Methodology for developing data-rich Key Event Relationships for Adverse Outcome Pathways exemplified by linking decreased androgen receptor activity with decreased anogenital distance.

The Adverse Outcome Pathway (AOP) framework has gained widespread acceptance in toxicological disciplines as a tool for aiding chemical hazard assessment. Despite increased activity in AOP development, progress towards a high volume of fully endorsed AOPs has been slow, partly due to the challenging task of constructing complete AOPs according to the AOP Developer's Handbook. To facilitate greater uptake of new knowledge units onto the open-source AOP-wiki platform, a pragmatic approach was recently proposed. This approach involves considering Key Event Relationships (KERs) for individual development through systematic approaches, as they represent essential units of knowledge from which causality can be inferred; from low complexity test data to adverse outcomes in intact organisms. However, more broadly adopted harmonized methodologies for KER development would be desirable. Using the AOP Developer's Handbook as a guide, a KER linking 'decreased androgen receptor (AR) activity' with 'reduced anogenital distance (AGD)' was developed to demonstrate a methodology applicable for future developments of KERs requiring systematic literature retrieval approaches.

Weight of Evidence: Is an Animal Study Warranted? Assessments for Carcinogenicity, Drug Abuse Liability, and Pediatric Safety.

Nonclinical safety studies are typically conducted to establish a toxicity profile of a new pharmaceutical in clinical development. Such a profile may encompass multiple differing types of animal studies, or not! Some types of animal studies may not be warranted for a specific program or may only require a limited evaluation if scientifically justified. The goal of this course was to provide a practical perspective on regulatory writing of a dossier(s) using the weight of evidence (WOE) approach for carcinogenicity, drug abuse liability and pediatric safety assessments. These assessments are typically done after some clinical data are available and are highly bespoke to the pharmaceutical being developed. This manuscript will discuss key data elements to consider and strategy options with some case studies and examples. Additionally, US FDA experience with dossier(s) including WOE arguments is discussed.

Assessing human carcinogenicity risk of agrochemicals without the rodent cancer bioassay.

The rodent cancer bioassays are conducted for agrochemical safety assessment yet they often do not inform regulatory decision-making. As part of a collaborative effort, the Rethinking Carcinogenicity Assessment for Agrochemicals Project (ReCAAP) developed a reporting framework to guide a weight of evidence (WOE)-based carcinogenicity assessment that demonstrates how to fulfill the regulatory requirements for chronic risk estimation without the need to conduct lifetime rodent bioassays. The framework is the result of a multi-stakeholder collaboration that worked through an iterative process of writing case studies (in the form of waivers), technical peer reviews of waivers, and an incorporation of key learnings back into the framework to be tested in subsequent case study development. The example waivers used to develop the framework were written retrospectively for registered agrochemical active substances for which the necessary data and information could be obtained through risk assessment documents or data evaluation records from the US EPA. This exercise was critical to the development of a framework, but it lacked authenticity in that the stakeholders reviewing the waiver already knew the outcome of the rodent cancer bioassay(s). Syngenta expanded the evaluation of the ReCAAP reporting framework by writing waivers for three prospective case studies for new active substances where the data packages had not yet been submitted for registration. The prospective waivers followed the established framework considering ADME, potential exposure, subchronic toxicity, genotoxicity, immunosuppression, hormone perturbation, mode of action (MOA), and all relevant information available for read-across using a WOE assessment. The point of departure was estimated from the available data, excluding the cancer bioassay results, with a proposed use for the chronic dietary risk assessment. The read-across assessments compared data from reliable registered chemical analogues to strengthen the prediction of chronic toxicity and/or tumorigenic potential. The prospective case studies represent a range of scenarios, from a new molecule in a well-established chemical class with a known MOA to a molecule with a new pesticidal MOA (pMOA) and limited read-across to related molecules. This effort represents an important step in establishing criteria for a WOE-based carcinogenicity assessment without the rodent cancer bioassay(s) while ensuring a health protective chronic dietary risk assessment.

Weight of evidence evaluation of the metabolism disrupting effects of triphenyl phosphate using an expert knowledge elicitation approach.

Identification of Endocrine-Disrupting Chemicals (EDCs) in a regulatory context requires a high level of evidence. However, lines of evidence (e.g. human, in vivo, in vitro or in silico) are heterogeneous and incomplete for quantifying evidence of the adverse effects and mechanisms involved. To date, for the regulatory appraisal of metabolism-disrupting chemicals (MDCs), no harmonised guidance to assess the weight of evidence has been developed at the EU or international level. To explore how to develop this, we applied a formal Expert Knowledge Elicitation (EKE) approach within the European GOLIATH project. EKE captures expert judgment in a quantitative manner and provides an estimate of uncertainty of the final opinion. As a proof of principle, we selected one suspected MDC -triphenyl phosphate (TPP) - based on its related adverse endpoints (obesity/adipogenicity) relevant to metabolic disruption and a putative Molecular Initiating Event (MIE): activation of peroxisome proliferator activated receptor gamma (PPARγ). We conducted a systematic literature review and assessed the quality of the lines of evidence with two independent groups of experts within GOLIATH, with the objective of categorising the metabolic disruption properties of TPP, by applying an EKE approach. Having followed the entire process separately, both groups arrived at the same conclusion, designating TPP as a "suspected MDC" with an overall quantitative agreement exceeding 85%, indicating robust reproducibility. The EKE method provides to be an important way to bring together scientists with diverse expertise and is recommended for future work in this area.

Normalised similarity assessment to inform grouping of advanced multi-component nanomaterials by means of an Asymmetric Sigmoid function.

This manuscript presents a procedure for similarity assessment as a basis for grouping of multi component nanomaterials (MCNMs). This methodology is an adaptation of the approach by Zabeo et al. (2022), which includes an impactful change: the calculated similarities are normalised in the [0,1] domain by means of asymmetric Logistic scaling to simplify comparisons among properties' distances. This novel approach allows for grouping of nanomaterials that is not affected by the dataset, so that group membership will not change when new candidates are included in the set of assessed materials. It can be applied to assess groups of MCNMs as well as mixed groups of multi and single component nanomaterials as well as chemicals. To facilitate the application of the proposed methodology, a software script was developed by using the Python programming language, which is currently undergoing migration to a user-friendly web-based tool. The presented approach was tested against a real industrial case study provided by the Andalusian Innovation Centre for Sustainable Solution (CIAC): SiO2-ZnO hybrid nanocomposite used in building coatings, which is designed to facilitate photocatalytic removal of NOx gases from the atmosphere. The results of applying the methodology in the case study demonstrated that ZnO is dissimilar from the other candidates mainly due to its different dissolution profiles.

ICH S1 prospective evaluation study and weight of evidence assessments: commentary from industry representatives.

Industry representatives on the ICH S1B(R1) Expert Working Group (EWG) worked closely with colleagues from the Drug Regulatory Authorities to develop an addendum to the ICH S1B guideline on carcinogenicity studies that allows for a weight-of-evidence (WoE) carcinogenicity assessment in some cases, rather than conducting a 2-year rat carcinogenicity study. A subgroup of the EWG composed of regulators have published in this issue a detailed analysis of the Prospective Evaluation Study (PES) conducted under the auspices of the ICH S1B(R1) EWG. Based on the experience gained through the Prospective Evaluation Study (PES) process, industry members of the EWG have prepared the following commentary to aid sponsors in assessing the standard WoE factors, considering how novel investigative approaches may be used to support a WoE assessment, and preparing appropriate documentation of the WoE assessment for presentation to regulatory authorities. The commentary also reviews some of the implementation challenges sponsors must consider in developing a carcinogenicity assessment strategy. Finally, case examples drawn from previously marketed products are provided as a supplement to this commentary to provide additional examples of how WoE criteria may be applied. The information and opinions expressed in this commentary are aimed at increasing the quality of WoE assessments to ensure the successful implementation of this approach.

Fuzzy cognitive mapping in participatory research and decision making: a practice review.

BACKGROUND: Fuzzy cognitive mapping (FCM) is a graphic technique to describe causal understanding in a wide range of applications. This practice review summarises the experience of a group of participatory research specialists and trainees who used FCM to include stakeholder views in addressing health challenges. From a meeting of the research group, this practice review reports 25 experiences with FCM in nine countries between 2016 and 2023. RESULTS: The methods, challenges and adjustments focus on participatory research practice. FCM portrayed multiple sources of knowledge: stakeholder knowledge, systematic reviews of literature, and survey data. Methodological advances included techniques to contrast and combine maps from different sources using Bayesian procedures, protocols to enhance the quality of data collection, and tools to facilitate analysis. Summary graphs communicating FCM findings sacrificed detail but facilitated stakeholder discussion of the most important relationships. We used maps not as predictive models but to surface and share perspectives of how change could happen and to inform dialogue. Analysis included simple manual techniques and sophisticated computer-based solutions. A wide range of experience in initiating, drawing, analysing, and communicating the maps illustrates FCM flexibility for different contexts and skill bases. CONCLUSIONS: A strong core procedure can contribute to more robust applications of the technique while adapting FCM for different research settings. Decision-making often involves choices between plausible interventions in a context of uncertainty and multiple possible answers to the same question. FCM offers systematic and traceable ways to document, contrast and sometimes to combine perspectives, incorporating stakeholder experience and causal models to inform decision-making. Different depths of FCM analysis open opportunities for applying the technique in skill-limited settings.

Remote sensing and geospatial approach: Optimizing groundwater exploration in semi-arid region, Nepal.

Groundwater is the fundamental component of the hydrological system that acts as a major factor in comprehensions of the physical processes in both the land surface and the atmosphere. Determining groundwater, which directly affects the agricultural productivity of semi-arid mountainous regions, is crucial. Mountain ecosystems, once abundant with flowing water, now face immense pressure from a changing climate, evident in the drying of springs and the diminishing flow of groundwater. Ensuring a steady flow of water, fair access to it, and responsible use are the cornerstones of a secure future for mountain communities. This study aims to assess the groundwater potential zones using remote sensing and a geospatial approach in the Mustang Valley's rural municipalities (Thasang and Gharapjhong). Nine factors were assigned to assess the groundwater potential map: slope, drainage density, lineament density, geology, soil, land use/land cover, rainfall, aspect, and soil moisture. The Bayesian weights of evidence model was used to delineate the groundwater potential zone. The study categorized groundwater potential across the region, creating five zones: very high, high, moderate, low, and very low. These zones covered 0.6 %, 12.4 %, 51.2 %, 35.5 %, and 0.3 % of the study area. The accuracy of the groundwater potential map was assessed by comparing its predictions with the actual locations of springs, using the area under the curve metric. The receiver operating characteristics curve analysis yielded an area under the curve of 0.7226, indicating a 72.26 % accuracy in predicting the presence of groundwater. The findings of this paper contribute to a better understanding of groundwater potential zones, which can support policymakers and planners for hydrological, meteorological, and crop planning applications in this climatically vulnerable region.

Evaluation of the Interaction-Based Hazard Index Formula Using Data on Four Trihalomethanes from U.S. EPA's Multiple-Purpose Design Study.

The interaction-based hazard index (HIINT), a mixtures approach to characterizing toxicologic interactions, is demonstrated and evaluated by statistically analyzing data on four regulated trihalomethanes (THMs). These THMs were the subject of a multipurpose toxicology study specifically designed to evaluate the HIINT formula. This HIINT evaluation uses single, binary and quaternary mixture THM data. While this research is considered preliminary, the results provide insights on the application of HIINT when toxicology mixture data are available and on improvements to the method. The results for relative liver weight show the HIINT was generally not conservative but did adjust the additive hazard index (HI) in the correct direction, predicting greater than dose-additivity, as seen in the mixture data. For the liver serum enzyme endpoint alanine aminotransferase, the results were mixed, with some indices giving an estimated effective dose lower than the observed mixture effective dose and others higher; in general, the HIINT adjusted the HI in the correct direction, predicting less than dose-additivity. In addition, a methodological improvement was made in the calculation of maximum interaction magnitude. Suggested refinements to the HIINT included mixture-specific replacements for default parameter values and approaches for supplementing the usual qualitative discussions of uncertainty with numerical descriptions.

Looking beyond the obvious: The ecotoxicological impact of the leachate from fishing nets and cables in the marine mussel Mytilus galloprovincialis.

Once in the marine environment, fishing nets and cables undergo weathering, breaking down into micro and nano-size particles and leaching plastic additives, which negatively affect marine biota. This study aims to unravel the ecotoxicological impact of different concentrations of leachate obtained from abandoned or lost fishing nets and cables in the mussel Mytilus galloprovincialis under long-term exposure (28 days). Biochemical biomarkers linked to antioxidant defense system, xenobiotic biotransformation, oxidative damage, genotoxicity, and neurotoxicity were evaluated in different mussel tissues. The chemical nature of the fishing nets and cables and the chemical composition of the leachate were assessed and metals, plasticizers, UV stabilizers, flame retardants, antioxidants, dyes, flavoring agents, preservatives, intermediates and photo initiators were detected. The leachate severely affected the antioxidant and biotransformation systems in mussels' tissues. Following exposure to 1 mg·L-1 of leachate, mussels' defense system was enhanced to prevent oxidative damage. In contrast, in mussels exposed to 10 and 100 mg·L-1 of leachate, defenses failed to overcome pro-oxidant molecules, resulting in genotoxicity and oxidative damage. Principal component analysis (PCA) and Weight of Evidence (WOE) evaluation confirmed that mussels were significantly affected by the leachate being the hazard of the leachate concentrations of 10 mg·L-1 ranked as major, while 1 and 100 mg·L-1 was moderate. These results highlighted that the leachate from fishing nets and cables can be a threat to the heath of the mussel M. galloprovincialis.

Prioritizing of potential environmental exposure carcinogens beyond IARC group 1-2B based on weight of evidence (WoE) approach.

Environmental exposures are the main cause of cancer, and their carcinogenicity has not been fully evaluated, identifying potential carcinogens that have not been evaluated is critical for safety. This study is the first to propose a weight of evidence (WoE) approach based on computational methods to prioritize potential carcinogens. Computational methods such as read across, structural alert, (Quantitative) structure-activity relationship and chemical-disease association were evaluated and integrated. Four different WoE approach was evaluated, compared to the best single method, the WoE-1 approach gained 0.21 and 0.39 improvement in the area under the receiver operating characteristic curve (AUC) and Matthew's correlation coefficient (MCC) value, respectively. The evaluation of 681 environmental exposures beyond IARC list 1-2B prioritized 52 chemicals of high carcinogenic concern, of which 21 compounds were known carcinogens or suspected carcinogens, and eight compounds were identified as potential carcinogens for the first time. This study illustrated that the WoE approach can effectively complement different computational methods, and can be used to prioritize chemicals of carcinogenic concern.

Evaluation of urban flood susceptibility through integrated Bivariate statistics and Geospatial technology.

Flood disasters are frequent natural disasters that occur annually during the monsoon season and significantly impact urban areas. This area is characterized by impermeable concrete surfaces, which increase runoff and are particularly susceptible to flooding. Therefore, this study aims to adopt Bi-variate statistical methods such as frequency ratio (FR) and weight of evidence (WOE) to map flood susceptibility in an urbanized watershed. The study area encompasses an urbanized watershed surrounding the Chennai Metropolitan area in southern India. The essential parameters considered for flood susceptibility zonation include geomorphology, soil, land use/land cover (LU/LC), rainfall, drainage, slope, aspect, Topographic Wetness Index (TWI), and Normalized Difference Vegetation Index (NDVI). The flood susceptibility map was derived using 70% of randomly selected flood areas from the flood inventory database, and the other 30% was used for validation using the area under curve (AUC) method. The AUC method produced a frequency ratio of 0.806 and a weight of evidence value of 0.865 contributing to the zonation of the three classes. The study further investigates the impact of urbanization on flood susceptibility and is further classified into high, moderate, and low flood risk zones. With the abrupt change in climatic scenarios, there is an increase in the risk of flash floods. The results of this study can be used by policymakers and planners in developing a preparedness system to mitigate economic, human, and property losses due to floods in any urbanized watershed.

A framework for integrating evidence to assess hazards and risk.

To accurately characterize human health hazards, human, animal, and mechanistic data must be integrated and the relevance to the research question of all three lines of evidence must be considered. Mechanistic data are often critical to the full integration of animal and human data and to characterizing relevance and uncertainty. This novel evidence integration framework (EIF) provides a method for synthesizing data from comprehensive, systematic, quality-based assessments of the epidemiological and toxicological literature, including in vivo and in vitro mechanistic studies. It organizes data according to both the observed human health effects and the mechanism of action of the chemical, providing a method to support evidence synthesis. The disease-based component uses the evidence of human health outcomes studied in the best quality epidemiological literature to organize the toxicological data according to authors' stated purpose, with the pathophysiology of the disease determining the potential relevance of the toxicological data. The mechanism-based component organizes the data based on the proposed mechanisms of effect and data supporting events leading to each endpoint, with the epidemiological data potentially providing corroborating information. The EIF includes a method to cross-classify and describe the concordance of the data, and to characterize its uncertainty. At times, the two methods of organizing the data may lead to different conclusions. This facilitates identification of knowledge gaps and shows the impact of uncertainties on the strength of causal inference.

Drug review process advancement and required manufacturer and contract research oraganization responses.

The United States Senate passed the "FDA Modernization Act 2.0." on September 29, 2022. Although the effectiveness of this Bill, which aims to eliminate the mandatory use of laboratory animals in new drug development, is limited, it represents a significant trend that will change the shape of drug applications in the United States and other countries. However, pharmaceutical companies have not taken major steps towards the complete elimination of animal testing from the standpoint of product safety, where they prioritize patient safety. Nonetheless, society is becoming increasingly opposed to animal testing, and efforts will be made to use fewer animals and conduct fewer animal tests as a natural and reasonable response. These changes eventually alter the shape of new drug applications. Based on the assumption that fewer animal tests will be conducted or fewer animals will be used in testing, this study explored bioinformatics and new technologies as alternatives to compensate for reduced information and provide a picture of how future new drug applications may look. The authors also discuss the directions that pharmaceutical companies and nonclinical contract research organizations should adopt to promote the replacement, reduction, and refinement of animals used in research, teaching, testing, and exhibitions.

ICH S1 prospective evaluation study: weight of evidence approach to predict outcome and value of 2-year rat carcinogenicity studies. A report from the regulatory authorities subgroup.

Introduction: The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) initiated a process in 2012 to revise the S1B Guideline "Testing for Carcinogenicity of Pharmaceuticals". Previous retrospective analysis indicated the importance of histopathological risk factors in chronic toxicity studies, evidence of endocrine perturbation, and positive genetic toxicology results as potentially predictive indicators of carcinogenic risk. In addition, a relationship between pharmacodynamic activity and carcinogenicity outcome in long-term rodent studies has been reported. It was postulated that these factors could be evaluated in a Weight-of-Evidence (WoE) approach to predict the outcome of a 2-year rat study. Methods: The ICH S1B(R1) Expert Working Group (EWG) conducted a Prospective Evaluation Study (PES) to determine the regulatory feasibility of this WoE approach. Drug Regulatory Authorities (DRAs) evaluated 49 Carcinogenicity Assessment Documents (CADs), which describe the WoE for submitted pharmaceutical compounds. Each compound was categorized into a carcinogenic risk category including a statement of the value of the 2-year rat study. The outcome of the completed 2-year rat studies was evaluated in relation to the prospective CAD to determine the accuracy of predictions. Results: Based on the results of the PES, the EWG concluded that the evaluation process for assessing human carcinogenic risk of pharmaceuticals described in ICH S1B could be expanded to include a WoE approach. Approximately 27% of 2-year rat studies could be avoided in cases where DRAs and sponsors unanimously agreed that such a study would not add value. Discussion: Key factors supporting a WoE assessment were identified: data that inform carcinogenic potential based on drug target biology and the primary pharmacologic mechanism of the parent compound and major human metabolites; results from secondary pharmacology screens for this compound and major human metabolites that inform carcinogenic risk; histopathology data from repeated-dose toxicity studies; evidence for hormonal perturbation; genotoxicity data; and evidence of immune modulation. The outcome of the PES indicates that a WoE approach can be used in place of conducting a 2-year rat study for some pharmaceuticals. These data were used by the ICH S1B(R1) EWG to write the R1 Addendum to the S1B Guideline published in August 2022.

A quantitative weight-of-evidence method for confidence assessment of adverse outcome pathway networks: A case study on chemical-induced liver steatosis.

The field of chemical toxicity testing is undergoing a transition to overcome the limitations of in vivo experiments. This evolution involves implementing innovative non-animal approaches to improve predictability and provide a more precise understanding of toxicity mechanisms. Adverse outcome pathway (AOP) networks are pivotal in organizing existing mechanistic knowledge related to toxicological processes. However, these AOP networks are dynamic and require regular updates to incorporate the latest data. Regulatory challenges also persist due to concerns about the reliability of the information they offer. This study introduces a generic Weight-of-Evidence (WoE) scoring method, aligned with the tailored Bradford-Hill criteria, to quantitatively assess the confidence levels in key event relationships (KERs) within AOP networks. We use the previously published AOP network on chemical-induced liver steatosis, a prevalent form of human liver injury, as a case study. Initially, the existing AOP network is optimized with the latest scientific information extracted from PubMed using the free SysRev platform for artificial intelligence (AI)-based abstract inclusion and standardized data collection. The resulting optimized AOP network, constructed using Cytoscape, visually represents confidence levels through node size (key event, KE) and edge thickness (KERs). Additionally, a Shiny application is developed to facilitate user interaction with the dataset, promoting future updates. Our analysis of 173 research papers yielded 100 unique KEs and 221 KERs among which 72 KEs and 170 KERs, respectively, have not been previously documented in the prior AOP network or AOP-wiki. Notably, modifications in de novo lipogenesis, fatty acid uptake and mitochondrial beta-oxidation, leading to lipid accumulation and liver steatosis, garnered the highest KER confidence scores. In conclusion, our study delivers a generic methodology for developing and assessing AOP networks. The quantitative WoE scoring method facilitates in determining the level of support for KERs within the optimized AOP network, offering valuable insights into its utility in both scientific research and regulatory contexts. KERs supported by robust evidence represent promising candidates for inclusion in an in vitro test battery for reliably predicting chemical-induced liver steatosis within regulatory frameworks.

Advancing Endocrine Disruptors via In Vitro Evaluation: Recognizing the Significance of the Organization for Economic Co-Operation and Development and United States Environmental Protection Agency Guidelines, Embracing New Assessment Methods, and the Urgent Need for a Comprehensive Battery of Tests.

Efforts are being made globally to improve the evaluation and understanding of endocrine-disrupting chemicals. Recognition of their impact on human health and the environment has stimulated attention and research in this field. Various stakeholders, including scientists, regulatory agencies, policymakers, and industry representatives, are collaborating to develop robust methodologies and guidelines for assessing these disruptors. A key aspect of these efforts is the development of standardized testing protocols and guidelines that aim to provide consistent and reliable methods for identifying and characterizing endocrine disruptors. When evaluating the potential endocrine-disrupting activity of chemicals, no single test is capable of detecting all relevant endocrine-disrupting agents. The test battery approach is designed to reduce the risk of false negative results for compounds with toxic potential. A weight-of-evidence approach is therefore necessary for endocrine disruptor evaluation. This approach considers various types of data from multiple sources, assessing the overall strength, consistency, and reliability of the evidence. OECD guidelines are highly regarded for their scientific rigor, transparency, and consensus-based development process. It is crucial to explore and develop new methodologies that can effectively evaluate the risks associated with potential endocrine disruptors. Integrating these methods into a comprehensive weight-of-evidence framework will enhance risk assessments and facilitate informed decisions regarding the regulation and management of these substances, ensuring the protection of human health and the environment from their adverse effects.

Use of human predictive patch test (HPPT) data for the classification of skin sensitization hazard and potency.

Since the 1940s, patch tests in healthy volunteers (Human Predictive Patch Tests, HPPTs) have been used to identify chemicals that cause skin sensitization in humans. Recently, we reported the results of a major curation effort to support the development of OECD Guideline 497 on Defined Approaches (DAs) for skin sensitization (OECD in Guideline No. 497: Defined Approaches on Skin Sensitisation, 2021a. https://doi.org/10.1787/b92879a4-en ). In the course of this work, we compiled and published a database of 2277 HPPT results for 1366 unique test substances (Strickland et al. in Arch Toxicol 97:2825-2837, 2023. https://doi.org/10.1007/s00204-023-03530-3 ). Here we report a detailed analysis of the value of HPPT data for classification of chemicals as skin sensitizers under the United Nations' Globally Harmonized System of Classification and Labelling of Chemicals (GHS). As a result, we propose the dose per skin area (DSA) used for classification by the GHS to be replaced by or complemented with a dose descriptor that may better reflect sensitization incidence [e.g., the DSA causing induction of sensitization in one individual (DSA1+) or the DSA leading to an incidence of induction in 5% of the tested individuals (DSA05)]. We also propose standardized concepts and workflows for assessing individual HPPT results, for integrating multiple HPPT results and for using them in concert with Local Lymph Node Assay (LLNA) data in a weight of evidence (WoE) assessment. Overall, our findings show that HPPT results are often not sufficient for deriving unambiguous classifications on their own. However, where they are, the resulting classifications are reliable and reproducible and can be integrated well with those from other skin sensitization data, such as the LLNA.

Allergic to bureaucracy? Regulatory allergenicity assessments of novel food: Motivations, challenges, compromises, and possibilities.

New sources of proteins are essential to meet the demands of the growing world population and evolving food trends. Assessing the allergenicity of proteins in novel food (NF) poses a significant food safety regulatory challenge. The Codex Alimentarius Commission presented an allergenicity assessment protocol for genetically modified (GM) foods, which can also be adapted for NF. Since no single laboratory test can adequately predict the allergenic potential of NF, the protocol follows a weight-of-evidence approach, evaluated by experts, as part of a risk management process. Regulatory bodies worldwide have adopted this safety protocol, which, among other things, promotes global harmonization. This review unravels the reliability and various motivations, terms, concepts, and approaches of allergenicity assessments, aiming to enhance understanding among manufacturers and the public. Health Canada, Food Safety Commission JAPAN, and Food Standards Australia New Zealand were surveyed, focusing on the European Food Safety Authority and the US Food Safety Administration for examples of scientific opinions regarding allergenicity assessments for novel and GM foods, from 2019 to 2023. According to our findings, current regulatory allergenicity assessments for NF approval primarily rely on literature reviews. Only a few of the NF assessments proactively presented additional tests. We recommend conducting bioinformatic analyses on NF when a panel of experts deems that there is insufficient prior scientific research.

Procedural application of mode-of-action and human relevance analysis: styrene-induced lung tumors in mice.

Risk assessment of human health hazards has traditionally relied on experiments that use animal models. Although exposure studies in rats and mice are a major basis for determining risk in many cases, observations made in animals do not always reflect health hazards in humans due to differences in biology. In this critical review, we use the mode-of-action (MOA) human relevance framework to assess the likelihood that bronchiolar lung tumors observed in mice chronically exposed to styrene represent a plausible tumor risk in humans. Using available datasets, we analyze the weight-of-evidence 1) that styrene-induced tumors in mice occur through a MOA based on metabolism of styrene by Cyp2F2; and 2) whether the hypothesized key event relationships are likely to occur in humans. This assessment describes how the five modified Hill causality considerations support that a Cyp2F2-dependent MOA causing lung tumors is active in mice, but only results in tumorigenicity in susceptible strains. Comparison of the key event relationships assessed in the mouse was compared to an analogous MOA hypothesis staged in the human lung. While some biological concordance was recognized between key events in mice and humans, the MOA as hypothesized in the mouse appears unlikely in humans due to quantitative differences in the metabolic capacity of the airways and qualitative uncertainties in the toxicological and prognostic concordance of pre-neoplastic and neoplastic lesions arising in either species. This analysis serves as a rigorous demonstration of the framework's utility in increasing transparency and consistency in evidence-based assessment of MOA hypotheses in toxicological models and determining relevance to human health.