ALTEX最新文献

{"title":"Perception and power: Barriers to animal-free research - Animalfree Research Forum 2025.","authors":"Miriam A Zemanova, Silvia Frey","doi":"10.14573/altex.2511191","DOIUrl":"https://doi.org/10.14573/altex.2511191","url":null,"abstract":"","PeriodicalId":520550,"journal":{"name":"ALTEX","volume":"43 1","pages":"184-185"},"PeriodicalIF":5.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145986105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Alternative Safety Profiling Algorithm (ASPA) to transform next generation risk assessment into a structured and transparent process.","authors":"Marcel Leist, Silvia Tangianu, Femke Affourtit, Hedwig Braakhuis, John Colbourne, Eike Cöllen, Nadine Dreser, Sylvia E Escher, Iain Gardner, Stefan Hahn, Barry Hardy, Matthias Herzler, Barira Islam, Hennicke Kamp, Viktoria Magel, Philip Marx-Stoelting, Martijn J Moné, Patrik Lundquist, Ilse Ottenbros, Gladys Ouedraogo, Giorgia Pallocca, Bob van de Water, Mathieu Vinken, Andrew White, Manuel Pastor, Mirjam Luijten","doi":"10.14573/altex.2509081","DOIUrl":"10.14573/altex.2509081","url":null,"abstract":"<p><p>Next generation risk assessment (NGRA) strategies use animal-free new approach methodol­ogies (NAMs) to generate information concerning chemical hazard, toxicokinetics (ADME), and exposure. The information from these major pillars of data gathering is used to inform risk assessment and classification decisions. While the required types of data are widely agreed upon, the pro­cesses for data collection, integration and reporting, as well as several decisions on the depth and granularity of required data, are poorly standardized. Here, we present the Alternative Safety Pro­filing Algorithm (ASPA), a broad-purpose, transparent, and reproducible risk assessment workflow that allows documentation and integration of all types of information required for NGRA. ASPA aims to make safety assessments fully traceable for the recipient (e.g., a regulator), delineating which steps and decisions have led to the final outcome and why certain decisions were made. An overarching objective of ASPA is to ensure that identical data input yields identical outcomes in the hands of independent assessors. Therefore, ASPA is not just a data gathering workflow; it also considers data interdependencies and requires precise justification of intermediate decisions. This includes the monitoring and assessment of uncertainties. To assist users, the ASPA-assist software was developed. It formalizes the reporting process in a reproducible and standardized fashion. By guiding an operator step-by-step through the ASPA workflow, a complete and comprehensive report is assembled, whereby all data, methods, operator activities, and intermediate decisions are recorded. Practical examples illustrating the broader applicability of ASPA across various regula­tions and problem formulations are provided through case studies.</p>","PeriodicalId":520550,"journal":{"name":"ALTEX","volume":" ","pages":"158-175"},"PeriodicalIF":5.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145305163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Custom GPTs to aid in compliance checking for reporting standards in academic publishing.","authors":"Ronit Mohapatra, Thomas Hartung","doi":"10.14573/altex.2601011","DOIUrl":"https://doi.org/10.14573/altex.2601011","url":null,"abstract":"<p><p>Reporting standards have proliferated across biomedicine, yet incomplete methods reporting remains routine - less because the community doubts the value of transparency, but rather because compliance checking is tedious, inconsistently enforced, and poorly integrated into everyday writing and review. As a sequel to the Good In Vitro Reporting Standards (GIVReSt) argument that better reporting is essential infrastructure, this article explores a pragmatic next step: translating standards from static checklists into interactive, always-on guidance. We describe the development of three specialized \"compliance copilots\" built as custom GPT-based assistants - one aligned with the emerging GIVReSt, one reflecting the established ToxRTool reliability framework, and one mapped to ARRIVE for animal studies. The tools are designed to point to specific text evidence, flag missing essential information, and provide actionable suggestions while the manuscript is being written. Early benchmarking against expert assessments suggests that this approach can approx-imate human judgments for many checklist items in a fraction of the time and with high consistency. We also highlight why \"strict\" versus \"lenient\" interpretations matter, and why these systems should be framed as decision-support, not decision-makers. The central claim is cultural, not technical: arti-ficial intelligence (AI) will matter most when it makes rigorous reporting the path of least resistance, turning standards into routine practice rather than aspirational add-ons.</p>","PeriodicalId":520550,"journal":{"name":"ALTEX","volume":"43 1","pages":"3-23"},"PeriodicalIF":5.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145968260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bridging the gap in chemical risk assessment: Leveraging metabolite similarity for enhanced read-across applications.","authors":"Jenny Irwan, George E N Kass, Rupert Kellner, Alexis V Nathanail, Nelly Simetska, Matthias M Wehr, Sylvia E Escher","doi":"10.14573/altex.2508271","DOIUrl":"10.14573/altex.2508271","url":null,"abstract":"<p><p>Read-across is frequently used in chemical risk assessment to predict the toxicological properties of data-poor compounds instead of performing new animal tests. The selection of relevant source com­pounds (SCs) for read-across to data-poor target compounds (TCs) is one of the main challenges, particularly for endpoints such as chronic and developmental toxicity, where the mechanisms leading to the observed apical toxicological findings are often unknown. In this study, the predic­tivities of using chemical, biological and/or metabolite similarity to inform read-across strategies were compared. Existing data from two reference compound groups, i.e., the pesticide classes of 27 triazoles and 8 triazinyl-sulfonylureas, were used to assess the performance of the three approaches and their modular combinations to identify relevant SCs from a large database of 468 pesticide active compounds. Metabolite similarity yielded high positive predictive values (PPV) of 85-100% while sensitivity was relatively low (12-65%). Basing metabolite similarity assessment on observed or predicted metabolites yielded comparable results. Chemical and biological simi­larity alone were less effective in separating SCs from irrelevant compounds. Modular approaches combining, e.g., chemical and metabolic similarity, enhanced SC selection (PPV up to 100%). This research underscores the potential of metabolite data to strengthen read-across justifications, thereby contributing to regulatory compliance and safety evaluations. We propose the integration of metabolite similarity assessment into an existing EU-ToxRisk workflow to enhance the reliability of read-across for chemical risk assessments.</p>","PeriodicalId":520550,"journal":{"name":"ALTEX","volume":" ","pages":"262-279"},"PeriodicalIF":5.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145728163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Merck \"3 Baskets\" approach for creating roadmaps to phase out animal testing.","authors":"Kerstin Kleinschmidt-Doerr, Frederic C Pipp, Isabelle Colmagne-Poulard, Sarah Sheridan, Jeffrey Whitford, Joachim Coenen, Michael W Schmitt, Christiane Amendt, Petra Van Sloun, Brigitte Simon-Hettich, Frank Bringezu, Kyra J Cowan, Stephanie Harlfinger, Flavio Peroglio, Sarah J Silveira, Steven Johnston, Philip Hewitt","doi":"10.14573/altex.2505201","DOIUrl":"10.14573/altex.2505201","url":null,"abstract":"<p><p>Since 2023 the European Commission has been working on a roadmap for phasing out animal testing in chemical safety assessment, and in 2025 the US FDA published a roadmap to phase out animal testing for the pharmaceutical industry. We describe our Merck KGaA strategy across Life Science, Healthcare, and Electronics, introduced in 2021, to reduce animal testing by 50% by 2032 and by 75% by 2040 through our 4R program (Replace, Reduce, Refine, Responsibility). The approach focuses on what we can achieve today and avoids obstructive discussions about unre­solved issues. We have categorized all animal tests currently required for our products into three “baskets” (3B). Basket 1 (Adoption) includes animal tests for which alternatives are available and accepted, including those still required in certain regions. Basket 2 (Adaptation) contains tests for which alternatives are proposed or being developed but that cannot yet be replaced. Basket 3 (Assessment) contains tests for which innovative replacement strategies still need to be developed. This strategy guides effective short-term replacement and directs investments into areas where inno­vation can replace animal testing in the future. It coordinates the way forward for all stakeholders and creates actionable milestones toward a genuine replacement of animal testing. The collabo­rative agreement in 2024 among the members of the European Federation of Pharmaceutical Industries and Associations to adopt the 3B approach, recognized by the European Commission and the European Medicines Agency, highlights its significance as a valuable tool for fostering a more ethical and sustainable science environment across Europe.</p>","PeriodicalId":520550,"journal":{"name":"ALTEX","volume":" ","pages":"247-261"},"PeriodicalIF":5.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145644236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Findable, Accessible, Interoperable, Reusable (FAIR) Lite Principles to ensure utility of computational toxicology models.","authors":"Mark T D Cronin, Homa Basiri, Samuel J Belfield, Swapnil Chavan, Georgios Chrysochoou, Steven J Enoch, James W Firman, Anish Gomatam, Barry Hardy, Palle S Helmke, Judith C Madden, Uko Maran, Erich March-Vila, Nikolai G Nikolov, Manuel Pastor, Geven Piir, Paul L A Popelier, Sulev Sild, Aljos̆a Smajić, Nicoleta Spînu, Eva B Wedebye","doi":"10.14573/altex.2502021","DOIUrl":"10.14573/altex.2502021","url":null,"abstract":"<p><p>A broad range of computational models is available for animal-free chemical safety assessment. The models are used to predict a variety of endpoints, including adverse effects or apical endpoints, tox­icokinetic properties, and exposure, often from chemical structure or in vitro inputs alone. To support their wider use, such models need to be findable, accessible, interoperable, and reusable (FAIR). This study has reevaluated the existing FAIR principles applied to quantitative structure-activity rela­tionships (QSARs) in order to adapt these principles to a wider range of computational models. Despite the breadth and variety of approaches, many computational models comprise common components including the training series, information about the modelling engine, and the model itself. As a result, a refined set of four FAIR Lite principles is proposed based on the methodological foundations of computational toxicology which are unambiguously understood by practitioners such as developers and end-users. To this end, it is proposed that to comply with the original FAIR prin­ciples, a computational toxicology model should be associated with (i) a globally unique identifier for model citation; (ii) the capture and curation of the model; (iii) the metadata for the dependent and independent variables and, where possible, data; and (iv) storage in a searchable and inter­operable platform. The FAIR Lite principles are mapped onto the original FAIR principles applied to QSARs, thereby demonstrating that a simpler checklist approach covers all aspects.</p>","PeriodicalId":520550,"journal":{"name":"ALTEX","volume":" ","pages":"215-227"},"PeriodicalIF":5.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145140026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"National workshop on non-mammalian models in research with emphasis on the 3Rs principle.","authors":"Yasir H Siddique, Gulshan Ara, Kajal Gaur, Iqra Subhan, Javeria Fatima, Sumbul Khan, Aditi Sharma, Mohammad A Akbarsha","doi":"10.14573/altex.2601121","DOIUrl":"https://doi.org/10.14573/altex.2601121","url":null,"abstract":"","PeriodicalId":520550,"journal":{"name":"ALTEX","volume":"43 2","pages":"361-362"},"PeriodicalIF":5.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147694619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"What does \"success\" look like in compliance check decisions by the European Chemicals Agency? The curious cases of accepted read-across adaptations.","authors":"Hannah M Roe, Han-Hsuan D Tsai, Nicholas Ball, King D Oware, Gang Han, Weihsueh A Chiu, Ivan Rusyn","doi":"10.14573/altex.2505191","DOIUrl":"10.14573/altex.2505191","url":null,"abstract":"<p><p>Under the European Union’s REACH (Registration, Evaluation, Authorisation and Restriction of Chemicals) regulation, the European Chemicals Agency (ECHA) is required to assess the compliance of safety data submitted by chemical registrants. ECHA must check a proportion of registration dos­siers for compliance. From 2010 to 2023, 4,854 compliance checks (CCHs) were conducted. When dossiers lack required studies or use inappropriate adaptations, ECHA issues decisions that are publicly available. As of April 2, 2024, 2,311 such decisions had been published. This study sys­tematically analyzed these published CCH decisions, focusing on ECHA’s findings of non-compliant REACH registrations and the use of adaptations to standard information requirements. We found that over 70% of published CCH decisions included at least one adaptation, with “read-across” being the most common (48%). Among these, 83 documents contained read-across adaptations with jus­tifications that ECHA deemed plausible. To understand what made these read-across hypotheses acceptable, we evaluated them using 17 assessment elements that capture specific arguments regis­trants proposed to justify the adaptation. Elements of “acceptable” read-across hypotheses included strong evidence of (i) toxicokinetic similarity between the registered substance and its analogues, and (ii) toxicodynamic similarity, supported by bridging studies. Additional support from in vitro studies and QSAR predictions further strengthened the accepted read-across hypotheses. Overall, this analysis provides insights into what constitutes a successful read-across under REACH data requirements. By identifying and evaluating accepted cases or read-across adaptations, we high­light best practices for establishing scientifically robust justifications for chemical similarity that can meet ECHA’s high regulatory standards.</p>","PeriodicalId":520550,"journal":{"name":"ALTEX","volume":" ","pages":"127-141"},"PeriodicalIF":5.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12831182/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144763000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Review on organs-on-chips for medicines safety assessment: A European regulatory perspective.","authors":"Joana M D Portela, Polly Paul, Orla Moriarty, Peter Theunissen, Sonja Beken, Susanne Brendler-Schwaab, Corinne de Vries, Stefano Ponzano","doi":"10.14573/altex.2502061","DOIUrl":"10.14573/altex.2502061","url":null,"abstract":"<p><p>This review examines a decade (2010-2020) of organ-on-chip (OoC) development, focusing on their application in the non-clinical safety assessment of medicinal products. It includes a detailed description of the types of OoCs, the organs, tissues and interactions mimicked, as well as their various applications. A broad range of organs and combinations of organs were modelled in the reviewed OoCs, with the liver, kidney and heart being the most frequently mimicked. Consistent with this, hepatoxicity and metabolism-induced toxicity were the primary focus of safety assessments, highlighting the interest in improving safety testing in the liver. Furthermore, a list of the reported biological safety endpoints and medicinal compounds tested in all OoCs is detailed. The majority of OoCs reviewed measured toxicity using only one endpoint, which was often related to viability or cell death. In the context of the data collected, this review also includes a regulatory discussion, highlighting challenges and opportunities for increased regulatory acceptance of OoCs for safety assessment. Key considerations for OoC qualification are discussed, including the importance of defining a clear context of use and selecting relevant endpoints and reference compounds. The ongoing activities of the European Medicines Agency to promote the integration of new approach methodologies (NAMs), including OoCs, into regulatory submissions are outlined.</p>","PeriodicalId":520550,"journal":{"name":"ALTEX","volume":" ","pages":"98-112"},"PeriodicalIF":5.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144762999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fish count, too - The animal toll of REACH aquatic toxicity tests.","authors":"Jean Knight, Costanza Rovida, Kate Willett, Jay Ingram","doi":"10.14573/altex.2506011","DOIUrl":"10.14573/altex.2506011","url":null,"abstract":"<p><p>The European Union’s main chemicals regulation, Registration, Evaluation, Authorization and Restriction of Chemicals (REACH), requires chemicals to be evaluated for health and environmental impacts, with animal tests the basis for many evaluations. Most discussions of REACH animal use focus on mammals, yet fish tests are also a significant component. Here we report the animal count for fish tests completed, ongoing, and pending under REACH, based directly on test reports. The esti­mated total to date is 382,000 fish used for short-term fish toxicity, long-term fish toxicity, endocrine disruption, and bioaccumulation tests. This count does not include new tests that will result from the 2022 REACH amendment, which extends requirements for long-term fish toxicity tests and removes the most common basis for waivers previously accepted for this test. An estimated 940−1,240 new long-term fish toxicity tests may result from these changes, requiring 520,000−680,000 fish. The count also does not include the potential expansion of endocrine disruption testing in the upcoming REACH revision. New non-animal alternatives to long-term fish toxicity and endocrine disruption tests are needed to reduce these impacts. For other fish tests, recently defined non-animal methods for short-term toxicity and the newly approved Hyalella azteca bioconcentration test for bioaccu­mulation should be evaluated for inclusion in REACH guidance, both to incentivize their use and to better comply with the REACH mandate to use animal testing only as a last resort.</p>","PeriodicalId":520550,"journal":{"name":"ALTEX","volume":" ","pages":"142-157"},"PeriodicalIF":5.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145260529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}