The long way from raw data to NAM-based information: Overview on data layers and processing steps.

Toxicological test methods generate raw data and provide instructions on how to use these to determine a final outcome such as a classification of test compounds as hits or non-hits. The data processing pipeline provided in the test method description is often highly complex. Usually, multiple layers of data, ranging from a machine-generated output to the final hit definition, are considered.

Challenges and opportunities for validation of AI-based new approach methods.

The integration of artificial intelligence (AI) into new approach methods (NAMs) for toxicology rep-resents a paradigm shift in chemical safety assessment. Harnessing AI appropriately has enormous potential to streamline validation efforts. This review explores the challenges, opportunities, and future directions for validating AI-based NAMs, highlighting their transformative potential while acknowledging the complexities involved in their implementation and acceptance.

Navigating the unseen peril: safeguarding medical imaging in the age of AI.

In response to the increasing significance of artificial intelligence (AI) in healthcare, there has been increased attention - including a Presidential executive order to create an AI Safety Institute - to the potential threats posed by AI. While much attention has been given to the conventional risks AI poses to cybersecurity, and critical infrastructure, here we provide an overview of some unique challenges of AI for the medical community. Above and beyond obvious concerns about vetting algorithms that impact patient care, there are additional subtle yet equally important things to consider: the potential harm AI poses to its own integrity and the broader medical information ecosystem.

E-validation - Unleashing AI for validation.

The validation of new approach methods (NAMs) in toxicology faces significant challenges, including the integration of diverse data, selection of appropriate reference chemicals, and lengthy, resource-intensive consensus processes. This article proposes an artificial intelligence (AI)-based approach, termed e-validation, to optimize and accelerate the NAM validation process. E-vali-dation employs advanced machine learning and simulation techniques to systematically design validation studies, select informative reference chemicals, integrate existing data, and provide tailored training.

Leveraging biomarkers and translational medicine for preclinical safety - Lessons for advancing the validation of alternatives to animal testing.

This article explores the potential of principles established in translational medicine for the use of bio-markers to advance the validation of alternatives to animal testing in preclinical safety assessment. It examines especially how such principles can enhance the predictive power, mechanistic under-standing, and human relevance of new approach methodologies (NAMs). Key concepts from translational medicine, such as fit-for-purpose validation, evidence-based approaches, and inte-grated testing strategies, are already being applied to the development and validation of NAMs.

The validation of regulatory test methods - Conceptual, ethical, and philosophical foundations.

Validation establishes the reproducibility and relevance of regulatory test methods, particularly for new approach methods (NAMs) as alternatives to animal testing. While validation concepts provide a framework to assess method suitability, they rarely undergo method-critical assessment. This paper explores the philosophical and ethical foundations of the validation process, drawing from various philosophical traditions and contemporary ethical frameworks.

Human Neural Organoid Microphysiological Systems Show the Building Blocks Necessary for Basic Learning and Memory.

Brain Microphysiological Systems including neural organoids derived from human induced pluripotent stem cells offer a unique lens to study the intricate workings of the human brain. This paper investigates the foundational elements of learning and memory in neural organoids, also known as Organoid Intelligence by quantifying immediate early gene expression, synaptic plasticity, neuronal network dynamics, and criticality to demonstrate the utility of these organoids in basic science research. Neural organoids showed synapse formation, glutamatergic and GABAergic receptor expression, immediate early gene expression basally and evoked, functional connectivity, criticality, and synaptic plasticity in response to theta-burst stimulation.

Cross-mapping of terms used in chemical risk assessment with those used in systematic review: research protocol.

The focus on implementation of systematic review (SR) principles in chemical risk assessments (CRAs) is growing as it has the potential to advance the rigour and transparency of the CRAs. However, the SR and CRA communities use their own specific terminologies. Understanding the meaning of core SR and CRA terms and where they overlap is critical for application of SR methods and principles in CRAs.

Toward a nomenclature consensus for diverse intelligent systems: Call for collaboration.

Disagreements about language use are common both between and within fields. Where interests require multidisciplinary collaboration or the field of research has the potential to impact society at large, it becomes critical to minimize these disagreements where possible. The development of diverse intelligent systems, regardless of the substrate (e.

The Implementation Moonshot Project for Alternative Chemical Testing (IMPACT) toward a Human Exposome Project.

The Human Exposome Project aims to revolutionize our understanding of how environmental exposures affect human health by systematically cataloging and analyzing the myriad exposures individuals encounter throughout their lives. This initiative draws a parallel with the Human Genome Project, expanding the focus from genetic factors to the dynamic and complex nature of environ-mental interactions. The project leverages advanced methodologies such as omics technologies, biomonitoring, microphysiological systems (MPS), and artificial intelligence (AI), forming the foun-dation of exposome intelligence (EI) to integrate and interpret vast datasets.

Trust your gut: Establishing confidence in gastrointestinal models - An overview of the state of the science and contexts of use.

The webinar series and workshop titled “Trust Your Gut: Establishing Confidence in Gastrointestinal Models – An Overview of the State of the Science and Contexts of Use” was co-organized by NICEATM, NIEHS, FDA, EPA, CPSC, DoD, and the Johns Hopkins Center for Alternatives to Animal Testing (CAAT) and hosted at the National Institutes of Health in Bethesda, MD, USA on October 11-12, 2023. New approach methods (NAMs) for assessing issues of gastrointestinal tract (GIT)- related toxicity offer promise in addressing some of the limitations associated with animal-based assessments. GIT NAMs vary in complexity, from two-dimensional monolayer cell line-based systems to sophisticated 3-dimensional organoid systems derived from human primary cells.

60 Years of the 3Rs symposium: Lessons learned and the road ahead.

When The Principles of Humane Experimental Technique was published in 1959, authors William Russell and Rex Burch had a modest goal: to make researchers think about what they were doing in the laboratory – and to do it more humanely. Sixty years later, their groundbreaking book was celebrated for inspiring a revolution in science and launching a new field: The 3Rs of alternatives to animal experimentation. On November 22, 2019, some pioneering and leading scientists and researchers in the field gathered at the Johns Hopkins Bloomberg School of Public Health in Bal­timore for the 60 Years of the 3Rs Symposium: Lessons Learned and the Road Ahead.

Revolutionizing developmental neurotoxicity testing - a journey from animal models to advanced in vitro systems.

Developmental neurotoxicity (DNT) testing has seen enormous progress over the last two decades. Preceding even the publication of the animal-based OECD test guideline for DNT testing in 2007, a series of non-animal technology workshops and conferences that started in 2005 has shaped a community that has delivered a comprehensive battery of in vitro test methods (DNT IVB). Its data interpretation is now covered by a very recent OECD guidance (No.

Pan-Cancer Interrogation of Variants Reveals Biallelic Inactivation and Defective Base Excision Repair Across a Spectrum of Solid Tumors.

Purpose: Biallelic germline pathogenic variants of the base excision repair (BER) pathway gene predispose to colorectal cancer (CRC) and other cancers. The possible association of heterozygous variants with broader cancer susceptibility remains uncertain. This study investigated the prevalence and consequences of pathogenic variants and loss of heterozygosity (LOH) in a large pan-cancer analysis.

Metabolomics in Preclinical Drug Safety Assessment: Current Status and Future Trends.

Metabolomics is emerging as a powerful systems biology approach for improving preclinical drug safety assessment. This review discusses current applications and future trends of metabolomics in toxicology and drug development. Metabolomics can elucidate adverse outcome pathways by detecting endogenous biochemical alterations underlying toxicity mechanisms.

Protocol for designing INVITES-IN, a tool for assessing the internal validity of studies.

This protocol describes the design and development of a tool for evaluation of the internal validity of studies, which is needed to include the data as evidence in systematic reviews and chemical risk assessments. The tool will be designed specifically to be applied to cell culture studies, including, but not restricted to, studies meeting the new approach methodology (NAM) definition. The tool is called INVITES-IN (IN VITro Experimental Studies INternal validity).

The Promise and Potential of Brain Organoids.

Brain organoids are 3D in vitro culture systems derived from human pluripotent stem cells that self-organize to model features of the (developing) human brain. This review examines the techniques behind organoid generation, their current and potential applications, and future directions for the field. Brain organoids possess complex architecture containing various neural cell types, synapses, and myelination.

Brain organoids and organoid intelligence from ethical, legal, and social points of view.

Human brain organoids, aka cerebral organoids or earlier "mini-brains", are 3D cellular models that recapitulate aspects of the developing human brain. They show tremendous promise for advancing our understanding of neurodevelopment and neurological disorders. However, the unprecedented ability to model human brain development and function also raises complex ethical, legal, and social challenges.

Artificial intelligence (AI)-it's the end of the tox as we know it (and I feel fine).

The rapid progress of AI impacts diverse scientific disciplines, including toxicology, and has the potential to transform chemical safety evaluation. Toxicology has evolved from an empirical science focused on observing apical outcomes of chemical exposure, to a data-rich field ripe for AI integration. The volume, variety and velocity of toxicological data from legacy studies, literature, high-throughput assays, sensor technologies and omics approaches create opportunities but also complexities that AI can help address.

Microinstrumentation for Brain Organoids.

Brain organoids are three-dimensional aggregates of self-organized differentiated stem cells that mimic the structure and function of human brain regions. Organoids bridge the gaps between conventional drug screening models such as planar mammalian cell culture, animal studies, and clinical trials. They can revolutionize the fields of developmental biology, neuroscience, toxicology, and computer engineering.

The probable future of toxicology - probabilistic risk assessment.

Both because of the shortcomings of existing risk assessment methodologies, as well as newly available tools to predict hazard and risk with machine learning approaches, there has been an emerging emphasis on probabilistic risk assessment. Increasingly sophisticated AI models can be applied to a plethora of exposure and hazard data to obtain not only predictions for particular endpoints but also to estimate the uncertainty of the risk assessment outcome. This provides the basis for a shift from deterministic to more probabilistic approaches but comes at the cost of an increased complexity of the process as it requires more resources and human expertise.

Alternative methods go green! Green toxicology as a sustainable approach for assessing chemical safety and designing safer chemicals.

Green toxicology is marching chemistry into the 21st century. This emerging framework will transform how chemical safety is evaluated by incorporating evaluation of the hazards, exposures, and risks associated with chemicals into early product development in a way that minimizes adverse impacts on human and environmental health. The goal is to minimize toxic threats across entire supply chains through smarter designs and policies.

A Novel Approach to Increase Glial Cell Populations in Brain Microphysiological Systems.

Brain microphysiological systems (bMPS) recapitulate human brain cellular architecture and functionality more closely than traditional monolayer cultures and have become increasingly relevant for the study of neurological function in health and disease. Existing 3D brain models vary in reflecting the relative populations of different cell types present in the human brain. Most models consist mainly of neurons, while glial cells represent a smaller portion of the cell populations.