Identification of non-validated endocrine disrupting chemical characterization methods by screening of the literature using artificial intelligence and by database exploration.

BACKGROUND: Exposure to endocrine disrupting chemicals (EDCs) represents a critical public health threat. Several adverse health outcomes (e.g., cancers, metabolic and neurocognitive/neurodevelopmental disorders, infertility, immune diseases and allergies) are associated with exposure to EDCs. However, the regulatory tests that are currently employed in the EU to identify EDCs do not assess all of the endocrine pathways. OBJECTIVE: Our objective was to explore the literature, guidelines and databases to identify relevant and reliable test methods which could be used for prioritization and regulatory pre-validation of EDCs in missing and urgent key areas. METHODS: Abstracts of articles referenced in PubMed were automatically screened using an updated version of the AOP-helpFinder text mining approach. Other available sources were manually explored. Exclusion criteria (computational methods, specific tests for estrogen receptors, tests under validation or already validated, methods accepted by regulatory bodies) were applied according to the priorities of the French Public-privatE Platform for the Pre-validation of Endocrine disRuptors (PEPPER) characterisation methods. RESULTS: 226 unique non-validated methods were identified. These experimental methods (in vitro and in vivo) were developed for 30 species using diverse techniques (e.g., reporter gene assays and radioimmunoassays). We retrieved bioassays mainly for the reproductive system, growth/developmental systems, lipogenesis/adipogenicity, thyroid, steroidogenesis, liver metabolism-mediated toxicity, and more specifically for the androgen-, thyroid hormone-, glucocorticoid- and aryl hydrocarbon receptors. CONCLUSION: We identified methods to characterize EDCs which could be relevant for regulatory pre-validation and, ultimately for the efficient prevention of EDC-related severe health outcomes. This integrative approach highlights a successful and complementary strategy which combines computational and manual curation approaches.

Harnessing the power of novel animal-free test methods for the development of COVID-19 drugs and vaccines.

The COVID-19-inducing virus, SARS-CoV2, is likely to remain a threat to human health unless efficient drugs or vaccines become available. Given the extent of the current pandemic (people in over one hundred countries infected) and its disastrous effect on world economy (associated with limitations of human rights), speedy drug discovery is critical. In this situation, past investments into the development of new (animal-free) approach methods (NAM) for drug safety, efficacy, and quality evaluation can be leveraged. For this, we provide an overview of repurposing ideas to shortcut drug development times. Animal-based testing would be too lengthy, and it largely fails, when a pathogen is species-specific or if the desired drug is based on specific features of human biology. Fortunately, industry has already largely shifted to NAM, and some public funding programs have advanced the development of animal-free technologies. For instance, NAM can predict genotoxicity (a major aspect of carcinogenicity) within days, human antibodies targeting virus epitopes can be generated in molecular biology laboratories within weeks, and various human cell-based organoids are available to test virus infectivity and the biological processes controlling them. The European Medicines Agency (EMA) has formed an expert group to pave the way for the use of such approaches for accelerated drug development. This situation illustrates the importance of diversification in drug discovery strategies and clearly shows the shortcomings of an approach that invests 95% of resources into a single technology (animal experimentation) in the face of challenges that require alternative approaches.

Towards a 21st-century roadmap for biomedical research and drug discovery: consensus report and recommendations.

Decades of costly failures in translating drug candidates from preclinical disease models to human therapeutic use warrant reconsideration of the priority placed on animal models in biomedical research. Following an international workshop attended by experts from academia, government institutions, research funding bodies, and the corporate and non-governmental organisation (NGO) sectors, in this consensus report, we analyse, as case studies, five disease areas with major unmet needs for new treatments. In view of the scientifically driven transition towards a human pathways-based paradigm in toxicology, a similar paradigm shift appears to be justified in biomedical research. There is a pressing need for an approach that strategically implements advanced, human biology-based models and tools to understand disease pathways at multiple biological scales. We present recommendations to help achieve this.

Consensus report on the future of animal-free systemic toxicity testing.

Since March 2013, animal use for cosmetics testing for the European market has been banned. This requires a renewed view on risk assessment in this field. However, in other fields as well, traditional animal experimentation does not always satisfy requirements in safety testing, as the need for human-relevant information is ever increasing. A general strategy for animal-free test approaches was outlined by the US National Research Council`s vision document for Toxicity Testing in the 21st Century in 2007. It is now possible to provide a more defined roadmap on how to implement this vision for the four principal areas of systemic toxicity evaluation: repeat dose organ toxicity, carcinogenicity, reproductive toxicity and allergy induction (skin sensitization), as well as for the evaluation of toxicant metabolism (toxicokinetics) (Fig. 1). CAAT-Europe assembled experts from Europe, America and Asia to design a scientific roadmap for future risk assessment approaches and the outcome was then further discussed and refined in two consensus meetings with over 200 stakeholders. The key recommendations include: focusing on improving existing methods rather than favoring de novo design; combining hazard testing with toxicokinetics predictions; developing integrated test strategies; incorporating new high content endpoints to classical assays; evolving test validation procedures; promoting collaboration and data-sharing of different industrial sectors; integrating new disciplines, such as systems biology and high throughput screening; and involving regulators early on in the test development process. A focus on data quality, combined with increased attention to the scientific background of a test method, will be important drivers. Information from each test system should be mapped along adverse outcome pathways. Finally, quantitative information on all factors and key events will be fed into systems biology models that allow a probabilistic risk assessment with flexible adaptation to exposure scenarios and individual risk factors.