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.
The whole blood pyrogen test was first described in this journal exactly thirty years ago. Its variant based on cryopreserved blood followed one year later. Together with other monocyte activation tests (MATs), it has fundamentally changed the landscape of pyrogen testing. In the five years since the 25th anniversary article in this series, progress has been remarkable: The European Pharmaco-poeia deleted the rabbit pyrogen test (RPT) effective January 2026, ending a 55-year era; ISO 10993-1:2025 removed material-mediated pyrogenicity from mandatory evaluation endpoints for medical devices; the U.S. FDA updated its guidance on pyrogen testing; and the MAT market grew to over $600 million. New validation studies have demonstrated MAT equivalence to the RPT for both endotoxin and non-endotoxin pyrogens, and the first product-specific MAT validations have been accepted in regulatory filings in Europe and the United States. Reporter cell lines and tran-scriptomic approaches are opening next-generation detection capabilities. Yet implementation gaps persist: The MAT is still underutilized for blood transfusions, cell therapies, and airborne pyrogens. Recombinant alternatives to the Limulus amebocyte lysate assay (LAL) have finally achieved phar-macopeial recognition, addressing horseshoe crab conservation concerns. This article reviews the developments of the last five years, updates the lessons learned, and reflects on three decades of bringing a human cell-based test from the laboratory bench to global regulatory acceptance.
OECD Guideline 497 includes defined approaches (DAs) that combine new approach methodologies (NAMs) to predict skin sensitization hazard and categorize potency according to the United Nations Globally Harmonized System of Classification and Labelling of Chemicals (UN GHS). To increase flexibility, the OECD allows the substitution in the DAs of NAMs addressing the same key events (KEs) in the adverse outcome pathway (AOP). This study evaluated the implementation of the U-SENS™ assay for dendritic cell activation (KE3) within two integrated testing strategy (ITS) DAs. First, EC150 threshold values were determined via computational modeling to convert CD86 stimulation index data into ITS DA scores. The performance of the modified ITS DAs was then evaluated against available Local Lymph Node Assay (LLNA) and human reference data. For hazard identification, the ITS DAs achieved 79% balanced accuracy compared with LLNA data, and 73-74% compared with human data. For potency categorization, correct classification rates were 67-68% against LLNA and 65-67% against human data. In comparison, the LLNA showed lower performance, with 58% balanced accuracy for hazard identification and 60% for potency categorization against human data. Selected case studies illustrate the practical application of these DAs following the Guideline 497 decision flowchart. Overall, findings underscore that incorporating U-SENS™ into ITS DAs enhances flexibility without compromising predictive capacity and outperforms traditional animal testing in providing reliable skin sensitization classification outcomes.
The use of terminology related to animal-free science has grown rapidly over the past two decades; however, definitions and interpretations of key terms remain inconsistent across global regulatory, scientific, and policy contexts. The term “new approach methodology(ies)” (NAM(s)) exemplifies this issue: though rarely used prior to 2019, its uptake in scientific literature has increased substantially in recent years. Despite this growth, the term, and its acronym, “NAM”, is used with varied meanings, leading to misunderstanding regarding the types of methods described. Similarly, the term “animal” is defined differently across common language, scientific discourse, and legal frameworks, resulting in further ambiguity in what constitutes “animal-free science”. These variations can hinder productive dialogue and collaboration, particularly in international settings. This manuscript maps the current landscape of definitions of key terms such as “NAM”, “animal”, and “animal-free”, drawing on regulatory, academic, and institutional sources to enhance understanding of the range of existing interpretations. By improving transparency and clarity in terminology, this effort seeks to support more coherent and effective global communication in the field of animal-free science. In addition, the definition of NAM, as agreed by the members of the International Collaboration on Cosmetics Safety, is described. Tabulated definitions and sources are provided as a reference tool.
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.
