# New approach methodologies in human health risk assessment across European regulatory frameworks: Status quo, barriers and drivers for regulatory acceptance and use

Angela Bearth, Nicolas Roth, Tom Jansen, Laura Holden, Aleksandra Čavoški, Emma Di Consiglio, Ingrid Hauzenberger, Robert Lee, Enrico Mombelli, Olga Tcheremenskaia, et al.

► To cite this version:

Angela Bearth, Nicolas Roth, Tom Jansen, Laura Holden, Aleksandra Čavoški, et al. New approach methodologies in human health risk assessment across European regulatory frameworks: Status quo, barriers and drivers for regulatory acceptance and use. Environment International, 2025, 196, pp.109279. 10.1016/j.envint.2025.109279. hal-05036333

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# New approach methodologies in human health risk assessment across European regulatory frameworks: Status quo, barriers and drivers for regulatory acceptance and use

Angela Earth<sup>a, *, †</sup>, Nicolas Roth<sup>a †</sup>, Tom Jansen<sup>b †</sup>, Laura Holden<sup>c †</sup>, Aleksandra Čavoški<sup>c</sup>,
Emma Di Consiglio<sup>d</sup>, Ingrid Hauzenberger<sup>e</sup>, Robert Lee<sup>c</sup>, Enrico Mombelli<sup>f</sup>,
Olga Tcheremenskaia<sup>d</sup>, Lina Wendt-Rasch<sup>g</sup>, Martin F. Wilks<sup>a</sup>

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

ARTICLE INFO

Handling Editor: Olga Kalantzi

Keywords:

Next Generation Risk Assessment

New Approach Methodologies

Chemical regulation

Barriers

Drivers

Perspectives

Social science

Survey

A B S T R A C T

The traditional approaches to chemical risk assessment for human health are continuously challenged by their limitations, such as validity concerns, societal pressure to use animal-free methods, and resource constraints. New Approach Methodologies (NAMs) are considered a promising avenue toward modernisation of chemical risk assessment practices but their implementation in practice has been slow. This article aims to investigate the perspectives of human health risk assessors on the status quo, barriers and drivers of the acceptance and use of NAMs across different regulatory frameworks. A mixed method design was applied: qualitative interviews (N = 19) and an online survey with human health risk assessors from industry, regulatory agencies/institutions and academia (N = 222). The results show heterogeneity in familiarity and use of specific NAMs (e.g., QSARs as well-known and used vs. —omics approaches that are seldom used), the risk assessors' background (e.g., industry vs. regulatory agencies and institutions vs. academia) and the application context (e.g., screening/prioritisation vs. hazard identification/characterisation). The identified barriers and drivers offer pointers for the future integration and acceptance of NAMs in regulatory risk assessment. For instance, guidance documents can facilitate the use of NAMs, showcasing successful examples that increase trust in the methods and thus, the risk assessors' confidence in using these methods. Among other things, the article highlights the importance of considering human health risk assessors' needs and prerequisites to foster bottom-up coordinated efforts and to ensure the success of top-down legal and institutional change to incorporate NAMs in regulatory risk assessment.

Abbreviations: 3R, Replacement, Reduction, Refinement; AOPs, Adverse Outcome Pathways; BPR, Biocidal Products Regulation; CLP, Classification, Labelling and Packaging Regulation; DA, Defined Approaches; DASS, Defined Approaches on Skin Sensitization; DST, Dempster-Shafer Theory; EPAA, European Partnership for Alternative Approaches to Animal Testing; EURL ECVAM, EU Reference Laboratory on Alternatives to Animal Testing; GD, Guidance Document; HTS, High-Throughput Screening; IATA, Integrated Approaches to Testing and Assessment; ICH, International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use; IVIVE, In Vitro to In Vivo Extrapolation; NAM, New Approach Methodologies; NGO, Non-Governmental Organizations; NGRA, Next-Generation Risk Assessment; NPO, Non-Profit Organizations; OECD, Organisation for Economic Co-Operation and Development; PARC, European Partnership for the Assessment of Risks from Chemicals; PARERE, EURL ECVAM Network for Preliminary Assessment of Regulatory Relevance; PB(P)K, Physiology-Based (Pharmaco-) Kinetic Modelling; PPP, Plant Protection Products Regulation; QAF, QSAR Assessment Framework; QSAR, Quantitative Structure-Activity Relationship; RAAF, Read-Across Assessment Framework; REACH, Regulation on the Registration, Evaluation, Authorisation and Restriction of Chemicals; TGs, Test Guidelines.

* Corresponding author at: Missionsstrasse 64 4055, Basel, Switzerland.

E-mail address: angela.bearth@unibas.ch (A. Earth).

<footnote><sup>a</sup> Swiss Centre for Applied Human Toxicology, and Department of Pharmaceutical Sciences, University of Basel, Basel, Switzerland</footnote>

<footnote><sup>b</sup> National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands</footnote>

<footnote><sup>c</sup> University of Birmingham, Birmingham Law School, Birmingham, United Kingdom</footnote>

<footnote><sup>d</sup> Italian National Institute of Health, Istituto Superiore di Sanità (ISS), Department of Environment and Health, Rome, Italy</footnote>

<footnote><sup>e</sup> Environment Agency Austria (Umweltbundesamt GmbH), Spittelauer Laende 5 1090, Vienna, Austria</footnote>

<footnote><sup>f</sup> French National Institute for Industrial Environment and Risks (INERIS), Verneuil-en-Halatte Parc Technologique ALATA BP 2, Verneuil-en-Halatte, France</footnote>

<footnote><sup>g</sup> Swedish Chemicals Agency, Stockholm, Sweden</footnote>
# 1. Introduction

The traditional paradigms and methodologies in chemical risk assessment for human health are continuously challenged by a multitude of factors, among them resource constraints, scientific limitations concerning human relevance of data produced by studies on animals or real-life chemical mixtures and societal pressure to move rapidly away from animal studies. Increasingly, New Approach Methodologies (NAMs) are brought forward as a promising avenue toward modernisation of chemical risk assessment practices (Krebs et al., 2020; Madden, Enoch, Paini, & Cronin, 2020; Schmeisser et al., 2023). Working definitions of NAMs have been proposed by various authorities and institutions at European and international level (European Chemicals Agency, 2016; European Food Safety Authority et al., 2022; National Academies of Sciences, 2023; Nordic Council of Ministers, 2021; OECD, 2020; United States Environmental Protection Agency, 2018). In line with these definitions, NAMs could comprise various strategies, methods and combinations of methods, such as *in silico* (predictive computer) models, e.g., Quantitative-Structure-Activity Relationships (QSARs), grouping and read-across approaches; or *in vitro* assays, that could be used in Integrated Approaches to Testing and Assessment (IATA); Defined Approaches (DAs); or to build Adverse Outcome Pathways (AOPs), sometimes in combination with *in vivo* tests (Schmeisser et al., 2023).

NAMs have the potential to provide human-relevant information for safety and exposure assessment and could be faster and more efficient than *in vivo* tests (e.g., Schmeisser et al., 2023; Westmoreland et al., 2022). However, the use of NAMs for regulatory decision-making is met with various legal and regulatory, scientific, technical and societal barriers (Ball et al., 2022; Mondou et al., 2020; Sewell et al., 2024; Westmoreland et al., 2022). The general conclusion is that the current legal and regulatory requirements have been developed and optimised for animal testing (Schmeisser et al., 2023; Stucki et al., 2022; van der Zalm et al., 2022). However, the perspectives of human health risk assessors in companies, regulatory agencies and institutions and at universities (subsequently called “industry, regulation and academia” for reader friendliness) specifically about the acceptance, barriers and use of NAMs, have received little attention so far. Equally, an overview of how and to what extent NAMs are currently applied for use in chemical risk assessment across regulatory sectors and application contexts is limited. This article aims to fill these gaps and contribute to the ongoing efforts to facilitate the integration of NAMs into the regulatory landscape and risk assessment workflow and practice.

# 2. Theoretical background

Based on changing policy, such as the recently published Chemical Strategy for Sustainability (European Commission, 2020), successful implementation and use of NAMs demands a joint effort from industry, regulation and academia (Carusi, Wittwehr, & Whelan, 2022). NAMs are already used by industry for screening purposes but frequently, are not considered ready for inclusion in all applications for registration (Berggren & Worth, 2023; Čavoski, Holden, & Lee, 2023). Building scientific confidence in NAMs is a fundamental aspect for implementing them in human health risk assessment (National Academies of Sciences, 2023; van der Zalm et al., 2022). Continued research and development of NAMs in academia and industry is needed, however for a wide range of NAMs to be suitable for regulatory risk assessment, a two-pronged approach is required. A bottom-up coordinated effort from stakeholders in academia, regulation and industry should encourage the development and adoption of suitable NAMs, and a top-down legal and institutional change should focus on expediting regulatory uptake of a diverse range of suitable NAMs (Zaunbrecher et al., 2017).

Legal and institutional changes as well as uptake of scientific and technological innovations, such as NAMs, will be difficult if the needs and pre-requisites of risk assessors, their knowledge, experience and

concerns are not considered. In prior literature, the perspective of different stakeholders has been investigated in various formats, such as literature reviews, stakeholder workshops, qualitative interviews or focus groups and large-scale surveys (e.g., Carusi et al., 2022; Čavoski et al., 2023; Dent et al., 2021; European Chemicals Agency, 2023; Hunka et al., 2013; Nordic Council of Ministers, 2021; Punt, Bouwmeester, Schiffelers, & Peijnenburg, 2018; Westmoreland et al., 2022; Zaunbrecher et al., 2017).

Zaunbrecher et al. (2017) applied a mixed-method approach by interviewing and surveying risk assessors (primarily) from the United States of America (USA), to investigate the barriers and drivers to the use of NAMs. The survey further asked the participants to indicate whether mechanistically based / high-throughput (HTS) *in vitro* cell or biochemical assays and *in vivo* small-animal assays, QSARs, and bio-markers detection and evaluation, would be “viable” approaches for toxicological assessment. The survey participants (N = 1381; 75 % from North America, 15 % from Europe and 10 % from other regions) expressed higher levels of “perceived viability” for NAMs for screening, prioritizing for further testing, and comparative assessment than for establishing safety levels.

The article by Zaunbrecher et al. (2017) is most notable for its approach, as it differentiated the application context of NAMs. Most other social science literature focused more broadly on stakeholders’ views on NAMs in general or for a specific type of NAM. It remains unclear how transferrable these general or highly specific insights are to different types of NAMs or application contexts. For example, Mondou et al. (2020) focused on NAMs in general and suggested that NAMs that were perceived as more familiar were judged as more “viable.” Pain et al. (2020) focused specifically on the use of toxicogenomics in chemical risk assessment and listed several drivers (i.e., the potential ability of NAMs to generate a better mechanistic understanding of health and environmental effects from exposures to chemicals; the potential for new applications in human and environmental toxicology; reduced cost; increased efficiency) and barriers (i.e., insufficient validation, complexity of interpretation, and lack of standardization). Pain et al. (2020) stressed that the strong focus on innovation instead of adoption might be a core obstacle to the use of toxicogenomics for chemical risk assessment. Further, early surveys from the 1990s in North America and the United Kingdom investigated toxicologists’ views on the validity of animal studies (Kraus, Malmfors, & Slovic, 1992; Slovic et al., 1995; Slovic, Malmfors, Mertz, Neil, & Purchase, 1997). The surveyed experts diverged in their views on whether results from animal studies are transferable to human health, with half disagreeing and half agreeing that the way an animal reacts to a chemical is a reliable predictor of how a human would react to it (Slovic et al., 1997). The authors (Slovic et al., 1997) connected the differences in responses to the experts’ backgrounds; specifically those working in industry expressed more pessimistic views on the validity of animal studies to determine carcinogenicity and, compared to the participants from academia or regulation, were more likely to see humans as less vulnerable than animals (Kraus et al., 1992). A more recent study (Bearth, Roth, Wilks, & Siegrist, 2024) showed that the divergences in risk assessors’ views on animal testing persist and that they also translate to NAMs, specifically *in vitro* and *in silico* approaches.

# 3. Study aims and research questions

This study aimed to tackle existing knowledge gaps about the use and regulatory uptake of NAMs in the context of European human health risk assessment of chemicals (e.g., pesticides, industrial chemicals and human medicines). The following research questions were investigated:

* What is the current familiarity with and use of NAMs in European human health risk assessors (i.e., status quo)?

* Which barriers and drivers to the acceptance and use of NAMs are top-of-the-mind of the European human health risk assessors?
* What are the needs, concerns, individual and organisational views of European human health risk assessors regarding NAMs in human health risk assessment?

* Are there differences based on the European human health risk assessors' background in regulation, industry or academia?

# 4. Methodological approach

## 4.1. Design and procedure

This study is based on a mixed method approach, namely a qualitative pilot study and a quantitative main study. The target group for both studies was European risk assessors<fnref n="1" /> from regulatory authorities, scientific organisations, consultancy, industry and academia. The risk assessors were recruited via email from the network of the involved researchers, through various European institutions and initiatives (e.g., European Food Safety Authority (EFSA), the Organization for Economic Co-operation and Development (OECD), the Network for Preliminary Assessment of Regulatory Relevance (PARERE) at the EU Reference Laboratory on Alternatives to Animal Testing (EURL ECVAM), the European Partnership for Alternative Approaches to Animal Testing (EPAA), particularly through the European Partnership for the Assessment of Risks from Chemicals (PARC). Participants were also asked to forward the survey to other participants to increase its reach. Duplicate participation on the same browser was not possible. All participants provided informed consent and ethical approval was obtained from two independent ethical boards prior to data collection (Switzerland: EK 2023-N-12; Netherlands: GZB-619).

## 4.2. Qualitative pilot study: Online interviews

### 4.2.1. Method of the pilot study

The first goal of the qualitative pilot study was to discover themes and identify gaps that could be filled with the survey. For this reason, in addition to risk assessors, researchers and experts involved in various European initiatives to promote the acceptance and use of NAMs were invited as well. The second goal was to extend the authors' mental models of the research topic for the survey design, i.e., the involved researchers' experiences, preferences, values and existing knowledge about a specific topic can influence the design of a survey and might introduce unwanted biases (e.g., omission of questions on issues that the authors are not familiar with or deem of little importance). The questionnaire guideline comprised semi-structured questions on NAMs (including their status of use and integration at desk level) for short online interviews. To increase heterogeneity in the sample, theoretical sampling was applied, meaning that interviewees were specifically chosen to represent a variety of institutional backgrounds and expertise (instead of a random selection of participants). A moderator with a social science background led the interviews, whereas an assistant with a (regulatory) toxicology background took notes. The notes were used as a basis for the thematic analysis by the social scientist. No recordings were made due to the sensitive nature of some of the discussions and to ensure that the participants felt they could share freely.

### 4.2.2. Results of the pilot study

In total, N = 19 interviewees from regulatory authorities, scientific organisations, consultancy, industry and academia from various European and national institutions and organisations were interviewed between September 2022 and January 2023. The interviews took between

30 and 70 min. All interviewees were familiar with the term NAMs; their definitions, however, varied from very simple ones (i.e., novel methods, not in vivo tests) to definitions that referenced specific types of NAMs (e. g., read-across, QSARs) or the 3R principles. The interviewees expressed different views regarding their acceptance and use of NAMs, depending largely on the legal framework they operated under; the (perceived) restrictiveness of the legislation; and their training and experience.

Common themes regarding the acceptance and use of NAMs were:

* The lack of formal validation and the required conditions to use “valid” methods that are scientifically sound for regulatory purposes.

* The lack of guidance that recommends the use of a particular NAM for a specific endpoint, in a given application context.

* Whether animal testing was the right standard to compare NAMs to and that NAMs require their own standards entirely and thus, a system change.

* Organizational / human factors, such as the role of different actors and institutions within the system, perceived public risk or uncertainty aversion (e.g., concerns over chemical risks by the general public, public pressure through protests or boycotts, formal complaints by NGOs), the consequences of positive or negative outputs of NAMs for risk management and communication and related challenges when characterizing uncertainty in NAMs.

## 4.3. Quantitative main study: Anonymous online survey

### 4.3.1. Sample description

Initially, N = 580 participants proceeded beyond the information page. Participants who indicated they were not risk assessors (n = 53) were screened out at the start of the questionnaire and participants who did not at least fill out the first two sections of the questionnaire (n = 201) were removed from the sample. Risk assessors who indicated to have expertise in environmental risk assessment were also removed from this sample (N = 103). This resulted in a final sample size of N = 222 European human health risk assessors. Table 1 presents an overview of the participants' expertise and socio-demographics. For further context, the participants were asked to indicate all European legal frameworks that were most relevant for their day-to-day work (cf. Table A in the Supplemental Materials). The most common legal frameworks were the Regulation on the Registration, Evaluation, Authorisation and Restriction of chemicals (REACH), the Classification, Labelling and Packaging (CLP) Regulation, the Plant Protection Products (PPP) Regulation, the Biocidal Products Regulation (BPR), and the medicinal products for human use (i.e., pharmaceuticals) Directive. The human health risk assessors chose on average M = 2.6 legal frameworks (SD = 1.7, range 1–12).

### 4.3.2. Survey questionnaire

The structure and content of the survey questionnaire were based on the themes identified in the qualitative interviews. The online survey comprised the following four sections in a mix of open- and closed-format questions:

* Background of human health risk assessors and socio-demographics

* Status quo of NAMs (familiarity and use)

* The barriers and drivers of the regulatory acceptance and use of NAMs

* The needs, concerns, individual and organisational views of human health risk assessors.

Several concepts were introduced and defined in the questionnaire. First, the following working definition of “NAMs” was given: “... any valid and relevant technology, methodology, approach, strategies, or combination thereof that aims at providing information on chemical hazard, exposure, and risk assessment to reduce, refine or replace animal testing.” Second, “risk assessment” was defined as an “umbrella term for all types of

<footnote n="1">¹ Both human health and environmental risk assessors were recruited. This paper focuses on the human health risk assessors, while a companion paper will present the data on the environmental risk assessors. This division of data was done, as substantial differences in results were expected, as well as differences in target readership.</footnote>
<caption>**Table 1**</caption>

Participants' expertise and socio-demographics (N = 193-222; sample sizes vary due to dropouts and missing values).

<table><thead><tr><th>Variable</th><th>Frequency (%) / Descriptives</th></tr></thead><tbody><tr><td><strong>Age</strong></td><td>M = 49 SD = 12<br>Med. = 48, range 28-78</td></tr><tr><td><strong>Years of experience</strong></td><td>M = 16 SD = 10<br>Med. = 15, range &lt; 1-54</td></tr><tr><td><strong>Gender</strong></td><td></td></tr><tr><td>Female</td><td>104 (53 %)</td></tr><tr><td>Male</td><td>75 (40 %)</td></tr><tr><td>Other</td><td>2 (1 %)</td></tr><tr><td>Do not want to tell</td><td>12 (6 %)</td></tr><tr><td><strong>Geographical origin</strong></td><td></td></tr><tr><td>Eastern Europe</td><td>6 (3 %)</td></tr><tr><td>Northern Europe</td><td>53 (24 %)</td></tr><tr><td>Southern Europe</td><td>33 (15 %)</td></tr><tr><td>Western Europe</td><td>130 (58 %)</td></tr><tr><td><strong>Background</strong></td><td></td></tr><tr><td>Academia</td><td>53 (24 %)</td></tr><tr><td>Consultancy and freelance</td><td>21 (9 %)</td></tr><tr><td>Industry</td><td>40 (18 %)</td></tr><tr><td>Non-governmental / Non-profit organisations</td><td>5 (2 %)</td></tr><tr><td>Regulatory authorities or agencies</td><td>87 (39 %)</td></tr><tr><td>Scientific organisations and committees</td><td>8 (4 %)</td></tr><tr><td>Other</td><td>8 (4 %)</td></tr><tr><td><strong>Educational background (multiple responses possible)</strong></td><td></td></tr><tr><td>Toxicology / Ecotoxicology</td><td>166</td></tr><tr><td>Chemistry</td><td>91</td></tr><tr><td>Biochemistry</td><td>98</td></tr><tr><td>Biology</td><td>111</td></tr><tr><td>Engineering (Chemical, Material, Environmental)</td><td>17</td></tr><tr><td>Ecology / Environmental Sciences</td><td>32</td></tr><tr><td>Industrial Ecology</td><td>1</td></tr><tr><td>Computer Science / Mathematics</td><td>21</td></tr><tr><td>Public and Occupational Health / Environmental Health Sciences</td><td>35</td></tr><tr><td>Medicine</td><td>25</td></tr><tr><td>Pharmaceutical Sciences</td><td>43</td></tr><tr><td>Veterinary Science</td><td>13</td></tr><tr><td>Epidemiology</td><td>28</td></tr><tr><td>Risk Assessment</td><td>118</td></tr><tr><td>Other (e.g., endocrinology, food safety, physics)</td><td>19</td></tr></tbody></table>

Note. M: Mean, SD: Standard Deviation, Med.: Median.

hazards and risk assessment of chemical substances, mixtures and products in any setting (e.g., academic, industry, consultancy, regulatory)." Third, "regulatory acceptance" was defined as the "incorporation of validated NAMs into standardized and harmonized regulatory testing guidelines and not (yet) validated NAMs used in risk assessment for regulatory decision-making on a case-by-case basis." The survey was open between May and June 2023. Median participation duration was 25 min.

### 4.3.3. Background of human health risk assessors and socio-demographics

The participants' current employment (or last employment for unemployed or retired participants) was assessed with a list of eight closed-format options and one open-format option (industry, regulatory authority or agency, scientific organisations and committees, academia, consultancy and freelance, non-governmental (NGOs) or non-profit-organisation (NPOs), not currently employed, retired, other). To account for the expected heterogeneity in responses based on their backgrounds (Kraus et al., 1992; Slovic et al., 1995), the article will focus on human health risk assessors with an industry (n = 61; i.e., industry, consultancy and freelance), a regulatory (n = 95; i.e., regulatory authority or agency, scientific organisations and committees) or a background in universities and research institutions (n = 53; i.e., academia). For this purpose, this variable was recoded accordingly, while the other backgrounds (i.e., NGOs, NPOs) were coded as missing, due to the substantially smaller participation rate.

### 4.3.4. Status quo of NAMs (familiarity and use)

The status quo was measured in three stages, namely familiarity, use in general and use for specific application contexts.

In the first stage "familiarity," the participants were presented with a list of 19 methods (in vitro assays, omics), approaches (e.g., grouping &amp; read-across, QSARs, DA, IATA) and concepts (e.g., AOP) and were asked to indicate how familiar they were with each ranging from 1 "very unfamiliar" (defined as knowing basic facts but feeling unprepared to analyse or interpret results), 2 "somewhat unfamiliar," 3 "somewhat familiar" to 4 "very familiar" (defined as knowing a lot about these methods and being skilled and trained in the analysis and interpretation of results). Additionally, they could indicate whether they had never heard of this method. *In vivo* assays (i.e., mammalian assays (e.g., rat, mouse, guinea pig, rabbit, monkey)) were also included in these 19 methods to offer a proxy to conventional methods used for human health risk assessment and thus, a comparative value.

In the second stage "use in general," the same list was presented to the participants, excluding the ones they had never heard of. They were asked to indicate how frequently they encountered these methods as part of their work in chemical risk assessment on a scale from 1 "never," 2 "rarely," 3 "every now and then" to 4 "frequently." It should be noted that depending on the participants background, use can be different (e.g., academics might apply a method, whereas regulators might make use of the data to take a decision).

In the third stage "use for specific application contexts," the list of methods was presented a final time, excluding the ones that they had never heard of and never encountered. In this stage, the participants could tick each concept or method that they had used for a specific application context in a multiple response matrix. The application contexts were "screening/prioritization," "hazard identification," "hazard characterisation," "exposure assessment," and "risk characterisation."

### 4.3.5. The barriers and drivers of the regulatory acceptance and use of NAMs

Participants were asked what, in their experience, were the most important barriers and drivers for the use and regulatory acceptance of NAMs. As the goal was to identify the most pressing barriers and drivers (i.e., top-of-the-mind barriers and drivers), an open-format recall with two response fields was applied. Responses were optional to avoid drop-outs. A total of n = 162 participants (73 % of the total sample) provided codable barriers and n = 152 participants (69 % of the total sample) provided codable drivers. The remaining participants left the optional response field empty. The participants provided a rich database and described the barriers with M = 33 words and drivers with M = 21 words. The responses were coded by two independent coders into a flexible coding scheme, which was informed by the pilot study's themes and extended based on the responses (i.e., new codes were added if new insights emerged). The coding scheme was purposefully built to discover as many diverse barriers and drivers as possible, instead of prioritising more frequently mentioned ones. Up to five codes per response were given, as risk assessors listed several barriers and drivers in one response. The Cohen's Kappa (McHugh, 2012) for the first code was 0.6 for barriers and 0.7 for drivers.<fnref n="2" /> Deviations between coders originated mostly in different orders in coding from the first to the fifth code given per response and were resolved by one of the coders after exchanging with the other coder.

Additionally, the participants were asked in a closed-format question to indicate what role different stakeholders, namely industry, regulatory authority or agency, scientific organisations and committees, academia, consultancy and freelance, non-governmental or non-profit-

<footnote n="2">² Cohen's Kappa measures the agreement between two coders (i.e., interrater reliability). It ranges from -1 to 0 to 1. Interrater reliabilities of >= 0.6 are considered acceptable for our purposes (McHugh, 2012).</footnote>
organisation played in the use and regulatory acceptance of NAMs (cf. Fig. 2 in the results section). Response options ranged from 1 “strongly hinder,” 2 “somewhat hinder,” 3 “neither hinder nor drive,” 4 “somewhat drive” and 5 “strongly drive the use of NAMs.”.

### 4.3.6. The needs, concerns, individual and organisational views of human health risk assessors

In the last section, three constructs measured the risk assessors' needs, concerns, individual and organisational views (cf. Figs. 3, 4 and 5 in the results section): the pre-conditions to using NAMs, perceived individual freedom and basic assumptions in risk assessment. The response options ranged from 1 “strongly disagree,” 2 “disagree,” 3 “agree” and 4 “strongly agree” (and “do not know / no opinion”).

Five items measured the pre-conditions to using NAMs in risk assessment. The items were preceded by defining the terms “valid” (scientifically sound test considered by risk assessors to have sufficient reliability and relevance for a specific purpose) and “formally validated” (the formal process by which reliability and relevance of a particular approach method, process or assessment are established for a defined purpose). The participants were asked about their perceived individual freedom in risk assessment with six statements, regarding difficulties to deviate from applicable guidance, peer opposition and resource restraints. Basic assumptions about risk assessment were assessed with five items that address the assumptions that might underlie risk assessors' views, such as what they perceive as gold standard in risk assessment or whether they are sceptical of NAMs (as illustrated in Fig. 3).

The questionnaire also featured additional questions and an optional part on perspectives about risk assessment, which are published elsewhere (Bearth et al., 2024), as these questions were designed to be compared to responses from the public.

## 4.4. Data analysis

All analyses were conducted in IBM SPSS Statistics 28.0 (IBM Corp., 2023). Non-response in optional questions or due to drop-out towards the end of the questionnaire were treated as missing values. Frequency distributions served as descriptive analyses of the response patterns. Bivariate relationships between familiarity and the use of different methods in risk assessment were quantified as Pearson's correlation coefficients. The coded barriers and drivers were analysed descriptively (empty response fields were treated as missing values). The role of different stakeholders in hindering vs. driving the use of NAMs was further investigated by linking it to the respondents' background in industry, regulation and academia (Chi-Square tests with Cramer's V). Similarly, Chi-Square tests with Cramer's V were used to link the risk assessors' backgrounds in industry, regulation and academia with their needs, concerns, individual and organisational views. Some data transformations were needed to ensure sufficient (expected) cell numbers. First, the responses were recoded into three response options for the role of different stakeholders (strongly or somewhat hindering, neither, strongly or somewhat driving) and two response options for the preference and views ((strongly) disagree, (strongly) agree). Second, “Do not know / no opinion responses” were treated as missing values for this analysis. Third, where the expected cell count dropped below 5 for more than 20 % of the cells, analyses were not conducted. To account for multiple testing due to tests done to single items (5–6 items per variable), the p-value was set conservatively to *p* < 0.001.

# 5. Results

## 5.1. Status quo of NAMs (familiarity and use)

Fig. 1 relates familiarity with methods to their use in their day-to-day work, split for human health risk assessors from industry, regulation and academia. Unsurprisingly, more familiar methods were more frequently encountered and vice versa (r = 0.54 to 0.79, *p* < 0.001). Fig. 1 shows

that differences exist across human health risk assessors' background. For industry (Fig. 1a), the most familiar and frequently encountered methods (top right quadrant) were mammalian *in vivo* assays (included for comparative purposes), grouping / read-across, QSAR and DA (i.e., a combination of *in chemico* and *in vitro* assays). For risk assessors from regulation (Fig. 1b), only mammalian *in vivo* and grouping / read-across methods fell in the top right quadrant. Risk assessors from academia (Fig. 1c) were most familiar and used most frequently *in vitro* assays and biomarkers (top right quadrant). The least familiar and frequently encountered methods (bottom left and middle quadrant) for industry and regulation were the omics methods, which were rated as more familiar and frequently encountered by risk assessors from academia (middle quadrant).

Table 2 shows which methods the human health risk assessors had encountered in different application contexts. The values in Table 2 represent the number and percentage (in brackets) of participants that had indicated to have encountered data from a specific method for the respective application context. Participants that had in the previous two steps said that they had never heard of or had never used a particular method (e.g., *In Vitro* to *In Vivo* Extrapolation (IVIVE)) did not see the method in the list (e.g., they did not rate whether they had used IVIVE in a specific application context). Thus, the baseline per cell (100 %) represents the number of participants that rated this method. There are some patterns across application contexts with most methods for generating data being encountered by the risk assessors for hazard identification and to a lesser degree for hazard characterisation. The highest percentages were observed in cells combining hazard identification / characterisation and *in vivo* assays, QSAR, grouping / read-across, *in vitro* assays and DA. Particularly, for exposure assessment (except for biomarkers and toxicokinetics (TK) / Physiology Based (Pharmaco) Kinetic Modelling (PB(P)K) modelling) and to a lesser degree for risk characterisation (except for *in vivo* assays (mammalian), grouping and/or read across) and screening / prioritization (except for HTS), methods were used by fewer risk assessors. Table F in the Supplementary Material present the heat map excluding the participants from academia for additional insights.

## 5.2. Barriers and drivers of the regulatory acceptance and use of NAMs

Tables 3 and 4 present the coded responses for barriers and drivers of the acceptance and use of NAMs and two specific examples for each code. It is important to note that the frequency of mentions can suggest that a barrier and driver is important, but less frequently mentioned barriers and drivers should not be disregarded. It is likely that frequently mentioned barriers and drivers are more obvious, yet infrequent mentions of a barrier or driver does not imply irrelevance. It should also be noted that there were overlaps between codes due to the complexity of responses.

Legal/regulatory (e.g., lack of standardisation, harmonisation, and validation, difficulty to change status quo and legal framework), scientific/technical (e.g., scientific or technical concern and limitations, uncertainty) and individual or organisational barriers (e.g., scepticism, lack of trust, lack of (formal) acceptance) were mentioned by the risk assessors. The participants also mentioned several different drivers of the acceptance and use of NAMs. In some cases, the drivers inverted the aspects mentioned in the barriers (e.g., lack of vs. pushing standardisation, harmonisation, and validation) or indirect drivers were mentioned (increased trust due to another driver, e.g., technical requirements fulfilled).

Fig. 2 presents the responses regarding the roles of different stakeholders in hindering or promoting the use of NAMs. There was a clear tendency that most stakeholders were seen as driving, rather than hindering the use of NAMs. Particularly academia (n = 144, 74 %) were seen as drivers of the use of NAMs by a majority of risk assessors, while regulatory authorities, agencies and scientific organisation were seen most frequently as hindering the use of NAMs. The response options
<figure><img src="image_3.png" /></figure>

<figure><img src="image_4.png" /></figure>

<figure><img src="image_5.png" /><figcaption>**Fig. 1.** Mean familiarity with and use of different methods (a. n = 59–61 human health risk assessors from industry; b. n = 93–95 human health risk assessors from regulation, c. n = 49–53 health risk assessors from academia); frequencies vary as use was only assessed if risk assessor had heard of the method).</figcaption></figure>
Role of stakeholders in hindering or promoting the use of NAMs (N = 188-196)

<figure><img src="image_6.png" /><figcaption>Fig. 2. Role of stakeholders in hindering or promoting the use of NAMs (N = 188–196).</figcaption></figure>

Pre-conditions of using NAMs (N = 197)

<figure><img src="image_7.png" /><figcaption>Fig. 3. Pre-conditions of using NAMs according to risk assessors (N = 197).</figcaption></figure>

"strongly/somewhat hinder the use of NAMs" were rarely chosen by the participants. It should be noted that these results should be interpreted with caution, as they involve self-evaluations (e.g., risk assessors from regulation judging their own role). The response distributions for the following stakeholders differed significantly for risk assessors from industry, regulation and academia: "academia" ($\chi^2(4) = 16.7, p = 0.002, V = 0.21"), "industry" ($\chi^2(4) = 35.2, p < 0.001, V = 0.31"), and "regulatory authorities and agencies" ($\chi^2(4) = 17.0, p = 0.002, V = 0.21"). The stakeholder "academia" was more frequently labelled as hindering the use of NAMs by risk assessors from industry (n = 8, 15%) than from risk assessors from regulation (n = 2, 2%) and academia (n = 1, 2%). The stakeholder "industry" was more frequently labelled as hindering the

use of NAMs by risk assessors from academia (n = 14, 31%) than from industry (n = 3, 6%) and regulation (n = 1, 1%). The stakeholder "regulatory authority and agency" was more frequently labelled as hindering the use of NAMs by risk assessors from industry (n = 22, 42%) than from regulation (n = 11, 13%) and academia (n = 9, 20%). No significant differences were observed for the other stakeholders ($\chi^2(4) < 8.6, p > 0.071$). Table B in the Supplementary Material shows the response distributions split by the risk assessors' background.
<figure><img src="image_8.png" /><figcaption>Fig. 4. Freedom in risk assessment (N = 196).</figcaption></figure>

<figure><img src="image_9.png" /><figcaption>Fig. 5. Basic assumptions of risk assessment (N = 169–196).</figcaption></figure>

### 5.3. The needs, concerns, individual and organisational views of human health risk assessors

A majority of participants (strongly) agreed with the different pre-conditions of using NAMs in risk assessment (cf. Fig. 3); strongest was that the associated uncertainty must be characterized and that there must be accompanying guidance. There was a strong agreement that NAMs must be formally validated before their use in risk assessment (n = 160, 81 %) and that they must also be regulatory accepted by another authority (n = 141, 72 %), whereas – based on the insights gained in the pilot study – the prior might be seen as a pre-condition to the latter. The response distributions for risk assessors from industry, regulation and academia differed for the statement regarding Good Laboratory Practice (GLP; $\chi^2(2) = 22.3$, p < 0.001, V = 0.29), namely, risk assessors from regulation disagreed less frequently (n = 6, 10 %) and risk assessors from academia more frequently (n = 17, 37 %) to this statement than would

have been expected. No other response distributions were significantly different based on the risk assessors' background ($\chi^2(2) < 4.5$, p > 0.108) or it could not be determined due to too low expected cell counts. Table C in the Supplementary Material shows the response distributions split by the risk assessors' background.

Fig. 4 shows that substantial restrictions to freedom-to-operate in risk assessment are perceived by the risk assessors. Only roughly a third of the participants (n = 69) agreed that they have a lot of freedom to choose how they conduct risk assessments. Agreement for the other statements focused on restrictions of freedom in risk assessment ranged between 58 % and 70 % (n = 114–138). The risk assessors' responses were more divided in terms of time and capacity constraints – while some felt that this prevented them from deviating from current risk assessment practice, others reported to not have these constraints. Significant differences were observed for some of the items for risk assessors from the industry, regulation and academia. Risk assessors from
<caption>**Table 2**</caption>

Heat map of the use of different methods for specific application contexts (cells: number and percentage of participants that chose this method for the respective application context). Colours represent a heat map ranging from low to high percentages (light to dark blue).

<table><thead><tr><th></th><th>Screening / prioritization</th><th>Hazard identification</th><th>Hazard characterisation</th><th>Exposure assessment</th><th>Risk characterisation</th><th>Total¹</th></tr></thead><tbody><tr><td>in vivo assays (mammalian)</td><td>38 (19%)</td><td>122 (61%)</td><td>131 (66%)</td><td>40 (20%)</td><td>101 (51%)</td><td>199 (100%)</td></tr><tr><td>in chemico assays</td><td>27 (19%)</td><td>63 (45%)</td><td>32 (23%)</td><td>7 (5%)</td><td>19 (14%)</td><td>139 (100%)</td></tr><tr><td>in vitro assays</td><td>60 (31%)</td><td>109 (56%)</td><td>75 (38%)</td><td>17 (9%)</td><td>35 (18%)</td><td>196 (100%)</td></tr><tr><td>other in vivo assays</td><td>24 (16%)</td><td>55 (36%)</td><td>39 (26%)</td><td>6 (4%)</td><td>11 (7%)</td><td>151 (100%)</td></tr><tr><td>High-throughput screening</td><td>60 (36%)</td><td>71 (43%)</td><td>29 (17%)</td><td>10 (6%)</td><td>19 (11%)</td><td>167 (100%)</td></tr><tr><td>Grouping and/or read-across</td><td>49 (26%)</td><td>112 (59%)</td><td>90 (47%)</td><td>21 (11%)</td><td>63 (33%)</td><td>190 (100%)</td></tr><tr><td>QSAR methods</td><td>54 (29%)</td><td>112 (60%)</td><td>58 (31%)</td><td>11 (6%)</td><td>34 (18%)</td><td>187 (100%)</td></tr><tr><td>Genomics</td><td>24 (19%)</td><td>28 (22%)</td><td>14 (11%)</td><td>2 (2%)</td><td>12 (9%)</td><td>127 (100%)</td></tr><tr><td>Transcriptomics</td><td>21 (18%)</td><td>27 (23%)</td><td>19 (17%)</td><td>6 (5%)</td><td>9 (8%)</td><td>115 (100%)</td></tr><tr><td>Metabolomics</td><td>22 (17%)</td><td>30 (23%)</td><td>15 (12%)</td><td>9 (7%)</td><td>10 (8%)</td><td>128 (100%)</td></tr><tr><td>Proteomics</td><td>17 (15%)</td><td>23 (20%)</td><td>11 (9%)</td><td>3 (3%)</td><td>5 (4%)</td><td>116 (100%)</td></tr><tr><td>Biomarkers (exposure, effect)</td><td>22 (12%)</td><td>58 (32%)</td><td>42 (23%)</td><td>64 (35%)</td><td>46 (25%)</td><td>184 (100%)</td></tr><tr><td>Toxicokinetics, PB(P)K modelling</td><td>16 (9%)</td><td>44 (24%)</td><td>53 (28%)</td><td>59 (32%)</td><td>55 (30%)</td><td>186 (100%)</td></tr><tr><td>IVIVE</td><td>12 (8%)</td><td>30 (21%)</td><td>37 (25%)</td><td>24 (16%)</td><td>30 (21%)</td><td>146 (100%)</td></tr><tr><td>Adverse Outcome Pathways</td><td>28 (15%)</td><td>77 (41%)</td><td>64 (34%)</td><td>7 (4%)</td><td>35 (19%)</td><td>189 (100%)</td></tr><tr><td>IATA</td><td>20 (11%)</td><td>60 (33%)</td><td>60 (33%)</td><td>21 (11%)</td><td>49 (27%)</td><td>184 (100%)</td></tr><tr><td>DA</td><td>24 (13%)</td><td>100 (54%)</td><td>77 (42%)</td><td>15 (8%)</td><td>55 (30%)</td><td>185 (100%)</td></tr></tbody></table>

Note. ¹ Number of participants that rated this method. This number varies across methods, as participants that had never heard of the method or had never encountered it were excluded. Given the fact that multiple choices were allowed the total number of participants does not need to sum up to the total reported in the last column.

regulation / industry, compared to risk assessors from academia, agreed more frequently that it is difficult for them to deviate from guidance (n = 73, 86% / n = 38, 76% vs. n = 21, 51%, χ²(2) = 17.8, p < 0.001, V = 0.32) and that they do not have freedom in how they conduct risk assessment (n = 68, 81% / n = 41, 82% vs. n = 20, 50%, χ²(2) = 15.8, p < 0.001, V = 0.30). No significant differences were observed for the other items (χ²(2) < 11.8, p > .003³). Table D in the Supplementary Material shows the response distributions split by the risk assessors' background.

Fig. 5 shows a high degree of variance regarding the risk assessors' basic assumptions in risk assessment. About half of the risk assessors associated higher uncertainty with NAMs and a third were more sceptical of NAMs compared to *in vivo* testing. However, only about a quarter of risk assessors (n = 51) (strongly) agreed that NAMs should only be used as supporting information in risk assessment and that *in vivo* testing should be taken as the gold standard. No significant differences in response patterns were found for risk assessors with different backgrounds (χ²(2) < 6.3, p > 0.042). Table E in the Supplementary Material shows the response distributions split by the risk assessors' background.

## 6. Discussion

Much has been written about the technical and non-technical barriers to the implementation of NAMs in regulatory chemical risk assessment (e.g., Archibald, Drake, & Coleman, 2015; Marx-Stoelting et al., 2023; Schmeisser et al., 2023; Sewell et al., 2024). Notable institutions have published reports on this issue to set up frameworks that aim at narrowing the gap between science and policy and regulatory decision-making (e.g., Carusi et al., 2022; Cattaneo et al., 2023; European Chemicals Agency, 2023; National Academies of Sciences, 2023; United States Environmental Protection Agency, 2021). Carusi et al. (2022) and Čavoški et al. (2023) highlighted that the technical barriers interact with, exacerbate or are exacerbated by non-technical barriers (e.g., trust among stakeholders from different backgrounds and institutions, confidence or scepticism in the data and the dialogue across

siloes). Our study adds to this knowledge base by documenting the views of individual risk assessors working in the system.

### 6.1. Status quo of NAMs in European human health risk assessment: Familiarity, use and application contexts

Our study showed that mammalian *in vivo* testing is by far still the most prevalent of all methods, particularly among industry and regulation.<fnref n="4" /> The higher familiarity and use associated with grouping and read-across, QSARs, *in vitro* assays and DA might partly relate to their inclusion as information requirements in existing regulations and the availability of specific regulatory guidance documents (e.g., GD for QSARs and grouping (European Chemicals Agency, 2011; OECD, 2024), Read-Across Assessment Framework RAAF (European Chemicals Agency, 2017), guideline for Defined Approaches on Skin Sensitization (DASS) (OECD, 2023a)). The prohibition of animal experiments as the default testing option under the Cosmetic Products Regulation ((EC) No 1223/2009) has been important for paving the way for the development and regulatory use of data from DA on skin sensitisation. The paths taken by such exemplary subgroups of NAMs can be regarded as an achievement deserving a retrospective analysis to capitalise on the regulatory, scientific and operational milestones that has resulted in the regulatory use of these NAMs.

NAMs are developed for certain endpoints, and are not in general (except for specific endpoints, e.g., skin and eye irritation, skin sensitisation), sufficient as stand-alone replacement of animal data for addressing a specific regulatory information requirement and/or end point (e.g., endocrine activity, genotoxicity, immunotoxicity) (Berggren & Worth, 2023). Our data highlights potential areas where NAMs are already used or would be easier to apply in regulatory risk assessment (i. e., NAMs that are already encountered in the regulatory requirements or guidance documents, e.g., QSARs for specific end points, read across, DA for hazard identification of skin sensitisation) vs. harder to apply (i.e., NAMs that are currently not developed for specific application context and therefore, rarely encountered by risk assessors).

<footnote n="3">³ As stated in section 4.4, a strict *p*-value of *p* < 0.001 was used to account for multiple testing. The responses regarding the item “I have a lot of freedom to choose how I conduct risk assessments (e.g., which data I use, which methods I use)” came close to this threshold (*p* = 0.003), whereas the other stakeholders did not (χ²(2) < 4.3, *p* > 0.119).</footnote>

<footnote n="4">⁴ Mammalian studies could in some circumstances be considered as NAMs (e. g., when contributing to the goals of reducing or refining animal testing). To avoid overloading the questionnaire, no distinction was made with regard to this in the questionnaire and we do not expect that the respondents differentiated either while responding.</footnote>
<caption>**Table 3**</caption>

Coded barriers mentioned in the open response field (n = 162 participants, N = 347 coded responses in total = 100%).

<table><thead><tr><th>Code and examples</th><th>Freq.</th></tr></thead><tbody><tr><td>Complexity of endpoints vs. limitations of NAMs<br>"For complex hazards like Immunotox and Reprotox, methods are not appropriate and standalone."<br>"Some compounds have pleiotropic effects, sex-dependent effects, effects on several organs at different doses, chronic effects, delayed effects (prenatal exposure)."</td><td>23 (7%)</td></tr><tr><td>Difficulty to change status quo and legal framework<br>"Difficulty in changing methodologies where they have been used for a long time."<br>"Legal binding data requirements have to be fulfilled no matter how good NAMs are"</td><td>29 (8%)</td></tr><tr><td>Lack of (formal) acceptance<br>"There is a fear of the industry that regulators will not accept results and just ask for more studies."<br>"Approval and acceptance among all players."</td><td>33 (10%)</td></tr><tr><td>Lack of guidance for interpretation<br>"Missing Guidance Documents at international level (e.g., OECD)."<br>"Clear guidance by the regulatory bodies to ensure acceptance by all decision makers."</td><td>30 (9%)</td></tr><tr><td>Lack of knowledge or skill<br>"Lack of knowledge in toxicological mechanisms ..."<br>"Lot of new sophisticated methods to learn and implement for one risk assessor."</td><td>36 (10%)</td></tr><tr><td>Lack of standardisation, harmonisation and validation<br>"The lack of inclusion in the OECD Test Guidelines Program indicates insufficient validation and creates uncertainty about potential acceptance."<br>"Lack of standardized methods, clearly devised assessment frameworks (the only exception being defined approaches)."</td><td>50 (14%)</td></tr><tr><td>Lack of use cases or success stories<br>"Lack of exposure: only very few ICH guidelines mention NAMs (e.g., ICH S5)."<br>"Lack of ... and experience in using the new methods among researchers and risk assessors."</td><td>13 (4%)</td></tr><tr><td>Pushback and lack of dialogue among stakeholders<br>"Many times, it seems, that even with a valid battery of NAMs with accompanying justifications, doubts still remain in, let's say, the old guard."<br>"Lack of freedom to operate due to well-entrenched institutional practice (line manager does not support)"</td><td>16 (5%)</td></tr><tr><td>Resource restraints (i.e., time, funding)<br>"Lack of sustainable funding for establishing NAM reliability and relevance."<br>"I think the cost and the unavailability of various NAMs at the same time may represent the main challenge."</td><td>20 (6%)</td></tr><tr><td>Care, risk avoidance and conservativeness among stakeholders<br>"Regulators need to make decisions which include a high responsibility."<br>"Health authorities/regulatory bodies being very conservative and risk-adverse."</td><td>8 (2%)</td></tr><tr><td>Scientific or technical concerns and criticism<br>"Information on robustness, validity, variability, uncertainties etc. There is hardly any focus on this information in NAM development in most research projects."<br>"Almost all NAMs lack information on integrated physiology responses to toxicants."</td><td>49 (14%)</td></tr><tr><td>Scepticism, lack of trust and concern over lack of acceptance of others<br>"Consumer tends to trust more, when food chemicals have been tested on animals."<br>"Lack of confidence in NAMs. Too often aim is to reproduce animal findings (perceived as golden standard) instead acknowledging that the data generated are different – also in purpose."</td><td>40 (11%)</td></tr></tbody></table>

The patterns in familiarity and use of NAMs were similar for human health risk assessors from industry and regulation (i.e., being more familiar with *in vivo*, grouping and read-across and DA), whereas a different pattern emerged for academia. While all participants in our sample identified as risk assessors (i.e., in the screening question at the start of the questionnaire), the participants indicating affiliation to an academic institution make up a more heterogeneous group with higher familiarity and or frequent use of particularly, *in vitro* methods and biomarkers. While this is not surprising, it might highlight a divergence in core goals for academics and regulators, which can be a hurdle for the implementation of NAMs in regulatory practice: the participants from

<caption>**Table 4**</caption>

Coded drivers mentioned in the open response field (n = 152 participants, N = 279 coded responses in total = 100%).

<table><thead><tr><th>Code and example</th><th>Freq.</th></tr></thead><tbody><tr><td>Disseminate use cases and success stories<br>"More practical examples and case studies with the use of NAMs in the context of risk assessment."<br>"Examples where NAMs have worked."</td><td>8 (3%)</td></tr><tr><td>Ease of understanding and training in interpretation<br>"... I think that the most important driver is the ease to understand for risk assessors..."<br>"Training is a key factor in disseminating and facilitating the use of these methods"</td><td>10 (4%)</td></tr><tr><td>Efficiency and resources<br>"For me the most important driver is that NAMs could provide a much faster assessment and also regulatory decisions of many more substances compared to animal testing, which is usually quite time ... intensive..."<br>"The biggest drivers will be the need for efficiency (coping with more chemicals in shorter timeframes with less staff)..."</td><td>30 (11%)</td></tr><tr><td>Financial incentives<br>"Cheaper ways forward benefits all."<br>"Driver for use is money. The cheaper ... the better."<br>(Formal or regulatory) acceptance of NAMs<br>"Acceptance by competent authorities and agencies..."<br>"In the EU, most NAMs generally rejected by regulators. No main driver for use."</td><td>23 (8%)</td></tr><tr><td>Increase trust and confidence<br>"Building trust in NAMs"<br>"This process seems to be able to gain the required trust."</td><td>17 (6%)</td></tr><tr><td>Legal requirement to using NAMs<br>"A top-down change of the legislation towards a general use of NAMs/ NGRA as a mandatory first line of risk assessment. New in vivo testing should only be allowed if NAMs/NGRA do not provide acceptable results."<br>"Amendment of the legislation so the registrants will submit info made with NAMs."</td><td>14 (5%)</td></tr><tr><td>Needs from specific stakeholders<br>"Cosmetic needs ..."<br>"Increased demand for data on hazard of chemicals."</td><td>9 (3%)</td></tr><tr><td>Overcoming the limitations of in vivo testing<br>"If well applied, NAMs will significantly improve risk assessment at various levels mainly by 1) strengthening the scientific 2) allowing the evaluation of a much larger number of chemicals 3) allowing to better address the mixture toxicology."<br>"Animal models are also just models and do not predict everything – biological relevance becomes more important."</td><td>40 (15%)</td></tr><tr><td>Providing guidance<br>"Inclusion of the NAMs in a guidance specific to our context of risk assessment and clear guidelines on how to interpret the results and estimate the level of reliability and relevance..."<br>"Existing Guidance Documents at international level (e.g., OECD)."</td><td>6 (2%)</td></tr><tr><td>Pushing standardisation, harmonisation and validation<br>"Not (yet) validated NAMs are of little use in risk assessment for regulatory decision-making. Such data would rather be a last resort if nothing else is available."<br>"Up to date, formal validation, generally including a comparative approach against in vivo reference tests/data, coupled with a thorough review process was most successful to bring NAM to regulatory acceptance."</td><td>14 (5%)</td></tr><tr><td>Societal or political pressure<br>"Society changes: need to protect animal uses, ever increasing need to get full information on medicines risk/benefit as soon as possible, ever increasing risk adversity while challenging anything new and different...""Public opinion (against animal studies)"</td><td>14 (5%)</td></tr><tr><td>Technical requirements or benefits<br>"Simple endpoints e.g., acute toxicity..."<br>"Making use of the best available science is a big driver..."</td><td>34 (12%)</td></tr><tr><td>The 3R principle and animal welfare<br>"The priority of reducing the use of vertebrate animal testing while continuing to protect human health and the environment."<br>"The most important driver for the use of NAMs is the 3R's principle."</td><td>53 (19%)</td></tr></tbody></table>

academia are more likely to be developers of NAMs, rather than users, such as our participants from industry or regulation. Successful translation of biological tools into assays and from research into regulation requires that academics are aware of the pre-conditions, needs and requirements of risk assessors and managers. This requires further a
translation of information derived from innovative and potentially un-
familiar NAMs to the predictions of potential toxicity to humans
required within a regulatory framework. This can be challenging due to
fundamental differences in core goals, the high specialisation and
diversification needed regarding different types of NAMs and due to the
work partly taking place in siloes (e.g., siloes based on legal framework,
institutional siloes). Important strides have been made in this area by
providing guidance and templates for describing *in vitro* test methods or
reporting mechanistic information (e.g., *Carnesecchi et al.*, 2023; OECD,
2004; OECD, 2017, 2018). However, more familiarity among academia
on *in vivo* methods and how they fulfil regulatory requirements, and the
areas where NAMs are already used (e.g. to support read across) would
likely increase their ability to facilitate the transition towards animal-
free methods for hazard identification and characterisation. Poten-
tially, translating and relating data from NAMs to the traditional infor-
mation obtained through *in vivo* tests to predict adverse effects, while
considering issues such as legal certainty, needs to be a research field in
itself. This differs from the work of facilitating the use of academic data
in regulatory risk assessment and demands thorough knowledge of both
the current testing systems, the available NAM-based tests systems, as
well as of the regulatory and legal frameworks. For instance, an article
by Pallocca and Leist (2022) summarises features and performance
characteristics that might serve to determine the benefits of using ani-
mal vs. NAMs-based methods.

According to our results, academia and to a lesser degree industry,
are seen as the main driving forces regarding the development and
consequent use of NAMs in regulatory risk assessment. However, while
both groups might be well-prepared for the task of producing fit for
purpose, useful NAMs for regulatory decision-making, they might not
have an incentive for doing so. According to the interviewees from in-
dustry and prior literature (Berggren & Worth, 2023), NAMs that are
used (and accepted) for internal processes and decision-making (e.g.,
screening and prioritisation for further testing, compound selection) are
frequently not published or made available to other stakeholders. In
addition, according to the interviewees from the pilot study, there is
little incentive for industry to invest in NAMs on a larger scale if the data
submitted as part of the dossier for market authorisation are not
accepted by regulatory authorities. From the perspective of interviewees
from regulatory institutions, this was sometimes described as a lack of
transparency and some interviewees suspected that results from NAMs
are sometimes excluded to avoid raising red flags. Regulatory author-
ities and scientific organisations were more frequently regarded as
hindering the use of NAMs. This result makes sense, as these stake-
holders primarily aim at using the best available data to protect human
health, while simultaneously being restricted by regulatory re-
quirements. Academic researchers are not necessarily constrained to
follow strict guidance and accordingly have more freedom to operate
than the other stakeholder groups. In simple terms, the primary goal of
academics is to publish and develop innovative methods and may
therefore, not have enough incentives to develop NAMs that can be used
for regulatory purposes. However, reality is more complex than this. The
rational for funding of research is often described in terms of developing
NAMs for regulatory context and many academics strive to develop
NAMs that are appropriate for different regulatory environments.
Increasing exchange across disciplinary siloes (e.g., by formulating and
disseminating criteria for regulatory uptake of NAMs) and equipping all
involved actors with a good understanding of each other's pre-
conditions and needs might remedy some of these hurdles
(Carnesecchi et al., 2023; van der Zalm et al., 2022). The need for
collaboration and a common understanding among different actors of-
fers a good segue into the next section, as the lack thereof is a substantial
barrier to the acceptance and use of NAMs.

## 6.2. Barriers and drivers to the acceptance and use of NAMs

The survey participants provided a wealth of views regarding the

barriers and drivers to the acceptance and use of NAMs. Responses
regarding the barriers were more complex or multifaceted than the re-
sponses regarding the drivers, which were frequently described in more
abstract or generic terms (e.g., improving uptake of NAMs), unspecific
(e.g., NAMs in general) or simply statements contrary to the previously
stated barriers (e.g., availability of guidance). A limitation of our
approach to the barriers and drivers is that we did not differentiate
between barriers and drivers for the acceptance of NAMs and barriers
and drivers for the use of NAMs in order to reduce the complexity of the
survey. While clearly related, acceptance and use are different, as a risk
assessor might *accept* that the NAM is scientifically valid but neverthe-
less not be able to *use* it in a regulatory context due to e.g. legal con-
straints, meaning that some changes in regulatory requirements are
needed. Accordingly, different barriers and drivers are at work for these
two factors, as some responses specifically differentiated between bar-
riers for the use (e.g., “lack of freedom to operate due to well-entrenched
institutional practice and resource constraints”) and acceptance (e.g.,
“lack of standardisation of methods, lack of guidance for specific
application contexts”). We suggest that future research should attempt
to untangle this further.

To synthesise the results, it might be informative to differentiate top-
down barriers and drivers, meaning aspects that need to be tackled on a
system or organisational basis, and bottom-up barriers and drivers,
which should be addressed at the level of individual risk assessors. For
example, the perceived soundness of a method can be a top-down barrier
(e.g., a methods' limitations, lack of accompanying information), but
also a bottom-up barrier based on risk assessors' expectations, needs,
concerns and organisational and individual views (e.g., lack of trust,
reservations towards methods, lack of skills or time to determine validity
of an unfamiliar method).

Top-down barriers or drivers include technical aspects (i.e., scientific
validity of methods, model assumptions, "getting the science right"),
legal or regulatory pre-conditions (e.g., due to the specific legal frame-
work), standardisation at the European or global level, and lack of
(formal) acceptance (i.e., "lack of standardisation and validation").
Interestingly, about 20 % of the participating human health risk asses-
sors disagreed that the formal acceptance by a specific authority or
institution is relevant for the future of NAMs, while the majority agreed
or strongly agreed. Reading between the lines, our results might suggest
that the hesitancy to use fit-for-purpose NAMs at desk level might also be
related to receiving some form of official approval or endorsement (e.g.,
specific information requirements, availability of TGs or GDs). Valida-
tion activities to demonstrate the relevance and reliability of methods
and approaches for regulatory safety assessment are important, yet
underfunded (Gourmelon et al., 2024). Increasing the funding available
for validation likely increase the incentives for academic researchers to
participate in validation activities which will facilitate the regulatory
use of data from (validated) NAMs.

Yet, our results show higher levels of agreement that the associated
uncertainty of a NAM needs to be characterised than that another au-
thority needs to accept it. The epistemic uncertainty (i.e., systematic
uncertainty linked to the model) emerging through the need to combine
different streams of evidence deserves more attention in the future.
Decision theories, such as the Dempster-Shafer theory (DST) or Bayesian
thinking might be useful supporting tools, as they allows to combine
evidence from different sources, while considering the ensuing uncer-
tainty (Ballabio, Biganzoli, Todeschini, & Consonni, 2017; Rathman,
Yang, & Zhou, 2018). In a similar way that the formalization of AOPs
helps all stakeholders to share their thoughts based on a common epis-
temological construct, a formalised approach for the characterisation of
uncertainty would be helpful in providing a common framework for
enhanced discussions. In this respect, the publication of practical guid-
ance and investment in capacity building are essential prerequisites.

Stringent top-down conditions that need to be met for the use of
NAMs in regulatory risk assessment are the legal ones. For example, in
REACH dossier evaluation, the registrants receive legally binding
decisions issued by ECHA. This decision lists the requested tests refer-
ring to internationally approved methods and protocols, and the specific
legal basis for those requests. This system creates the boundaries for
legal certainty around what studies should be performed and why, and a
basis for acceptance of the results in the context of compliance with data
requirements. If those conditions are not met, the decisions do not
withstand juridical scrutiny and are annulled. If so, the studies are not
performed and the juridical process itself consumes resources in terms of
monetary costs, time and commitment of expertise.

Registrants may fear that using data from NAMs that are not formally
published in the Test Method Regulation and/or are subject to an OECD
Test Guideline might result in lengthy discussions to demonstrate that
NAMs have been used appropriately, and they are likely to ultimately
wish to avoid appeals. While there already exists the legal basis for
authorities to be able to assess information provided by NAMs for reg-
ulatory decision making via Annex XI of REACH (for example, on a
Weight of Evidence basis), this appears to be under-utilised, perhaps
indicating a need to improve guidance for registrants. Resources avail-
able to a risk assessor or institution, such as time, specialised skills,
money, motivation or available (digital) tools, can limit the potential to
innovate processes. Additionally, he resources required for authorities to
consider each of the thousands of substances on the market on a case-by-
case basis using Weight of Evidence also highlights the importance of
standardisation and an improved route to formal acceptance of methods.
These and similar aspects highlight that there are resource limits and
constraints to what an individual human health risk assessor or an
institution can achieve. Yet, these issues can also act as a driver for
innovation. Several joint efforts have been launched or are currently
ongoing (e.g., European Food Safety Authority et al., 2022; Marx-
Stoelting et al., 2023; OECD, 2023b; Pallocca et al., 2022) to facilitate
this fundamental paradigm-shift and capacity building in regulatory risk
assessment.

Bottom-up barriers, on the other hand, put more weight on an in-
dividual’s needs, concerns, individual and organisational views, as well
as personal responsibilities. Ideally, top-down measures are accompa-
nied by the assessment, monitoring and consideration of human and
institutional factors, such as needs, trust and social influences. These
should be continuously addressed through education, training, stake-
holder involvement and evidence-based change management (By,
2005). There already exist good examples of successful engagement
events and activities from individuals from academia and regulation,
such as the Nordic NAM Training and Networking Event, DyNAMic
Discussion Series, US EPA NAMs training, the OECD IATA case study
project or the EPAA NAM Designathon or the ISTNET-DNT or DART
workshops (Crofton, Fritsche, Ylikomi, & Bal-Price, 2014; Fritsche, Selfa
Aspiroz, Arand, Faustman, & Müller, 2024). It can be much harder to
measure these human and institutional factors than top-down barriers,
as these factors frequently are implicit, difficult to put into words or,
more importantly, entangled with technical concerns. For example,
about a third of all the participating risk assessors agreed or strongly
agreed that they associate NAMs with higher uncertainty than animal
studies and that they feel more sceptical towards NAMs. While partic-
ularly the responses regarding the uncertainty associated with NAMs are
rooted in technical concerns and the risk assessors’ knowledge and ex-
periences, the response regarding the scepticism towards NAMs might
also be based on a feeling of uneasiness. According to the interviewees,
this feeling of uneasiness is triggered by a lack of familiarity with NAMs,
lack of training in the interpretation and lack of guidance documents,
which might contribute to the hesitation to take NAM data into account.
Equally, a third of the participants thought that animal testing should be
taken as the gold standard. This relates to an important concern of
regulators that the NAM itself and the knowledge gained from its
application must be compared to the current system that is based on in
vivo testing. In general, it is difficult to overcome a prevalent frame of
reference or default (e.g., Masatlioglu & Ok, 2005; Samuelson & Zeck-
hauser, 1988), but on an individual or institutional level, it might be

useful to disseminate cases where NAMs are superior or overcome the
limitations of *in vivo* testing. Moreover, knowledge gathered during the
development of NAMs can offer deeper mechanistic biological knowl-
edge and support interpretations of various test results. Lastly, to in-
crease the confidence in NAMs through increased familiarity and
training, it is suggested to use them as part of IATAs or in a DA (Caloni,
De Angelis, & Hartung, 2022; OECD, 2020).

Another interesting observation is that over 50 % of the participants agreed or strongly agreed that they are met with opposition if they use non-traditional ways of safety testing. This is slightly more nuanced compared to the other items about freedom (e.g., freedom to choose how risk assessment is done, legal requirements, difficulties to deviate), as it might additionally be linked to perceived (social) norms and pressures (e.g., shared and oftentimes implicit standards of how things are done or ought to be among a group of individuals or institutions). Opposition, in this alternative line of interpretation, is then a form of (social) sanction that discourages the use of NAMs (Sunstein, 1996). While legal constraints are the pressing barrier, e.g. a risk assessor might be met with opposition if they do not adhere to legal requirement in their work, these human-based barriers need to be taken into account too. In light of this, the pressure that risk assessors feel from the public and their expectations of chemical risk assessment (e.g., which can result in boycotts, protests or declines in public trust) might also play a role here (Bearth et al., 2024; Kraus et al., 1992).

6.3. *Limitations and implications for future research*

Our approach has some limitations. While we undertook efforts to disseminate our online survey as broadly as possible, there is selectivity in who our participants were. More precisely, participants with a background in regulatory risk assessment and academia coming from Western and Northern Europe represented the majority of the sample, whereas NGOs were clearly underrepresented. It is also possible that the participants in our sample were more interested in, and more informed about, NAMs than the general population of European risk assessors due to sample selection bias. The participants were informed about the content of the survey, and this might have led to self-selection among the sample participants (i.e., more interested or knowledgeable risk assessors were more likely to take part). This implies that our results might paint a too optimistic picture regarding the status quo of acceptance and use of NAMs in Europe. Moreover, analyses for risk assessors working under different legal frameworks (e.g., REACH, plant protection products) were not possible for statistical reasons due to too small samples per cell, despite potentially explaining some of the variance found in the responses.

It is also important to take note that dividing the health risk assessors
into three categories (i.e., industry, regulation and academia) is a
necessary step, yet a simplification. The risk assessors’ background
partly explains differences in views about NAMs as core goals, tasks and
associated challenges of these three groups differ (Kraus et al., 1992).
However, other differences within these broad groups might also
contribute to heterogeneity in responses (i.e., educational background,
legal frameworks, institution or organization of employment). At this
point, we also would like to reiterate that the participants from
academia were more likely to be developers of NAMs, rather than users,
such as the participants from industry or regulation.

As the survey attempted to cover a lot of ground content-wise, some
methodological limitations should also be discussed. First, due to the
broad scope of the survey and target population, the questions were
somewhat hypothetical in nature and sometimes very generalised (e.g.,
endpoints were not linked to specific NAMs or application contexts,
NAMs were a mixture of methodologies, approaches and concepts). This
was somewhat amended by the fact that researchers with heterogeneous
backgrounds contributed to the development of the questionnaire.
Nonetheless, future research should attempt to investigate the insights
in more specific cases. Particularly, the questions that addressed NAMs
in general might have been responded to differently, if they were
formulated for specific methodologies (e.g., in vitro assays), approaches
(e.g., grouping & read-across) or concepts (e.g., AOPs). For example,
specific cases of NAMs for a concrete purpose could be presented to
participants in a qualitative (e.g., focus group, interviews) or quantita-
tive setting (e.g., online experiment) to make the judgments and de-
cisions regarding NAMs more tangible. Another methodological
limitation is that during the development of the questionnaire, we did
not sufficiently consider the distinction between in vivo tests and in vivo
tests as NAMs in line with the 3Rs (i.e., to replace or reduce animal
testing).

6.4. Conclusion

To conclude, our survey highlighted several barriers and drivers to
the top-down and bottom-up implementation of NAMs in regulatory
chemical risk assessment. Particularly, the building of capacity and
mutual understanding of prerequisites among regulatory risk assessors
and academic developers, institutional change management and the
development of formal approaches to decision-making under uncer-
tainty deserve attention. The European Commission are developing a
roadmap to ultimately phase out animal testing for chemical safety as-
sessments, outlining actions that should facilitate the transition towards
animal-free chemicals safety assessment (Berggren & Worth, 2023; Eu-
ropean Commission & Cronin, 2024). Our study shows that it is essential
that this roadmap includes actions to improve the process of validation,
support the development of guidance document that encourage the use
of NAMs and even provides a legal framework to use NAMs in regulation
in order to withstand juridical scrutiny. Aside from building up the
necessary structures, moving away from the comfort zone built into the
broad siloes of academia, regulation and industry will take time. Further
case studies where regulatory and academic risk assessors collaborate in
the (fictive) application of NAMs for specific regulatory purpose (e.g.
hazard classification) and compare with the current regulatory status (e.
g. current hazard class) could help to gain trust as well as identifying
technical gaps.

It is anticipated that as more positive examples and successful use
cases of NAMs for regulatory decision-making become available, more
experience and familiarity with NAMs will be gained for the whole
stakeholder chain (Berggren & Worth, 2023; Zaunbrecher et al., 2017).
It could be argued that the slow and cautious adaptation of NAMs in
regulatory risk assessment are not necessarily a bad thing in light of the
core goal of chemical risk assessment to protect human health through
the use of the best possible method.

CRediT authorship contribution statement

**Angela Bearth:** Writing – review & editing, Writing – original draft, Visualization, Methodology, Investigation, Formal analysis, Data cura- tion, Conceptualization. **Nicolas Roth:** Writing – review & editing, Project administration, Methodology, Data curation, Conceptualization. **Tom Jansen:** Writing – review & editing, Resources, Methodology, Investigation, Conceptualization. **Laura Holden:** Writing – review & editing, Methodology, Investigation, Data curation, Conceptualization. **Aleksandra Cavoski:** Writing – review & editing, Methodology, Investigation, Data curation, Conceptualization. **Emma Di Consiglio:** Writing – review & editing, Conceptualization. **Ingrid Hauzenberger:** Writing – review & editing, Conceptualization. **Robert Lee:** Writing – review & editing, Conceptualization. **Enrico Mombelli:** Writing – review & editing, Investigation, Conceptualization. **Olga Tcher- emenskaia:** Writing – review & editing, Conceptualization. **Lina Wendt-Rasch:** Writing – review & editing, Conceptualization. **Martin F. Wilks:** Writing – review & editing, Supervision, Project administra- tion, Methodology, Investigation, Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to influence
the work reported in this paper.

Acknowledgements

This work was carried out in the framework of the European Part-
nership for the Assessment of Risks from Chemicals (PARC) and has
received funding from the European Union's Horizon Europe research
and innovation program under Grant Agreement No 101057014 and
from the Federal Office of Public Health in Switzerland (FOPH). Views
and opinions expressed are however those of the author(s) only and do
not necessarily reflect those of the European Union, the Health and
Digital Executive Agency or the FOPH. Neither the European Union, the
FOPH nor the granting authority can be held responsible for them. Not
all conclusions in this article represent the views of the Swedish
Chemicals Agency.

**Appendix A. Supplementary material**

Supplementary data to this article can be found online at https://doi.
org/10.1016/j.envint.2025.109279.

Data availability

Data will be made available on request.

References

Archibald, K., Drake, T., Coleman, R., 2015. Barriers to the uptake of human-based test methods, and how to overcome them. Altern. Lab. Anim. 43 (5), 301–308. https://doi.org/10.1177/026119291504300504.

Ball, N., Bars, R., Botham, P.A., Cuciareanu, A., Cronin, M.T.D., Doe, J.E., van
Renzwaay, B., 2022. A framework for chemical safety assessment incorporating
new approach methodologies within REACH. Arch. Toxicol. 96 (3), 743–766.
https://doi.org/10.1007/s00204-021-03215-9.

Ballabio, D., Biganzoli, F., Todeschini, R., Consonni, V., 2017. Qualitative consensus of QSAR ready biodegradability predictions. Toxicol. Environ. Chem. 99 (7-8), 1193-1216. https://doi.org/10.1080/02772248.2016.1260133.

Bearth, A., Roth, N., Wilks, M. F., & Siegrist, M. (2024). Intuitive Toxicology in the 21st century - Bridging the perspectives of the public and risk assessors in Europe. *Risk Analysis, early view*. doi:10.1111/risa.14296.

Berggren, E., Worth, A.P., 2023. Towards a future regulatory framework for chemicals in the European Union – chemicals 2.0. Regul. Toxicol. Pharm. 142, 105431. https://doi.org/10.1016/j.yrtph.2023.105431.

By, R.T., 2005. Organisational change management: a critical review. J. Chang. Manag. 5 (4), 369–380. https://doi.org/10.1080/14697010500359250.

Caloni, F., De Angelis, I., Hartung, T., 2022. Replacement of animal testing by integrated approaches to testing and assessment (IATA): A call for in vivitrosi. Arch. Toxicol. 96 (7), 1935–1950. https://doi.org/10.1007/s00204-022-03299-x.

Carnesecchi, E., Langezaal, I., Browne, P., Batista-Leite, S., Campia, I., Coecke, S.,
Wittwehr, C., 2023. OECD Harmonised Template 201: structuring and reporting
mechanistic information to foster the integration of New Approach Methodologies
for hazard and risk assessment of chemicals. Regul. Toxicol. Pharm. 142, 105426.
https://doi.org/10.1016/j.yrtph.2023.105426.

Carusi, A., Wittwehr, C., Whelan, M., 2022. Addressing evidence needs in chemicals policy and regulation. Publications Office of the European Union, Luxembourg, LU.

Cattaneo, I., Astuto, M.C., Binaglia, M., Devos, Y., Dorne, J.L.C.M., Agudo, A.F.,
Terron, A., 2023. Implementing New Approach Methodologies (NAMs) in food safety
assessments: strategic objectives and actions taken by the European Food Safety
Authority. Trends Food Sci. Technol. 133, 277–290. https://doi.org/10.1016/j.
tifs.2023.02.006.

Cavoski, A., Holden, L., Lee, R., 2023. D6.1 Report on Socio-Technical Barriers to the Uptake of NAMs. University of Birmingham, Birmingham, UK.

Crofton, K., Fritsche, E., Ylikomi, T., Bal-Price, A., 2014. International STakeholder
NETwork (ISTNET) for creating a developmental neurotoxicity testing (DNT)
roadmap for regulatory purposes. ALTEX 31 (2), 223–224.

Dent, M.P., Vaillancourt, E., Thomas, R.S., Carmichael, P.L., Ouedraogo, G., Kojima, H., Yang, C., 2021. Paving the way for application of next generation risk assessment to safety decision-making for cosmetic ingredients. Regul. Toxicol. Pharm. 125, 105026. https://doi.org/10.1016/j.yrtph.2021.105026.

European Chemicals Agency. (2011). Chapter R.6: QSARs and grouping of chemicals. In *Guidance on information requirements and chemical safety assessment*. Helsinki, FI: European Chemicals Agency.
European Chemicals Agency. (2016). *New approach methodologies in regulatory science: Proceedings of a scientific workshop, 19-20 April 2016*. Helsinki, FI: European Chemical Agency.

European Chemicals Agency. (2017). *Read-Across Assessment Framework (RAAF)*. Helsinki, FI: European Chemicals Agency.

European Chemicals Agency. (2023). *Report on the European Chemicals Agency's "New approach methodologies workshop: towards an animal free regulatory system for industrial chemicals"* (31 May – 1 June 2023, Helsinki, Finland): European Chemicals Agency.

European Commission, & Cronin, M. (2024). *Report of the European Commission workshop on "The Roadmap Towards Phasing Out Animal Testing for Chemical Safety Assessments"* - Brussels, 11-12 December 2023: Publications Office of the European Union.

European Commission. (2020). *Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions - Chemicals Strategy for Sustainability - Towards a toxic-free environment*. Brussels, BE: European Commission.

European Food Safety Authority, Tarazona, J., Kass, G., Dorne, J.-L., Liem, D., Parasekvopoulos, K., . . . Hugas, M. (2022). New Approach Methodologies. EFSA *Supporting Publication*, e200502, 1-8. doi:10.2903/sp.efsa.2022.e200502.

Fritsche, E., Selfa Aspiroz, L., Arand, M., Faustman, E., Müller, I., 2024. International Stakeholder NETwork (ISTNET) Workshop for creating a developmental and reproductive toxicity (DART) testing roadmap for regulatory purposes. ALTEX - Alternat. Anim. Exp. 41 (4), 671–673. https://doi.org/10.14573/altex.2410081.

Gourmelon, A., Hubert, P., Grignard, E., Baumann, L., Munn, S., Michel, C., 2024. The benefits of validation of methods for toxicity testing outweigh its costs. ALTEX - Alternat. Anim. Exp. https://doi.org/10.14573/altex.2403051.

Hunka, A.D., Meli, M., Thit, A., Palmqvist, A., Thorbek, P., Forbes, V.E., 2013. Stakeholders' perspective on ecological modeling in environmental risk assessment of pesticides: challenges and opportunities. Risk Anal. 33 (1), 68–79. https://doi.org/10.1111/j.1539-6924.2012.01835.x.

IBM Corp. (2023). IBM SPSS Statistics for Macintosh, Version 29. Armonk, NY: IBM Corp.

Kraus, N., Malmfors, T., Slovic, P., 1992. Intuitive toxicology: expert and lay judgments of chemical risks. Risk Anal. 12 (2), 215–232. https://doi.org/10.1111/j.1539-6924.1992.tb00669.x.

Krebs, A., van Vugt-Lussenburg, B.M.A., Waldmann, T., Albrecht, W., Boei, J., ter Braak, B., Leist, M., 2020. The EU-ToxRisk method documentation, data processing and chemical testing pipeline for the regulatory use of New Approach Methods. Arch. Toxicol. 94 (7), 2435–2461. https://doi.org/10.1007/s00204-020-02802-6.

Madden, J.C., Enoch, S.J., Paini, A., Cronin, M.T.D., 2020. A review of in silico tools as alternatives to animal testing: principles, resources and applications. Altern. Lab. Anim. 48 (4), 146–172. https://doi.org/10.1177/0261192920965977.

Marx-Stoelting, P., Rivière, G., Luijten, M., Aiello-Holden, K., Bandow, N., Baken, K., Sanders, P., 2023. A walk in the PARC: developing and implementing 21st century chemical risk assessment in Europe. Arch. Toxicol. 97 (3), 893–908. https://doi.org/10.1007/s00204-022-03435-7.

Masatlioglu, Y., Ok, E.A., 2005. Rational choice with status quo bias. J. Econ. Theory 121 (1), 1–29. https://doi.org/10.1016/j.jet.2004.03.007.

McHugh, M.L., 2012. Interrater reliability: the kappa statistic. Biochem. Med. 22 (3), 276–282.

Mondou, M., Hickey, G.M., Rahman, H.T., Maguire, S., Pain, G., Crump, D., Basu, N., 2020. Factors affecting the perception of New Approach Methodologies (NAMs) in the ecotoxicology community. Integr. Environ. Assess. Manag. 16 (2), 269–281. https://doi.org/10.1002/ieam.4244.

National Academies of Sciences, E. a. M. (2023). *Building confidence in new evidence streams for human health risk assessment: Lessons learned from laboratory mammalian toxicity tests*. Washington, D.C.: The National Academies Press.

Nordic Council of Ministers. (2021). Nordic workshop on New Approach Methodologies (NAMs) for Grouping and read-Across under REACH and CLP, November 9-11, 2021. Retrieved from https://pub.norden.org/temanord2022-526/#.

OECD. (2004). *The Application of the Principles of GLP to in vitro Studies*. Paris, FR: OECD Series on Principles of Good Laboratory Practice and Compliance Monitoring, No. 14.

OECD. (2017). *Guidance document for describing non-guideline in vitro test methods*. Paris, FR: OECD Publishing.

OECD. (2018). *Guidance Document on Good In Vitro Method Practices (GIVIMP)*. Paris, FR: OECD Series on Testing and Assessment, No. 286.

OECD. (2020). Overview of concepts and available guidance related to Integrated Approaches to Testing and Assessment (IATA). In H. a. S. Environment, Environment

Directorate, OECD (Ed.), *OECD Series on Testing and Assessment, No. 329* (pp. 46-47): Organisation for Economic Co-operation and Development.

OECD. (2023a). *Guideline No. 497: Defined Approaches on Skin Sensitisation*.

OECD. (2023b). (Q)SAR Assessment Framework: Guidance for the regulatory assessment of (Quantitative) Structure - Activity Relationship models, predictions, and results based on multiple predictions. Paris, FR: Environment, Health and Safety, Environment Directorate, OECD.

OECD. (2024). (Q)SAR Assessment Framework: Guidance for the regulatory assessment of (Quantitative) Structure Activity Relationship models and predictions. Paris, FR: OECD Series on Testing and Assessment, No. 405.

Pain, G., Hickey, G., Mondou, M., Crump, D., Hecker, M., Basu, N., Maguire, S., 2020. Drivers of and obstacles to the adoption of toxicogenomics for chemical risk assessment: Insights from social science perspectives. Environ. Health Perspect. 128 (10), 105002. https://doi.org/10.1289/EHP6500.

Pallocca, G., Leist, M., 2022. On the usefulness of animals as a model system (part II): considering benefits within distinct use domains. Alternat. Anim. Exp. 39 (3), 531–539. https://doi.org/10.14573/altex.2207111.

Pallocca, G., Moné, M.J., Kamp, H., Luijten, M., van de Water, B., Leist, M., 2022. Next-generation risk assessment of chemicals – rolling out a human-centric testing strategy to drive 3R implementation: The RISK-HUNT3R project perspective. Alternat. Anim. Exp. 39 (3), 419–426. https://doi.org/10.14573/altex.2204051.

Punt, A., Bouwmeester, H., Schifелers, M.-J.-W.-A., Peijnenburg, A.A.C.M., 2018. Expert opinions on the acceptance of alternative methods in food safety evaluations: formulating recommendations to increase acceptance of non-animal methods for kinetics. Regul. Toxicol. Pharm. 92, 145–151. https://doi.org/10.1016/j.yrtph.2017.11.015.

Rathman, J.F., Yang, C., Zhou, H., 2018. Dempster-Shafer theory for combining in silico evidence and estimating uncertainty in chemical risk assessment. Comput. Toxicol. 6, 16–31. https://doi.org/10.1016/j.comtox.2018.03.001.

Samuelson, W., Zeckhauser, R., 1988. Status quo bias in decision making. J. Risk Uncertain. 1 (1), 7–59. https://doi.org/10.1007/BF00055564.

Schmeisser, S., Miccoli, A., von Bergen, M., Berggren, E., Braeuning, A., Busch, W., Tralau, T., 2023. New approach methodologies in human regulatory toxicology – not if, but how and when! Environ. Int. 178, 108082. https://doi.org/10.1016/j.envint.2023.108082.

Sewell, F., Alexander-White, C., Brescia, S., Currie, R.A., Roberts, R., Roper, C., Kimber, I., 2024. New approach methodologies (NAMs): identifying and overcoming hurdles to accelerated adoption. Toxicol. Res. 13 (2), tfae044.

Slovic, P., Malmfors, T., Krewski, D., Mertz, C.K., Neil, N., Bartlett, S., 1995. Intuitive toxicology II: expert and lay judgments of chemical risks in Canada. Risk Anal. 15 (6), 661–675. https://doi.org/10.1111/j.1539-6924.1995.tb01338.x.

Slovic, P., Malmfors, T., Mertz, C.K., Neil, N., Purchase, I.F.H., 1997. Evaluating chemical risks: results of a survey of the British Toxicology Society. Hum. Exp. Toxicol. 16 (6), 289–304. https://doi.org/10.1177/0960327197016006.

Stucki, A.O., Barton-Maclaren, T.S., Bhuller, Y., Henriquez, J.E., Henry, T.R., Hirn, C., Clippinger, A.J., 2022. Use of New Approach Methodologies (Nams) to meet regulatory requirements for the assessment of industrial chemicals and pesticides for effects on human health. Front. Toxicol. 4. https://doi.org/10.3389/ftox.2022.964553.

Sunstein, C.R., 1996. Social norms and social roles. Columbia Law Rev. 96 (4), 903–968. https://doi.org/10.2307/1123430.

United States Environmental Protection Agency. (2018). *Strategic plan to promote the development and implementation of alternative test methods within the TSCA program*. Washington, D.C.: U.S. Environmental Protection Agency, Office of Chemical Safety and Pollution Prevention.

United States Environmental Protection Agency. (2021). *New Approach Methods work plan*. Washington, D.C.: U.S. Environmental Protection Agency.

van der Zalm, A.J., Barroso, J., Browne, P., Casey, W., Gordon, J., Henry, T.R., Clippinger, A.J., 2022. A framework for establishing scientific confidence in New Approach Methodologies. Arch. Toxicol. 96 (11), 2865–2879. https://doi.org/10.1007/s00204-022-03365-4.

Westmoreland, C., Bender, H.J., Doe, J.E., Jacobs, M.N., Kass, G.E.N., Madia, F., Cronin, M.T.D., 2022. Use of New Approach Methodologies (NAMs) in regulatory decisions for chemical safety: Report from an EPA Deep Dive Workshop. Regul. Toxicol. Pharm. 135, 105261. https://doi.org/10.1016/j.yrtph.2022.105261.

Zaunbrecher, V., Beryt, E., Parodi, D., Telesca, D., Doherty, J., Malloy, T., Allard, P., 2017. Has toxicity testing moved into the 21st century? a survey and analysis of perceptions in the field of toxicology. Environ. Health Perspect. 125 (8). https://doi.org/10.1289/ehp1435.