the TK part of this review suggest
potential variations in ADME processes among bisphenol analogues,
which requires additional research to verify. Regarding the TD aspect,
this review emphasizes the necessity for predictive models capable of
assessing the impacts of bisphenols across various levels of biological
organization, from the organism to the ecosystem.

4.5. Biological activity of bisphenols

BPA and its substitutes can be detected in a wide range of materials
that can degrade and release bisphenols into the surrounding environ-
ment. Consequently, BPA alternatives have been found in diverse
environmental compartments, including the atmosphere, water bodies,
soil, and sediment, as discussed in Chapter 3. While the biological effects

of BPA alternatives have been studied in relation to human health, given
their presence in plastics and packaging materials that come into direct
contact with humans, it is equally important to delve into the ecological
impact of these substances in the environment. This includes a focused
investigation of their impact on the environment, particularly on the
various forms of life inhabiting it.

In the upcoming chapters, we methodically outline the existing
knowledge regarding the biological effects of BPA alternatives through a
wide range of model organisms and conducted exposure experiments.
This synthesis aims to provide a thorough comprehension of the influ-
ence of BPA alternatives on various organisms, spanning from micro-
biomes to vertebrates, in order to assess the toxicity of these compounds
and pinpoint areas where further research is needed.

4.5.1. *Microbial organisms as single species or microbiomes*

Microbial communities play a tremendous role in natural (e.g. freshwater ecosystems, soil) and host-associated ecosystems (holobiont). For instance, phototrophic organisms play a critical role in biogeochemical cycles and primary production. While microbial-based bioassays (i.e. as monoculture) have been included in regulatory hazard assessment already for a long time with standardized guidelines at ISO and OECD [e.g. ISO 8692:2012, OECD 201 (Test No. 201, 2006)], the last decade has seen the expanse of microbial ecotoxicology studies investigating the response of free-living or host-associated microbial communities as a whole (i.e. microbiome) (Duperron et al., 2020; Adamovsky et al., 2018; Ghiglione et al., 2016). Altogether, these studies could provide better insight into the potential impairment of ecosystem function and services by chemical contaminants. In this section, we specifically reviewed the effect of BPA and their derivatives on microbes as single species or more free-living complex assemblages (i.e., soil and sediment microbiomes).

4.5.1.1. *Effect on unicellular organisms.* The broadest literature about the effect of BPA on single species microbes is on microalgae in both freshwater and marine ecosystems. Indeed, as recently reviewed (Azizullah et al., 2022), many studies have shown the ability of BPA to impair the growth, photosynthesis, membrane integrity, and cellular shape of these organisms, and lead to oxidative stress. Fortunately, only few of them have reported such an impact at environmentally relevant European concentration (<10 µg/L). For instance, Chae et al. (Chae et al., 2020) highlighted that 7 days exposure of *Chlorophyceae* species to BPA in the ng/L range (from expanded polystyrene leachate) triggers an increase of the photosynthetic yield leading to growth stimulation. Also, Rabet at al. (M'Rabet et al., 2018) reported a decrease of chlorophyll *a* and cell density and of photosynthetic activity (quantum yield) in the marine dinoflagellate *Alexandrium pacificum* following 7 days exposure to 2 and/or 20 µg/L of BPA, respectively. Interestingly, the same authors did not report any effect of BPA on the diatom *Chaetoceros decipiens* following similar exposure regimes, highlighting that single species microalgal assays might not be sufficient to uncover toxicity effects. A potential explanation for this species' lack of sensitivity could relate to microalgae specific bacterial microbiome which might reduce BPA toxicity, e.g. through metabolic degradation (M'Rabet et al., 285 (2021)).

Literature on the effect of BPA derivatives on microorganisms re-
mains very scarce. Czarny-Krzymińska et al. (Czarny-Krzymińska et al.,
2022) recently investigated the toxicity of the BPAF, BPG, BPM, BPX,
BPA, BPY, BPP on the green algae species, *Chlorella vulgaris* and *Des-
modesmus armatus*. Here, effects were observed at quite high concen-
tration (5–100 mg/L) and demonstrated that BPA substitutes were more
actively inhibiting growth than BPA (i.e., BPG > BPX > mixture > BPAF
> BPA > BPY > BPP) and that the combined exposure to BPA and its
structural congeners led to synergistic effect. (Li et al., 2022) evaluated
the effect of BPA, BPS and their mixture on the green algae *Chlorella
pyrenoidosa* following 6 days exposure in the 1–100 mg/L range. At these
concentrations, both compounds caused inhibition of growth (cell density) and chlorophyll a biosynthesis while inducing oxidative stress as determined by measuring increased levels of ROS, a modulation of MDA (malondialdehyde) content and the induction of SOD (superoxide dismutase) and peroxidases activity. This study also highlighted an overall synergistic effect of the combination of BPA and BPS. Finally, there is also evidence that BPA and its derivatives can have anti-cyanobacterial activity. Indeed, Czarny et al. (Czarny et al., 2021) reported a reduced chlorophyll a content and growth in *Anabaena variabilis* and *Microcystis aeruginosa* following a 14 days exposure to BPA, BPAF, BPB, BPBP, BPC, BPE and their mixture in the 1–100 mg/L range. Also, they highlighted that some of the analogues were more active than BPA with a ranking of the effect magnitude that is species-dependent: BPAF > BPC > BPB > BPA > BPE > BPBP for *Anabaena variabilis* and BPB > BPAF > BPC > BPA > BPE > BPBP for *Microcystis aeruginosa*.

### 4.5.1.2. Effect on free-living microbiomes.
Beyond the effects on host-associated microbiomes, there is also recent evidence that BPA and its substitutes impair the functioning and biodiversity of environmental microbiomes. Almost 10 years ago, Yang et al. 2014 (Yang et al., 2014) demonstrated that BPA decreased bacterial community diversity in sediments, likely by promoting the growth of tolerant species capable of degrading the chemical. More recently, Zaborowska et al. 2020 (Zaborowska et al., 2020) evaluated the response of soil microbiomes to BPA, BPF and BPS at both the functional (i.e., enzymatic activities) and structural (i.e. counts and diversity of bacteria) levels. They demonstrated that all tested bisphenols altered both the bacterial composition (e.g., reduction of *Proteobacteria* and increase of *Actinobacteria*) within soil as well as modulated bacterial enzymatic activities (i.e., mainly arylsulphatase and urease) as a function of exposure time and bisphenol diversity. This revealed that BPF was more active towards soil microbiomes than BPS and BPA. Finally, by using metagenomics, Tong et al. 2021 (Tong et al., 2021) demonstrated similar structural shifts (i.e., decreasing diversity and richness) and associated changes in the functional potential of soil communities following 28 days exposure to BPA. This revealed that the pattern of response, as well as the biodegradation capacity towards BPA, differed according to soil types (i.e., various mangrove rhizosphere soils vs. unplanted soil).

Together, these findings highlight that environmental and host-associated microbiomes are impacted by bisphenols at both the functional and structural level, which might lead to unanticipated impacts on ecosystem functioning and associated services. Thus, we advocate that microbes and their communities should be integrated into standard hazard assessment workflows. To this end, already available protocols could be used to routinely monitor the impact of BPA and its alternatives on the physiology, functioning and structure of microorganisms including host-associated microorganisms (Guasch et al., 2017; Birrer et al., 2017; Adamovsky et al., 2020). Finally, the development of additional cutting-edge assessment methods (e.g. omics, high throughput microphysiology) will help facilitate the rapid testing and monitoring of exposure effects on microorganisms of importance to ecosystems and human health.

### 4.5.2. Invertebrates

One of the priorities at European level as presented in Chemicals Strategy for Sustainability and other policy documents is to ensure that the endocrine disruptive substances are recognized in a timely manner and that exposure of humans, and the environment is minimized. One of the means to achieve this goal is the development and uptake of methods to generate information on endocrine disruptors through screening and testing of chemicals. In addition, the need for the development of new methods for the identification of possible adverse effects on endocrine system of specific categories of organisms, mainly invertebrates, has been highlighted by EFSA (European Food Safety Authority), ECHA (European Chemicals Agency) and other relevant authorities with the

technical support of the Joint Research Centre (JRC). In the Final Report of the State-of-the-Art Assessment of Endocrine Disruptors (Kortenkamp et al., 2011), it is highlighted that biotests with invertebrates offer some advantages over vertebrate models, namely due to the fact that there are fewer ethical considerations, doses are easier to deliver precisely in aquatic species, and their small size and inexpensive maintenance requirements allow larger datasets to be collected. Although some of them have been explored so far, invertebrate models have much to offer in terms of investigating EDC effects relevant to vertebrates and as eco-toxicological models for screening chemicals for potential ED properties. Many endocrine pathways are evolutionary well-conserved, and despite existing knowledge gaps, in particular for most invertebrate phyla, it is clear that there are structural and functional commonalities across vertebrate and invertebrate taxa. However, the endocrine system of invertebrates is different than for vertebrates (Fodor et al., 2022), which suggests also other targets for endocrine disruption, and well-known vertebrate EDCs may interfere with the development, reproduction and endocrine system of invertebrates via other pathways than the estrogen, androgen, thyroid and steroidogenesis pathways e.g. the retinoid-signaling pathway. How vertebrate EDCs affect most invertebrate taxa is largely unknown. Better understanding of the effects of EDCs on invertebrates could not only help better protect invertebrates in the environment, but also permit future extrapolation of knowledge across species and thereby help reduce the need for vertebrate testing. Therefore, in this chapter the current state of knowledge regarding the toxicity of BPA and its alternatives on invertebrates has been reviewed and is presented in Supp.info 5 (Table 1) with the aim to identify possible gaps in their toxicity assessment with classic (standardized) methods and development of NAMs. Based on the review of more than 70 publications (listed in the Supp.info 5 (Table 1), our investigation identified that most of the available data still refers mostly to BPA (~80 %), and only 16 BPA alternatives have been toxicologically evaluated towards different invertebrate species so far. It might be also concluded (similarly to the data referring to vertebrate models) that BPA alternatives have not been studied systematically. For example, there is a lack of systematic approach in terms of the evaluation of a specific endpoint. The effects of BPA alternatives are also unequally investigated. Three BPA alternatives that were studied most commonly are BPS (22 %), BPF (14 %), and BPAF (6 %).

This highlights the gaps in the ecotoxicity assessment of BPA alternatives. Detailed information is presented in the following sub-sections referring to the specific groups of invertebrates.

#### 4.5.2.1. Terrestrial and aquatic insects.
Insects are the most common animals on earth with more than 80 % of animal species being insects. Insects are of high importance to terrestrial and aquatic ecosystems since they are involved in a series of essential processes related to ecosystem maintenance e.g. pollination, decomposition and nutrient recycling, soil formation, etc. In addition, insects play a critical role in food webs and as predators provide natural population control of other insects, arthropods and other invertebrates (Redak, 2023). Therefore, there is a growing concern as regards the global decline in insect biodiversity and the possible adverse effects caused by several parameters (including the environmental chemical pollution) on insects' survival, reproduction and on different systems (e.g. endocrine system).

So far, endocrine disruptive effects on invertebrates and specifically on arthropods/insects were only assessed through reproduction studies that do not specifically address ED related endpoints. In parallel, certain chemicals that are emerging environmental contaminants like some BPA alternatives have been shown to exhibit adverse effects on the endocrine and immune system, on reproduction and metabolism of invertebrates, and therefore further investigation is required. As regards the endocrine system, several studies were focused on the effects on ecdysis. Ecdysis is the process of an arthropod moulting its exoskeleton. Moulting is necessary as the arthropod exoskeleton is inflexible and so, to grow
concentrations, both compounds caused inhibition of growth (cell density) and chlorophyll a biosynthesis while inducing oxidative stress as determined by measuring increased levels of ROS, a modulation of MDA (malondialdehyde) content and the induction of SOD (superoxide dismutase) and peroxidases activity. This study also highlighted an overall synergistic effect of the combination of BPA and BPS. Finally, there is also evidence that BPA and its derivatives can have anti-cyanobacterial activity. Indeed, Czarny et al. (Czarny et al., 2021) reported a reduced chlorophyll a content and growth in *Anabaena variabilis* and *Microcystis aeruginosa* following a 14 days exposure to BPA, BPAF, BPB, BPBP, BPC, BPE and their mixture in the 1–100 mg/L range. Also, they highlighted that some of the analogues were more active than BPA with a ranking of the effect magnitude that is species-dependent: BPAF > BPC > BPB > BPA > BPE > BPBP for *Anabaena variabilis* and BPB > BPAF > BPC > BPA > BPE > BPBP for *Microcystis aeruginosa*.

### 4.5.1.2. Effect on free-living microbiomes.
Beyond the effects on host-associated microbiomes, there is also recent evidence that BPA and its substitutes impair the functioning and biodiversity of environmental microbiomes. Almost 10 years ago, Yang et al. 2014 (Yang et al., 2014) demonstrated that BPA decreased bacterial community diversity in sediments, likely by promoting the growth of tolerant species capable of degrading the chemical. More recently, Zaborowska et al. 2020 (Zaborowska et al., 2020) evaluated the response of soil microbiomes to BPA, BPF and BPS at both the functional (i.e., enzymatic activities) and structural (i.e. counts and diversity of bacteria) levels. They demonstrated that all tested bisphenols altered both the bacterial composition (e.g., reduction of *Proteobacteria* and increase of *Actinobacteria*) within soil as well as modulated bacterial enzymatic activities (i.e., mainly arylsulphatase and urease) as a function of exposure time and bisphenol diversity. This revealed that BPF was more active towards soil microbiomes than BPS and BPA. Finally, by using metagenomics, Tong et al. 2021 (Tong et al., 2021) demonstrated similar structural shifts (i.e., decreasing diversity and richness) and associated changes in the functional potential of soil communities following 28 days exposure to BPA. This revealed that the pattern of response, as well as the biodegradation capacity towards BPA, differed according to soil types (i.e., various mangrove rhizosphere soils vs. unplanted soil).

Together, these findings highlight that environmental and host-associated microbiomes are impacted by bisphenols at both the functional and structural level, which might lead to unanticipated impacts on ecosystem functioning and associated services. Thus, we advocate that microbes and their communities should be integrated into standard hazard assessment workflows. To this end, already available protocols could be used to routinely monitor the impact of BPA and its alternatives on the physiology, functioning and structure of microorganisms including host-associated microorganisms (Guasch et al., 2017; Birrer et al., 2017; Adamovsky et al., 2020). Finally, the development of additional cutting-edge assessment methods (e.g. omics, high throughput microphysiology) will help facilitate the rapid testing and monitoring of exposure effects on microorganisms of importance to ecosystems and human health.

### 4.5.2. Invertebrates

One of the priorities at European level as presented in Chemicals Strategy for Sustainability and other policy documents is to ensure that the endocrine disruptive substances are recognized in a timely manner and that exposure of humans, and the environment is minimized. One of the means to achieve this goal is the development and uptake of methods to generate information on endocrine disruptors through screening and testing of chemicals. In addition, the need for the development of new methods for the identification of possible adverse effects on endocrine system of specific categories of organisms, mainly invertebrates, has been highlighted by EFSA (European Food Safety Authority), ECHA (European Chemicals Agency) and other relevant authorities with the

technical support of the Joint Research Centre (JRC). In the Final Report of the State-of-the-Art Assessment of Endocrine Disruptors (Kortenkamp et al., 2011), it is highlighted that biotests with invertebrates offer some advantages over vertebrate models, namely due to the fact that there are fewer ethical considerations, doses are easier to deliver precisely in aquatic species, and their small size and inexpensive maintenance requirements allow larger datasets to be collected. Although some of them have been explored so far, invertebrate models have much to offer in terms of investigating EDC effects relevant to vertebrates and as ecotoxicological models for screening chemicals for potential ED properties. Many endocrine pathways are evolutionary well-conserved, and despite existing knowledge gaps, in particular for most invertebrate phyla, it is clear that there are structural and functional commonalities across vertebrate and invertebrate taxa. However, the endocrine system of invertebrates is different than for vertebrates (Fodor et al., 2022), which suggests also other targets for endocrine disruption, and well-known vertebrate EDCs may interfere with the development, reproduction and endocrine system of invertebrates via other pathways than the estrogen, androgen, thyroid and steroidogenesis pathways e.g. the retinoid-signaling pathway. How vertebrate EDCs affect most invertebrate taxa is largely unknown. Better understanding of the effects of EDCs on invertebrates could not only help better protect invertebrates in the environment, but also permit future extrapolation of knowledge across species and thereby help reduce the need for vertebrate testing. Therefore, in this chapter the current state of knowledge regarding the toxicity of BPA and its alternatives on invertebrates has been reviewed and is presented in Supp.info 5 (Table 1) with the aim to identify possible gaps in their toxicity assessment with classic (standardized) methods and development of NAMs. Based on the review of more than 70 publications (listed in the Supp.info 5 (Table 1), our investigation identified that most of the available data still refers mostly to BPA (~80 %), and only 16 BPA alternatives have been toxicologically evaluated towards different invertebrate species so far. It might be also concluded (similarly to the data referring to vertebrate models) that BPA alternatives have not been studied systematically. For example, there is a lack of systematic approach in terms of the evaluation of a specific endpoint. The effects of BPA alternatives are also unequally investigated. Three BPA alternatives that were studied most commonly are BPS (22 %), BPF (14 %), and BPAF (6 %).

This highlights the gaps in the ecotoxicity assessment of BPA alternatives. Detailed information is presented in the following sub-sections referring to the specific groups of invertebrates.

#### 4.5.2.1. Terrestrial and aquatic insects.
Insects are the most common animals on earth with more than 80 % of animal species being insects. Insects are of high importance to terrestrial and aquatic ecosystems since they are involved in a series of essential processes related to ecosystem maintenance e.g. pollination, decomposition and nutrient recycling, soil formation, etc. In addition, insects play a critical role in food webs and as predators provide natural population control of other insects, arthropods and other invertebrates (Redak, 2023). Therefore, there is a growing concern as regards the global decline in insect biodiversity and the possible adverse effects caused by several parameters (including the environmental chemical pollution) on insects' survival, reproduction and on different systems (e.g. endocrine system).

So far, endocrine disruptive effects on invertebrates and specifically on arthropods/insects were only assessed through reproduction studies that do not specifically address ED related endpoints. In parallel, certain chemicals that are emerging environmental contaminants like some BPA alternatives have been shown to exhibit adverse effects on the endocrine and immune system, on reproduction and metabolism of invertebrates, and therefore further investigation is required. As regards the endocrine system, several studies were focused on the effects on ecdysis. Ecdysis is the process of an arthropod moulting its exoskeleton. Moulting is necessary as the arthropod exoskeleton is inflexible and so, to grow
larger, arthropods must moult. Therefore, successful moulting/ecdysis is a critical event for the development, survival and reproduction of arthropods. Ecdysis is controlled by complex multi-hormone systems and therefore it can be affected by endocrine disruptive chemicals (EDCs).

More specifically, for example, exposure to environmentally relevant concentrations of BPA during the early stages of the housefly *Musca domestica* life cycle variously affects its development. The observed effects (i.e. alteration in pupal weight, sex ratio, and levels of juvenile hormones) were related to endocrine disruption (Izumi et al., 2008). Several studies indicate that BPA interferes with the ecdysteroidal pathways of the lepidopteran insect species. BPA exhibits ecdysone agonistic activity and causes developmental delay, alterations in pupal and larval weight, decreased adult emergence and malting malformations during development and metamorphosis (Kontogiannatos et al., 2015; Kontogiannatos et al., 2015). These effects were correlated with modification of expression of various genes involved in ecdysis process: EcR, USP, E75AB, E75D, Br-c (Maria et al., 2019), SnEcR and SnUSP (Kontogiannatos et al., 2015), SnoHsc70 (Kontogiannatos et al., 2015), SnoHsp19.5, SnoHsp20.8, SnoHsp83 (Michail et al., 2012).

BPA exhibits endocrine disruptive effects also on *Drosophila melanogaster* by affecting endocrine signaling through disrupting hormone levels and/or gene expression levels of hormone receptor or signaling pathways controlled by these hormones (Frat et al., 2023; Weiner et al., 2014). Besides the ED related effects, BPA induces gastrointestinal toxicity in *D. melanogaster* (Chen et al., 2022) and was involved in the regulation of metabolic pathways, behavioral patterns, stress response, endocrine homeostasis, neural functioning, and the development of specific organs in *Drosophila* (Begum et al., 2021). In *Culex quinquefasciatus*, BPA treatment caused decrease of the time for embryonic and larval development. More specifically, BPA caused a dose-dependent increase of 20-hydroxyecdysone (20-E) peaks, phospholipase A2 induction and upregulation of ecdysone receptor gene, EcRA, and ecdysone inducible gene E75A, which results in early pupation (Valsala and Asirvadam, 2022).

BPA and other bisphenols also affect aquatic insects. More specifically, exposure to sublethal concentrations of BPA causes delayed moulting and decreased larval wet weight in *Chironomus riparius* (Watts et al., 2003). In addition, BPP alters embryo hatching, larval emergence, and adult sex ratio at concentrations close to the effective concentrations for hormonal genetic endpoints in embryos and larvae after 48 h of exposure (Wang et al., 2019). BPA and other bisphenols also affect the expression of genes involved in the endocrine and other systems of aquatic insects. In *C. riparius*, BPS causes alteration in several genes related to the ecdysone pathway and metabolism (EcR, ERR, E74, cyp18a1, swadow) and other genes crucial for insect development and metamorphosis, stress and biotransformation mechanism (hsp70, hsp40, cyp4g, GPx and GST) (Herrero et al., 2018; Morales et al., 2020). Other studies indicate that EcR and E93 were statistically significantly upregulated in response to BPA, while in parallel reduced transcription of JHamt and DECAY genes was observed (Muniz-González and Martínez-Guitarte, 2020).

Besides the endocrine system, BPA was found to have genotoxic activity on *C. riparius* as demonstrated by tests other than basic eco-toxicity assays, i.e. comet investigating DNA damage eco-epigenetics (global DNA and histone methylations) and non-targeted global metabolomics (NMR based) approaches (Lee et al., 2018; Martínez-Paz et al., 2013).

In conclusion, there are several indications that BPA and BPA alternatives influence the endocrine system of insects through affecting the ecdysis pathway. Therefore, these results highlight the need for the development of methods to include not only morphological assessment but also molecular, analytical and omics techniques to identify molecular markers for the assessment of the possible adverse effects on an insect's endocrine system. These molecular markers can also be used to enrich the existing adverse outcome pathways (AOPs) or/and to develop new AOPs related to the ecdysis process in invertebrates.

#### 4.5.2.2. Mollusks.
Mollusca is the second-largest invertebrate phylum consisting of > 85,000 species, whereof 80% are gastropods. Combined with their commercial and ecological importance and their use as bio-monitoring organisms, this phylum has gained particular research focus among invertebrates. Mollusks could offer predictive capabilities for understanding effects of chemicals in vertebrates as they have closer evolutionary relationships with vertebrates than other protostome invertebrates such as the arthropods (Rosenberg, 2014).

Two mollusk species, both being freshwater gastropods, are used as model species in OECD test guidelines (TG); the New Zealand mud snail (*Potamopyrgus antipodarum*) in TG 242 and the great pond snail (*Lymnaea stagnalis*) in TG 243. Both TGs were adopted in 2016 and are 28-days toxicity and reproduction tests with sexually mature snails, but without endocrine specific endpoints. Therefore, major gaps remain in understanding the role and function of the endocrine system in e.g., development and reproduction in mollusks and how pollutants interfere with endocrine pathways. Thus, the mechanisms of endocrine disruption and the relationships to hormonal changes and reproduction disturbances are not fully clear yet. Vertebrate nuclear receptor (NR) orthologues such as ER and TR have been identified in mollusks including gastropods. However, evolutionary changes in binding specificities and activation profiles of NRs are well-known as structure is better conserved than function. For example, accumulating evidence suggests that the mollusk estrogen receptor (ER) is unable to bind vertebrate-type estrogen (E2) and has its function as a constitutively active transcription receptor (Keay et al., 2006). Hence, the actual functionality of the molluscan ER *in vivo* still needs clarification. Although mollusks can capture, store, and metabolize vertebrate-type steroid hormones, there is no conclusive evidence that they can synthesize vertebrate-type steroid hormones endogenously (Scott, 2012), and in contrast to fish, yolk protein is not induced by vertebrate E2 or EE2 in bivalves (Fernández-González et al., 2020; Morthorst et al., 2014). It has been suggested that estrogens could act through non-genomic signaling pathways in bivalves (Balbi et al., 2019).

Due to a fairly well-characterized reproduction, development, and nervous system, *L. stagnalis* is both a well-established multipurpose model within neuroscience and evolutionary biology, and a promising mollusk model organism in ecotoxicology (Fodor et al., 2020). *L. stagnalis* is a freshwater hermaphroditic snail commonly found in Europe and North America (Fodor et al., 2020) and it is easily maintained under laboratory conditions. The snails are hermaphrodites that reach sexual maturity a few months after hatch and can produce high numbers of offspring all year round. The embryonic development is easily studied due to large and transparent individual eggs within a transparent egg cocoon. The species is thus well suited for assessing developmental and reproductive toxicity of chemicals. There is a need for standardized assessment of chemical toxicity, especially for early life stages such as embryos as they are often more sensitive, which is also the case for BPA. Therefore, *L. stagnalis* (adults and embryos) is used for NAM development within PARC. However, some biological areas need further research to fully understand and utilize the full potential of *L. stagnalis*. The genome of *L. stagnalis* has not yet been fully characterized, and there is a need for further genome identification which can allow for knowledge and development of molecular toxicity biomarkers. Consistently, there are very few studies using "omics" techniques for assessment of chemical toxicity in *L. stagnalis*. In addition, other biomarkers reflecting the organism health, such as biochemical, histological, morphological, behavioral, and physiological measures, should be further explored as well.

BPA and BPA alternatives have been detected in mollusks in the environment in the ng/g tissue range (Baralla et al., 2021). The literature concerning the effects of BPA on mollusks was comprehensively analyzed in the support document for identification of BPA as a Substance of Very High Concern (SVHC) based on endocrine disruptive properties (ANSES, 2017). Embryo malformations, increased egg production, induction of super females and malformations of genital tissue
larger, arthropods must moult. Therefore, successful moulting/ecdysis is a critical event for the development, survival and reproduction of arthropods. Ecdysis is controlled by complex multi-hormone systems and therefore it can be affected by endocrine disruptive chemicals (EDCs).

More specifically, for example, exposure to environmentally relevant concentrations of BPA during the early stages of the housefly *Musca domestica* life cycle variously affects its development. The observed effects (i.e. alteration in pupal weight, sex ratio, and levels of juvenile hormones) were related to endocrine disruption (Izumi et al., 2008). Several studies indicate that BPA interferes with the ecdysteroidal pathways of the lepidopteran insect species. BPA exhibits ecdysone agonistic activity and causes developmental delay, alterations in pupal and larval weight, decreased adult emergence and malting malformations during development and metamorphosis (Kontogiannatos et al., 2015; Kontogiannatos et al., 2015). These effects were correlated with modification of expression of various genes involved in ecdysis process: EcR, USP, E75AB, E75D, Br-c (Maria et al., 2019), SnEcR and SnUSP (Kontogiannatos et al., 2015), SnoHsc70 (Kontogiannatos et al., 2015), SnoHsp19.5, SnoHsp20.8, SnoHsp83 (Michail et al., 2012).

BPA exhibits endocrine disruptive effects also on *Drosophila melanogaster* by affecting endocrine signaling through disrupting hormone levels and/or gene expression levels of hormone receptor or signaling pathways controlled by these hormones (Frat et al., 2023; Weiner et al., 2014). Besides the ED related effects, BPA induces gastrointestinal toxicity in *D. melanogaster* (Chen et al., 2022) and was involved in the regulation of metabolic pathways, behavioral patterns, stress response, endocrine homeostasis, neural functioning, and the development of specific organs in *Drosophila* (Begum et al., 2021). In *Culex quinquefasciatus*, BPA treatment caused decrease of the time for embryonic and larval development. More specifically, BPA caused a dose-dependent increase of 20-hydroxyecdysone (20-E) peaks, phospholipase A2 induction and upregulation of ecdysone receptor gene, EcRA, and ecdysone inducible gene E75A, which results in early pupation (Valsala and Asirvadam, 2022).

BPA and other bisphenols also affect aquatic insects. More specifically, exposure to sublethal concentrations of BPA causes delayed moulting and decreased larval wet weight in *Chironomus riparius* (Watts et al., 2003). In addition, BPP alters embryo hatching, larval emergence, and adult sex ratio at concentrations close to the effective concentrations for hormonal genetic endpoints in embryos and larvae after 48 h of exposure (Wang et al., 2019). BPA and other bisphenols also affect the expression of genes involved in the endocrine and other systems of aquatic insects. In *C. riparius*, BPS causes alteration in several genes related to the ecdysone pathway and metabolism (EcR, ERR, E74, cyp18a1, swadow) and other genes crucial for insect development and metamorphosis, stress and biotransformation mechanism (hsp70, hsp40, cyp4g, GPx and GST) (Herrero et al., 2018; Morales et al., 2020). Other studies indicate that EcR and E93 were statistically significantly upregulated in response to BPA, while in parallel reduced transcription of JHamt and DECAY genes was observed (Muniz-González and Martínez-Guitarte, 2020).

Besides the endocrine system, BPA was found to have genotoxic activity on *C. riparius* as demonstrated by tests other than basic eco-toxicity assays, i.e. comet investigating DNA damage eco-epigenetics (global DNA and histone methylations) and non-targeted global metabolomics (NMR based) approaches (Lee et al., 2018; Martínez-Paz et al., 2013).

In conclusion, there are several indications that BPA and BPA alternatives influence the endocrine system of insects through affecting the ecdysis pathway. Therefore, these results highlight the need for the development of methods to include not only morphological assessment but also molecular, analytical and omics techniques to identify molecular markers for the assessment of the possible adverse effects on an insect's endocrine system. These molecular markers can also be used to enrich the existing adverse outcome pathways (AOPs) or/and to develop new AOPs related to the ecdysis process in invertebrates.

#### 4.5.2.2. Mollusks.
Mollusca is the second-largest invertebrate phylum consisting of > 85,000 species, whereof 80% are gastropods. Combined with their commercial and ecological importance and their use as bio-monitoring organisms, this phylum has gained particular research focus among invertebrates. Mollusks could offer predictive capabilities for understanding effects of chemicals in vertebrates as they have closer evolutionary relationships with vertebrates than other protostome invertebrates such as the arthropods (Rosenberg, 2014).

Two mollusk species, both being freshwater gastropods, are used as model species in OECD test guidelines (TG); the New Zealand mud snail (*Potamopyrgus antipodarum*) in TG 242 and the great pond snail (*Lymnaea stagnalis*) in TG 243. Both TGs were adopted in 2016 and are 28-days toxicity and reproduction tests with sexually mature snails, but without endocrine specific endpoints. Therefore, major gaps remain in understanding the role and function of the endocrine system in e.g., development and reproduction in mollusks and how pollutants interfere with endocrine pathways. Thus, the mechanisms of endocrine disruption and the relationships to hormonal changes and reproduction disturbances are not fully clear yet. Vertebrate nuclear receptor (NR) orthologues such as ER and TR have been identified in mollusks including gastropods. However, evolutionary changes in binding specificities and activation profiles of NRs are well-known as structure is better conserved than function. For example, accumulating evidence suggests that the mollusk estrogen receptor (ER) is unable to bind vertebrate-type estrogen (E2) and has its function as a constitutively active transcription receptor (Keay et al., 2006). Hence, the actual functionality of the molluscan ER *in vivo* still needs clarification. Although mollusks can capture, store, and metabolize vertebrate-type steroid hormones, there is no conclusive evidence that they can synthesize vertebrate-type steroid hormones endogenously (Scott, 2012), and in contrast to fish, yolk protein is not induced by vertebrate E2 or EE2 in bivalves (Fernández-González et al., 2020; Morthorst et al., 2014). It has been suggested that estrogens could act through non-genomic signaling pathways in bivalves (Balbi et al., 2019).

Due to a fairly well-characterized reproduction, development, and nervous system, *L. stagnalis* is both a well-established multipurpose model within neuroscience and evolutionary biology, and a promising mollusk model organism in ecotoxicology (Fodor et al., 2020). *L. stagnalis* is a freshwater hermaphroditic snail commonly found in Europe and North America (Fodor et al., 2020) and it is easily maintained under laboratory conditions. The snails are hermaphrodites that reach sexual maturity a few months after hatch and can produce high numbers of offspring all year round. The embryonic development is easily studied due to large and transparent individual eggs within a transparent egg cocoon. The species is thus well suited for assessing developmental and reproductive toxicity of chemicals. There is a need for standardized assessment of chemical toxicity, especially for early life stages such as embryos as they are often more sensitive, which is also the case for BPA. Therefore, *L. stagnalis* (adults and embryos) is used for NAM development within PARC. However, some biological areas need further research to fully understand and utilize the full potential of *L. stagnalis*. The genome of *L. stagnalis* has not yet been fully characterized, and there is a need for further genome identification which can allow for knowledge and development of molecular toxicity biomarkers. Consistently, there are very few studies using "omics" techniques for assessment of chemical toxicity in *L. stagnalis*. In addition, other biomarkers reflecting the organism health, such as biochemical, histological, morphological, behavioral, and physiological measures, should be further explored as well.

BPA and BPA alternatives have been detected in mollusks in the environment in the ng/g tissue range (Baralla et al., 2021). The literature concerning the effects of BPA on mollusks was comprehensively analyzed in the support document for identification of BPA as a Substance of Very High Concern (SVHC) based on endocrine disruptive properties (ANSES, 2017). Embryo malformations, increased egg production, induction of super females and malformations of genital tissue