Established and emerging new approach methodologies in neuroscience

The increasing need for ethical, human-relevant, and efficient alternatives to animal testing is driving the development of New Approach Methodologies (NAMs) in safety assessment and drug development. However, the inherent complexity of neurological diseases presents a significant challenge to fully replace animal models in this field. In neuroscience, a range of NAMs, from traditional 2D cell cultures to advanced brain organoids and alternative vertebrate models like zebrafish, demonstrate complementary strengths and limitations. Together, these models support translational research, including the investigation of neurodevelopment, disease, and neurotoxicity. While human and mouse brain organoids that mimic the structural and functional properties of mammalian brain tissue hold great promise, their applicability for high-throughput screening is hindered by their cost- and time-intensive nature. Complementary approaches such as embryonic and larval zebrafish models and the emerging zebrafish brain organoids provide faster, cost-effective, and scalable yet biologically relevant platforms for early-phase screening, thanks to the zebrafish’s rapid development, conserved vertebrate neuroanatomy, and proven value in toxicology. This review maps the current landscape of NAMs in neuroscience, examining approaches ranging from 2D and 3D in vitro systems to zebrafish models. It highlights the advantages and challenges of the different models, including a comparison of human, mouse, and zebrafish brain organoids, and outlines the future directions for integrating these complementary systems into robust, efficient, and ethically responsible pipelines for both early-phase toxicity testing and drug discovery.

Introduction

The fields of toxicology and drug development are undergoing a pivotal transformation, driven by the need for more ethical, human-relevant and predictive testing systems in accordance with the 3Rs principle (i.e., replacing, reducing, and/or refining animal studies) (Krewski et al., 2010; Kavlock et al., 2009; Punt et al., 2020; Schmeisser et al., 2023). Traditional animal models, such as rodents, have been indispensable for decades, offering critical insights into disease mechanisms and safety assessment. Undoubtedly, they continue to play a vital role in advancing our understanding today. However, given the ethical concerns, as well as the significant time and cost associated with animal testing, there is a growing incentive to reduce animal use where possible, without compromising scientific rigor and safety. This has accelerated the development of New Approach Methodologies (NAMs) (Turner et al., 2023), being alternative approaches that minimize or eliminate animal use and may complement or even improve the predictive power for human health outcomes, although, in some cases, further validation is needed.

The development and implementation of effective and reliable NAMs is also becoming necessary to meet legal regulatory requirements mandating the use of scientifically valid non-animal testing methods (European Parliament and Council, 2009; European Parliament and Council, 2006; OECD, 2022). In recent years, legislation and regulatory guidance from agencies such as the US Food and Drug Administration (FDA) and the European Medicines Agency (EMA), along with EU policies like the ban on animal testing for cosmetics (European Parliament and Council, 2009) and the Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) regulation (European Parliament and Council, 2006), have created a strong incentive to advance alternative methods.

NAMs encompass a wide variety of innovative technologies and methodologies, each with its own strengths and limitations. These include, but are not limited to, in silico models, basic in vitro toxicity assays, monolayer 2D cell cultures, organotypic co-cultures, 3D culture systems such as patient-derived organoids, more advanced microphysiological systems (e.g., organ-on-a-chip and tissue-on-a-chip), and the use of alternative non-mammalian species, including both vertebrates [e.g., Danio rerio (zebrafish) and Oryzias latipes and Oryzias melastigma (medaka)] and non-vertebrates [e.g., Daphnia magna (water flea) and Drosophila melanogaster (fruit fly)] (Turner et al., 2023; Schneider et al., 2021).

Among these, human organoids have emerged as one of the most promising in vitro tools in modern biomedical research (Kim et al., 2020; Matsui and Shinozawa, 2021). Brain organoids in particular, represent a breakthrough for neuroscience and neurotoxicology (Lancaster et al., 2013), enabling disease modeling, the study of human neurodevelopment, and responses to chemical exposure (e.g., neurotoxicants and candidate therapeutic compounds in development) in a more physiologically relevant context than traditional 2D cultures (Cao, 2022; Fan et al., 2022; Lei et al., 2024). However, despite these advantages, human brain organoids are not without limitations. Their production is time-consuming and resource-intensive, often requiring months to reach maturation stages suitable for experimentation (Qian et al., 2019). Compared to standard cell lines, brain organoids require specialized media, growth factors, and labor-intensive protocols, which raise costs considerably, often approaching those of small-scale animal models such as mice and significantly exceeding those of aquatic model organisms like zebrafish. Additionally, reproducibility between organoid batches can vary (Maisumu et al., 2025), and achieving complete representation of human brain complexity, such as vasculature (Lancaster et al., 2013; Cakir et al., 2019), microglia (Ormel et al., 2018; Sabate-Soler et al., 2022), and regional specification, remains challenging. These constraints limit their utility for large-scale, high-throughput screening purposes, posing a bottleneck for early-phase toxicity testing and drug discovery efforts where speed and scalability are critical.

Mouse organoids have emerged as a complementary model to human organoids (Marshall and Mason, 2019). Stem cell-derived mouse organoids are valuable for optimizing protocols to generate brain region-specific structures. Extensive in vivo data on mouse brain development, together with detailed analyses of genetic mutants, provide critical benchmarks for validating organoids as tools to study the genetics of neural development (Lloyd-Davies Sánchez et al., 2024). Moreover, they offer a practical means to reduce, or potentially replace, the use of animals in research on normal brain development. However, mouse brain organoids are costly and relatively slow (several weeks) to generate. In addition, they lack full tissue maturity and are not well-suited to high-throughput studies (Medina-Cano et al., 2025). As a result, their utility for disease modeling still largely remains experimental (Marshall and Mason, 2019).

Zebrafish are already well established in toxicology research (Bambino and Chu, 2017; Guo, 2009; Hoffmann et al., 2021; MacRae and Peterson, 2015; Nishimura et al., 2016; Rosa et al., 2022; Sipes et al., 2011; Zhao et al., 2024) due to their rapid development, optical transparency during embryogenesis, and genetic tractability (He et al., 2006; Howe et al., 2013; Kily et al., 2008; Kimmel et al., 1995; Mueller and Wullimann, 2003). They not only facilitate the early identification of neurotoxicity before advancing compounds to more costly stages of drug development, but also enhance the ethically favorable, biologically relevant, cost-effective, and scalable assessment of potential environmental neurotoxicants, such as industrial chemicals. This dual utility aligns closely with the One Health framework (FAO, UNEP, WHO, and WOAH, 2022), which emphasizes the interconnectedness of human, animal, and environmental health, supporting a more holistic strategy for safeguarding health across species and ecosystems. Importantly, essential features of vertebrate brain organization are preserved, and zebrafish share many conserved pathways of neurodevelopment, neurotransmission, and toxicity responses with humans (Guo, 2009). This species is now considered a powerful complementary model in neuroscience (Guo, 2009), offering valuable insights into brain development, neural circuitry, and neurological diseases such as epilepsy (De Meulemeester et al., 2024; Kalueff et al., 2014), and serving as a powerful tool in drug discovery and development initiatives (Sourbron et al., 2017; Thevissen et al., 2025; Baraban et al., 2013). Building on this foundation, recent advances in stem cell and developmental biology enabled the generation of zebrafish brain organoids (Zilova et al., 2021), offering a novel in vitro platform that combines organoid technology with the practical advantages of the zebrafish model. Zebrafish brain organoids develop significantly faster than their human and mouse counterparts and can be produced at a large scale using relatively simple protocols. While they cannot fully replicate human brain complexity (Mueller and Wullimann, 2003; Mueller and Wullimann, 2009), their potential as a faster and more scalable system for high-throughput screening could become strategically important and advantageous as a relevant intermediate model, especially when used in combination with human-derived systems for validation.

This review maps the evolving landscape of NAMs in neuroscience with a focus on organoid technology and zebrafish models. Their strengths and limitations for neurodevelopmental studies, disease modeling, and neurotoxicity screening are critically assessed and compared to in vivo vertebrate models. Moreover, future directions are proposed for integrating these complementary systems into robust, efficient, and ethically responsible pipelines for both early-phase toxicity testing and drug discovery and development.

The regulatory paradigm shift

In recent years, regulatory agencies worldwide such as the EMA, the European Chemicals Agency (ECHA), US-FDA and US Environmental Protection Agency (EPA) have gradually explored and promoted the paradigm shift toward using alternative methods for preclinical research to provide reliable and predictive data without animal studies (European Parliament and Council, 2009; European Parliament and Council, 2006; OECD, 2018; Avila et al., 2020). The development and implementation of NAMs gained momentum after the EU banned animal testing for cosmetics in 2013 (European Parliament and Council, 2009; Parish et al., 2020), especially for toxicological endpoints such as skin and eye irritation. Momentum further increased with the introduction of REACH, which created a strong demand for alternative methods to assess the safety of large numbers of chemicals (European Parliament and Council, 2006). These legislative milestones not only accelerated the development of NAMs but also challenged regulators to establish clear pathways for their acceptance and integration into risk assessment frameworks. As part of this effort, the Organisation for Economic Co-operation and Development (OECD) played a key role by developing and updating internationally recognized Test Guidelines that incorporate NAMs, helping to harmonize validation standards and facilitate regulatory acceptance across countries. Consequently, academia, industry and governmental institutions made international collaborative efforts to develop a wide variety of NAMs and to validate their reproducibility, accuracy and predictivity (Turner et al., 2023; Avila et al., 2020). Such initiatives include the EU Horizon Europe and Innovative Health (European Commission, 2021) and EU’s Next Generation Risk Assessment (NGRA) program (Pallocca et al., 2022). In addition, each year, the EU Reference Laboratory for alternatives to animal testing (EURL ECVAM) publishes an overview of the progress of research projects in the EU relating to NAM development (EURL ECVAM Status Report 2024) (Baccaro et al., 2025). Together, these changes represent a paradigm shift towards modern, animal-free testing strategies that address ethical concerns while maintaining high levels of human and environmental protection.

While the pharmaceutical industry traditionally relies on animal studies due to the complex systemic safety requirements, recent scientific and regulatory initiatives, such as the FDA’s Modernization Act 2.0 (2022) (US Congress, 2021-2022), Tox21 consortium (Kavlock et al., 2009), ToxCast program (Dix et al., 2007), and the Innovative Health Initiative (IHI) in Europe (Initiative IH, n.d.), are increasingly promoting the integration of NAMs into pharmaceutical research and development. Animal studies still remain a requirement before first-in-human trials because of perceived physiological similarities between species (e.g., rodents, dogs, non-human primates), and therefore, NAMs are not (yet) envisioned as a full replacement. Instead, they are increasingly used to support early-stage efficacy and safety assessment, helping to inform and refine subsequent animal studies (Turner et al., 2023). By generating robust in silico and in vitro data early in the pipeline, NAMs will help to identify and eliminate potentially ineffective or toxic compounds before they reach animal testing. Moreover, these approaches generate valuable mechanistic and dose–response data that help prioritize candidates, optimize study design and dose selection, and ensure that subsequent animal studies are more targeted, scientifically justified, and aligned with the 3Rs principle. Overall, continued investment in NAMs will further enhance their ability to predict human toxicity, ultimately strengthening the safety and translational relevance of preclinical testing.

Reflecting this shift, regulatory guidelines such as the EMA’s Guideline on “Strategies to identify and mitigate risks for first-in-human and early clinical trials with investigational medicinal products” (van Gerven and Bonelli, 2018; European Medicines Agency (EMA), 2017) and the ICH S6 guideline on “Nonclinical safety evaluation of biotechnology-derived pharmaceuticals” (European Medicines Agency (EMA), 2011), aim to reduce clinical failures and unnecessary animal studies. They assist in species selection for safety assessments during drug development and explicitly discourage toxicity studies in non-relevant animal species. Moreover, these guidelines recommend conducting additional nonclinical testing to obtain relevant data for risk assessment, and they encourage the use of in vitro methods based on human-derived material. In line with this, a report by the US National Academy of Sciences (National Academies of Sciences, Engineering, and Medicine, 2023) also highlights the limitations of animal models and emphasizes that NAMs can enhance the validity of safety assessments by complementing traditional approaches.

The current landscape of NAMs in neuroscience

The complexity of central nervous system (CNS) disorders is a key contributor to the higher failure rates of drugs targeting neurological disorders when compared to other areas of drug discovery (Gribkoff and Kaczmarek, 2017). Hence, the need for models that can capture the disease processes and the added challenge within the neuroscience field to fully replace animal testing (i.e., whole organisms) by more simple non-animal models. However, challenges in translatability arise from the unique complexity of the human brain, with species-specific features in its structure, function, and development (Sousa et al., 2017; Onishi and Shimogori, 2025). One major hurdle is the inaccessibility of human brain tissue for research. The long, complex process of human brain development and the higher-order brain processes (e.g., cognitive functions) (Kelley and Pasca, 2022) involved in complex brain disorders such as Alzheimer’s disease, Parkinson’s disease and epilepsy, are challenging to fully replicate in traditional animal models. In addition, significant differences between human and animal CNS biology such as neurotransmitter systems (Fitzgerald, 2009; Beed et al., 2020), blood–brain barrier (BBB) permeability (Hoshi et al., 2013; Uchida et al., 2013; Syvanen et al., 2009) and gene expression patterns in neurons and glial cells, can result in poor translation of efficacy and safety data from animals to humans. One example is the relatively higher proportion of cortical GABAergic interneurons compared to glutamatergic neurons in humans, in contrast to the ratios observed in non-human primates and rodents (Bakken et al., 2021; Krienen et al., 2020). Consequently, the predictive value of animal models remains imperfect, contributing to high clinical attrition rates (Sun et al., 2022).

Recent technological evolution in NAMs addresses some of these limitations through the integration of advanced in silico, in vitro and in vivo systems. A diverse range of NAMs are being explored to complement traditional animal studies to study specific human-relevant mechanisms, improve the prediction of neurotoxicity for human and environmental health (Cao, 2022; Fitzgerald et al., 2021), and support early-stage drug discovery and development (Robertson et al., 2025; Mehta et al., 2025). The following sections provide an overview (Figure 1) of these advancements and their potential to support more reliable, human-relevant, and ethically responsible neuroscience. Nevertheless, NAMs come with their own limitations, including the lack of complexity compared to whole organisms. Hence, they are not (yet) envisioned as a full substitute for established in vivo models. Instead, they serve as complementary tools that, when used together with animal studies, and in partial replacement thereof, strengthen the overall predictive power and human relevance of neuroscience research.

Figure 1

Figure 1. Overview of state-of-the-art preclinical models used in neuroscience. Representation of how each model, from simple 2D in vitro systems to complex in vivo xenograft models and non-human primates, differs in level of physiological relevance to human brain function, biological complexity, face validity and the extent of ethical justifiable use. High face validity includes the ability to display behavior (locomotion, sleep, tremor, seizures, etc.) and other clinically relevant observations such as cognition (memory impairment, executive dysfunction, etc.). The suitability as a new approach methodology (NAM), experimental throughput, cost-effectiveness, and time efficiency are indicated using circles: filled circle, high; semi-filled, intermediate; open circle, low. *Zebrafish embryos and larvae <120 h post-fertilization (hpf) are legally not considered laboratory animals. Figure created with Biorender.com.

Human in vitro approaches for brain research

In recent years, significant advancements have been made in developing in vitro cell models for brain research (Peng et al., 2021; Dabhekar et al., 2024). These models have become invaluable tools for investigating brain biology and pathology, substantially advancing our understanding of the brain’s complexity.

2D cultures of immortalized and primary cells

Immortalized neuronal cell lines, such as the widely used human neuroblastoma SH-SY5Y cells (Encinas et al., 2000), are commonly used due to their human origin, ease of culture, ability and reproducibility to differentiate into neuron-like cells, genetic manipulability, and suitability for high-throughput screening. While they exhibit neuronal properties and express key neuronal markers (Sahin et al., 2021), they are tumor-derived and do not fully replicate the complexity or maturity of primary neurons. The latter are derived directly from brain tissue, have a limited lifespan but offer greater physiological relevance at the cellular level (Murphy-Royal et al., 2020). Cell-based transfection of DNA or RNA of interest is often performed to manipulate gene expression and to cost-effectively assess the biological and functional consequences. To more accurately mimic the intricate cellular environment of the brain, co-culture systems, combining neurons with glial cells (e.g., astrocytes, microglia, and oligodendrocytes) and/or endothelial cells (Sivandzade and Cucullo, 2018; Cucullo et al., 2011), can be used. These co-cultures enable researchers to study essential processes such as glial support for neuronal survival, synaptic regulation, and neuroinflammation. Incorporating endothelial cells provides a platform to model the complex BBB, facilitating research on neurovascular interactions and the delivery of therapeutics to the brain (Helms et al., 2016). Even though these 2D models are rather simplistic and do not fully capture the complexity of the human brain, they are invaluable tools for fundamental research (e.g., providing initial insights into cellular mechanisms) and high-throughput drug screening, including small molecules, RNAi therapeutics, and gene therapy candidates.

2D iPSC-derived neural cultures

In the past two decades, advances in stem cell technology have enabled the development of more sophisticated in vitro models that better mimic human (patho)physiology. Human induced pluripotent stem cells (iPSCs), reprogrammed from adult somatic cells like skin-derived fibroblasts or blood mononuclear cells, possess the capacity to differentiate into all cell types found within the three germ layers (ectoderm, endoderm, and mesoderm), including various neuronal and glial cell types, similar to embryonic stem cells (Kim et al., 2011; Takahashi et al., 2007; Yu et al., 2007; Lowry et al., 2008). A wide range of differentiation protocols are established, typically involving the exposure of iPSCs to neural patterning cues and developmental signaling molecules, resulting in the reliable generation of diverse cell types such as motor neurons (Boulting et al., 2011; Dimos et al., 2008), dopaminergic neurons (Kriks et al., 2011), GABA- and glutamatergic neurons (Doorn et al., 2023; Frega et al., 2017; Mossink et al., 2022; van Hugte et al., 2023), as well as astrocytes (Krencik et al., 2011; Roybon et al., 2013). iPSC technology thereby provides an unlimited source of patient-specific cells for studying neurological disorders and disease modeling, offering particular value for diseases like epilepsy and Parkinson’s disease, characterized by significant genetic heterogeneity (Simkin et al., 2022; Klein and Westenberger, 2012). Moreover, the development of CRISPR/Cas9 technology made it possible to create isogenic iPSC lines that are identical to the original parental lines except for the specific edited sites (Seeger et al., 2017). This allows for clear genotype–phenotype correlations without confounding effects from the surrounding genetic background. Nevertheless, 2D iPSC-based disease models also have important limitations. They do not fully recapitulate the complexity of the human brain, including interactions with other organ systems, the immune system, and the surrounding microenvironment (Gattazzo et al., 2014). Additionally, variability between iPSC lines and differences in differentiation protocols across laboratories impact reproducibility and consistency, highlighting the need for standardized protocols and rigorous quality control (Volpato and Webber, 2020). Another key limitation is that iPSC-derived neurons often remain in an immature state, reducing their relevance for studying adult-onset or late-stage neurological diseases (Centeno et al., 2018). The slow maturation of neuronal cultures, on the other hand, mirrors the prolonged development of the human brain, enabling researchers to study the origins and progression of developmental diseases over time. Moreover, while iPSCs bypass many of the embryo-related ethical issues associated with ESCs, ethical challenges remain, particularly regarding donor consent, privacy, and genetic manipulation, as iPSCs retain the donor’s full genetic information (Velasco et al., 2019). Despite lacking the cellular heterogeneity, tissue architecture, and microenvironmental cues of the complex human brain, patient-specific iPSC-derived disease models serve as powerful platforms for pathomechanistic research, drug screening and personalized medicine, helping to develop tailored therapeutic strategies based on individual patient profiles (Miccoli et al., 2018).

3D brain organoids

3D organoid technology bridges this gap and creates more physiologically relevant and predictive systems. Brain organoids are miniature 3D structures that arise from the self-organization, self-renewal, and differentiation of pluripotent stem cells (Lancaster et al., 2013; Bartfeld and Clevers, 2017; Fatehullah et al., 2016). They mimic key features of the developing human brain, including region-specific organization, interactions between multiple neural cell types, and the emergence of all necessary cell types for neuronal activity (Kim et al., 2020). These cells follow a human-like developmental timeline with gene expression patterns resembling those of the immature cortex (Camp et al., 2015; Pollen et al., 2014). Electrical activity of a single neuron can be measured using whole-cell patch clamp technology (Landry et al., 2023), while multielectrode arrays or calcium imaging detect activity across multiple neurons in the network simultaneously (Oliva et al., 2024). As such, brain organoids provide a promising platform for studying human brain development (e.g., neurogenesis, neuronal migration, synaptogenesis, and the creation of various brain areas), neurological disease modeling, and enhancing the predictive power of neurotoxicity testing (Bremond Martin et al., 2021; Gerakis and Hetz, 2019; Bagley et al., 2017; Trujillo and Muotri, 2018; Nzou et al., 2018). Among others, reviews by Cao (2022), Fan et al. (2022), and Lei et al. (2024), provide a comprehensive overview of the use of 3D human brain organoids in neurotoxicity evaluation. These studies show that organoid models effectively mimic human brain development and offer a valuable platform for assessing the effects of various neurotoxicants, including environmental toxins, drugs, and chemicals, on neural cells and circuits.

Despite their immense potential, human brain organoids face significant limitations that hinder their utility and ability to fully replicate the complexity of the human brain. Culturing brain organoids is time-consuming as it mirrors the natural pace of human brain development, requiring multiple differentiation stages, maturation of various cell types, and long-term growth to achieve meaningful structural and functional complexity (Qian et al., 2019). This lengthy process limits the efficiency and throughput of brain organoid production. Moreover, brain organoid protocols are often complex and lack standardization, which contributes to significant batch-to-batch variability (Maisumu et al., 2025). The sophisticated procedures also require skilled and experienced researchers to achieve consistent results, further limiting reproducibility across different labs. Additionally, generating and maintaining organoids requires expensive growth factors, specialized culture media, and advanced laboratory equipment, posing a financial barrier. These challenges collectively hinder scalability and the reliable application of brain organoids in neuroscience. Another important limitation is that human brain organoids, like other in vitro models, have a low face validity as they cannot model behavioral phenotypes and symptoms. For example, although organoids display seizure-like electrical activity and upregulation of molecular markers relevant to epilepsy (Samarasinghe et al., 2021) or dopaminergic neuron loss seen in Parkinson’s disease (Cui et al., 2024), they cannot replicate the motor symptoms, such as seizures or tremors, observed in patients. The same limitations apply to comorbidities such as sleep disturbances, psychological problems (e.g., depression, anxiety, and aggression), autism spectrum disorder (ASD), impaired cognition, and others.

Nevertheless, the incorporation of these more sophisticated and physiologically relevant in vitro models is transforming biomedical research and safety assessment in neuroscience. By improving the prediction of human responses, these models help advance health outcomes (Langhans, 2018) while simultaneously reducing the need for animal testing, in alignment with the 3Rs principle (Csukovich et al., 2022; Csukovich et al., 2022). Although the resource- and time-intensive nature of 3D brain organoids makes them low-throughput and less suitable for primary drug screening, they already complement animal studies in preclinical neuroscience research and drug development in the pharmaceutical sector, as evidenced by numerous recent reports (Matsui and Shinozawa, 2021; Beilmann et al., 2025; Beilmann et al., 2019; Pognan et al., 2023; Mina et al., 2019; Wang et al., 2022; Gjorevski et al., 2020). Their ability to detect neurotoxic or adverse effects at early stages facilitates earlier decision-making in drug pipelines, helping to avoid late-stage failures, reduce development costs, and minimize the use of both human and animal resources. This shift is further supported by international frameworks like the OECD’s Guidance Document on “Good In Vitro Method Practices (GIVIMP)” (OECD, 2018) and expert recommendations like those of Bal-Price et al. on “in vitro test readiness for developmental neurotoxicity” (Bal-Price et al., 2018), highlighting the global commitment to improve in vitro approaches for brain research and safety assessment. Notably, single in vitro tests are insufficient to fully capture the complexity of biological systems or to entirely replace animal experiments. More reliable and comprehensive data are generated by combining them with other NAMs. These combinatorial approaches, integrating in silico, in chemico, in vitro, and non-animal in vivo methods, are supported by the OECD’s framework of Integrated Approaches to Testing and Assessment (IATA) offering a more holistic and flexible strategy for safety assessment, leading to more robust and human-relevant risk evaluations (OECD, 2022; Sakuratani et al., 2018).

Microfluidic brain-on-a-chip platforms

A well-documented consequence of the prolonged brain organoid culture process is cell death in the organoid core, due to insufficient oxygen and nutrient diffusion (Lancaster et al., 2013; Cakir et al., 2019). To address this, dynamic culturing methods such as orbital shakers and spinning bioreactors have been introduced. The integration of organoids into microfluidic systems further enhances their physiological relevance by creating dynamic, controllable environments (Kim et al., 2020; Chauhdari et al., 2025; Cho et al., 2021). These advanced brain-on-a-chip platforms improve oxygen and nutrient delivery, facilitate waste removal, and simulate extracellular fluid flow by linking neuronal compartments through microfluidic channels. This setup more accurately mimics in vivo conditions and allows for the incorporation of vascular structures. As a result, in vitro models of the BBB are developed, enabling more sophisticated studies of neurovascular interactions, drug transport, and BBB function (Lei et al., 2024; Bergmann et al., 2018; Kawakita et al., 2022; Bell et al., 2025; Shi et al., 2020). However, the need for advanced microfluidic approaches adds to the already labor-intensive nature of the use of brain organoids, in contrast to traditional animal models, which naturally provide the full systemic complexity of a whole organism. Additionally, the spontaneous emergence of glial cells, such as astrocytes and oligodendrocytes, occurs only at later stages of organoid development (Sloan et al., 2017; Verkerke et al., 2024; Pasca et al., 2015). This delay, which reflects the natural progression from neurogenesis to gliogenesis during human embryogenesis, further prolongs the culturing timeline. Consequently, the ability to study more mature brain features and early neuron–glia interactions is limited, especially for drug discovery purposes that rely on high-throughput capacities. Nevertheless, significant research continues to focus on improving both brain organoid and brain-on-a-chip technologies, aiming to balance physiological relevance with practical scalability to make them viable for applications such as drug screening, disease modeling, and personalized medicine.

Human neuron xenograft models

Transplantation of human neurons and brain organoids into animal brains, typically immunodeficient rodents, is a recent exploratory technique aimed at addressing the limitations of in vitro 2D neuronal and 3D organoid models by providing a more physiologically relevant in vivo context (Mansour et al., 2018; Revah et al., 2022; Xiang et al., 2017; Wilson et al., 2022; Mancuso et al., 2024; Linaro et al., 2019). Implanted neurons can integrate with the host’s vascular system, form synaptic connections with host neurons, and respond to sensory stimuli, enabling more dynamic modeling of human brain development and function. Furthermore, transplantation models overcome the fact that the gene expression profiles in 2D and 3D iPSC-derived brain cultures are altered by artificial in vitro conditions and remain relatively immature, thus not fully reflecting in vivo brain tissue. In a recent study by Revah et al. (2022), 3D human cortical brain organoids derived from hiPSCs were transplanted into the primary somatosensory cortex of immunodeficient newborn rats, demonstrating that the in vivo environment is beneficial for advanced neuronal maturation compared to neurons kept in vitro. Neurons from transplanted organoids formed functional synaptic connections with rat thalamic and cortical circuits, responded to sensory input, and extended axonal projections into the rat brain that influenced rat behavior. Clear differences in neuronal morphology and electrical activity were observed for transplanted organoids derived from patients with Timothy syndrome, a rare genetic disorder linked to autism and epilepsy, compared to isogenic controls, underscoring that this approach is promising for disease modeling.

In addition to the challenges of slow development, high variability, low throughput, and limited network maturation, human brain organoids recently also raise ethical concerns (Kataoka et al., 2025). As these models become increasingly complex, exhibiting features such as spontaneous electrical activity and primitive sensory structures, questions are raised about their potential for consciousness or sentience. While current human brain organoids remain far from achieving such capabilities, these concerns highlight the need for ongoing ethical oversight and clear guidelines as the field advances.

Mouse brain organoids

The application of human brain organoids is constrained by high cost, lengthy differentiation times, and substantial variability between batches. Mouse brain organoids (Lloyd-Davies Sánchez et al., 2024), derived from either mouse ESCs or iPSCs, address these limitations and leverage the extensive knowledge derived from the most widely used mammalian in vivo model in neuroscience. The extensive molecular (Langlieb et al., 2023), physiological (Demin et al., 2021), and developmental data from the mouse brain provide a valuable reference framework for benchmarking and validating these emerging in vitro systems. Such data help identifying potential artefacts and remaining biological limitations when comparing organoid models to the in vivo biology they aim to represent. Moreover, the generation of mouse organoids, in combination with human brain organoids, offers a platform that can help bridge findings between traditional in vivo studies and human clinical trials, improving translational reliability. Several established protocols to generate mouse brain organoids already exist, including cerebellar (Guglielmi et al., 2024), hippocampus (Ciarpella et al., 2023) and forebrain models (Medina-Cano et al., 2022), recapitulating aspects of cortical layering, synapse formation, and neuronal activity in vitro.

While mouse brain organoids offer strategic advantages, their use is not without challenges. The generation process remains relatively long (several weeks) and costly, and these models still lack the full structural and functional complexity of the intact brain, such as vascularization, long-range connectivity, and full neuronal maturation (Medina-Cano et al., 2025). Moreover, because mouse organoids model murine rather than human neurobiology, their relevance to human biology is limited, which significantly constrains the interpretation and extrapolation of disease mechanisms compared with human-derived in vitro models. While mouse organoids are valuable for studying fundamental aspects of neural development, regional specification, and circuit formation, their ability to recapitulate disease-specific phenotypes such as neurodegeneration, synaptic dysfunction, or network hyperexcitability remains limited. The gap underscores the need for genetically tractable, reproducible mouse organoid systems that more accurately reflect pathological processes. Thus, although they provide a valuable mammalian system to refine and complement existing models, further methodological optimization and validation are required before they can fully capture the complexities of neural development and disease (Marshall and Mason, 2019).

Zebrafish model

Zebrafish (Danio rerio) are a non-mammalian vertebrate species with several unique advantages that make them particularly well-suited as in vivo NAMs when used at embryonic and early larval stages (Figure 2). Zebrafish embryos are not legally classified as protected animals until 120 h post-fertilization (hpf) when they are independently-feeding, aligning their use with international regulatory and ethical considerations, such as the EU Directive 2010/63/EU on the protection of animals used for scientific purposes (EU, 2010). This makes them a refined alternative that significantly reduces the need for higher-order vertebrates while maintaining biological relevance and in vivo complexity. This aspect makes zebrafish a non-animal in vivo model during early development that is particularly attractive for early-stage research and drug discovery and development, especially in toxicological assessments and pharmacological studies where large-scale screening is essential. As such, zebrafish bridge the gap between traditional in vitro assays and mammalian in vivo models, effectively fulfilling the 3Rs principles (Strahle et al., 2012; Cassar et al., 2020).

Figure 2

Figure 2. Advantages and relevance of zebrafish as a vertebrate model in neuroscience research. Zebrafish offer high level of conservation with regards to the human reference genome, conserved brain structure and neurotransmitter systems, ease of genome editing, rapid reproduction, short generation time, and cost-effectiveness, making them ideal for neurodevelopment and toxicity studies, functional genomics, disease modeling, and drug discovery. Figure created with Biorender.com.

Zebrafish have a high level of conservation with regards to the human reference genome, with approximately 70% of human genes having at least one zebrafish ortholog, and up to 84% of genes known to be associated with human disease having a zebrafish counterpart (Howe et al., 2013). Despite being small and evolutionarily distant, zebrafish exhibit remarkable conservation in vertebrate brain regions, gene expression patterns (Mueller and Wullimann, 2009) and neurotransmitter systems (Guo, 2009), making them a valuable model for studying the CNS, neurological diseases, and drug effects. However, they lack the highly complex cortical architecture seen in humans and other mammals, not possessing layers and gyri (Mueller and Wullimann, 2003). Importantly, zebrafish embryos are transparent and develop rapidly ex utero, allowing real-time observation of (neuro)developmental processes and organ formation within just a few days post-fertilization. Moreover, embryos and larvae can be arrayed in microtiter plates (body length ≤4.5 mm). This makes them ideal for high-throughput screening in drug discovery and toxicology, where hundreds of compounds are tested quickly and cost-effectively in multi-well plate formats. Their susceptibility to genetic manipulation (e.g., CRISPR/Cas9) further enhances their utility in modeling human diseases and understanding gene function (Chang et al., 2013; Hwang et al., 2013).

Thanks to these strengths, zebrafish are well-accepted as a reliable, rapid, inexpensive, and medium- to high-throughput in vivo model in toxicological studies (Rosa et al., 2022; Zhao et al., 2024; Bult and Sternberg, 2023; Yamamoto et al., 2024), drug discovery screening, and (patho)mechanistic investigations (Bambino and Chu, 2017; Shao et al., 2024; Tang et al., 2023). For example, the Zebrafish Embryotoxicity Test (ZET) is a widely used in vivo assay for evaluating the developmental toxicity and teratogenicity of chemicals (Achenbach et al., 2020; Brannen et al., 2010; Gustafson et al., 2012). It can detect effects of known human teratogens such as thalidomide and valproic acid (Hoffmann et al., 2021), by monitoring morphological changes during early embryonic development. The ZET is included in integrated testing strategies (ITS) for developmental and reproductive toxicity (DART) testing (Burbank et al., 2023), alongside in silico models from the OECD QSAR (Quantitative Structure–Activity Relationships) Toolbox (Lavado et al., 2020; Lovric et al., 2021; Saavedra and Duchowicz, 2021) and in vitro assays like the human iPSC-based devTox assay (Zurlinden et al., 2020), to support comprehensive chemical risk assessment. Zebrafish are also valuable in predicting human developmental toxicity (Boyd et al., 2016; Padilla et al., 2012), as evidenced by data from the US Environmental Protection Agency (EPA) “ToxCast” program (launched in 2007) (Dix et al., 2007), and comparative studies further state that zebrafish can serve as alternatives to traditional mammalian models for developmental toxicology (Nishimura et al., 2016; Kily et al., 2008; Wester et al., 2004). In the field of neurotoxicity, zebrafish are widely used to detect toxicant-induced functional changes in the nervous systems, including behavioral alterations (e.g., changes in locomotor activity) and electrophysiological disturbances (e.g., seizure-like discharges) (Fitzgerald et al., 2021; Tomasello and Wlodkowic, 2022; Forner-Piquer et al., 2021; Chai et al., 2024). Moreover, zebrafish are a state-of-the-art model for studying neurological disorders such as Alzheimer’s disease, Parkinson’s disease and epilepsy. Standard read-outs include molecular, behavioral and electrophysiological measurements. Both chemically-induced and genetic zebrafish models significantly contributed to the discovery of therapeutic compounds for neurological conditions. A notable example is the zebrafish model of Dravet syndrome (Griffin et al., 2021), a severe drug-resistant childhood epilepsy caused by mutations in the SCN1A gene. This model has been instrumental in identifying repurposed drug candidates such as clemizole (Baraban et al., 2013) using high-throughput screening and in gaining mechanistic insights in fenfluramine (Sourbron et al., 2017), a recently approved therapeutic agent. In addition, the zebrafish ethyl ketopentenoate (EKP) model of drug-resistant seizures was used for identifying clioquinol as a repurposed drug candidate, which is now in clinical trials for a new disease indication (Thevissen et al., 2025). Beyond drug discovery, zebrafish disease models are invaluable for (patho)mechanistic research, offering insight into pathological processes that in turn can result in the discovery of novel drug targets and the development of innovative therapies. For example, a study in a zebrafish model of DS revealed novel early mechanisms of disease pathogenesis, describing dynamic changes in neuronal and glial cell populations during epileptogenesis, and provided first-time evidence for potential disease modification by fenfluramine (Tiraboschi et al., 2020). Moreover, in zebrafish models of Alzheimer’s disease, a pathological loop linking oxidative stress, neuroinflammation, and gut microbiota dysbiosis along the gut-brain axis has been demonstrated (Qu et al., 2023; He et al., 2024). Finally, zebrafish are invaluable for functional genomics, providing a versatile in vivo system to investigate how genes and genetic variants contribute to biological processes and human disease (Howe et al., 2013; Dore et al., 2025; Patton et al., 2021). Many genetic mutant lines and morphant models have been generated, enabling, among others, the efficient validation of candidate disease genes identified by human GWAS or sequencing studies, as well as the investigation of how genetic mutations affect behavior and neurobiology. This is illustrated by recent reports employing high-throughput generation and characterization of genetic mutants, demonstrating the capacity of zebrafish for rapid disease modeling across conditions ranging from epilepsy (Griffin et al., 2021) to other complex neurological traits (Kroll et al., 2021).

Zebrafish brain organoids

Traditional human brain organoids mimic key features of the developing human brain and model neurological diseases, but they are limited by high cost, long culture times, variability and lack of direct comparison to an in vivo reference. Mouse organoids offer a faster, more cost-effective, and ethically simpler model than human organoids and mice themselves (Marshall and Mason, 2019) and are used mainly for developmental research. Although they show potential for disease modeling and drug testing, these applications remain largely experimental (Marshall and Mason, 2019). They also remain relatively costly, slow to develop, and less amenable to high-throughput studies. In contrast, zebrafish embryos develop rapidly, are cost-effective and are highly accessible for in vivo studies, but after 120 hpf they are considered animal models, which introduces regulatory and ethical constraints. Noteworthy, brain structures such as the BBB are still developing beyond this stage (Kimmel et al., 1995), which can necessitate the use of older larvae and hence animal studies. To bridge these gaps, zebrafish brain organoids provide a pioneering complementary model that combines the strengths of in vitro organoid technology with those of the zebrafish, including rapid development, offering a novel and high-throughput platform for drug discovery and development and for studying neural development and neurotoxicity in a controlled yet physiologically relevant and ethically favorable context.

2D cultures of primary fish-derived embryonic stem cells

In the last decades, several studies (Ho et al., 2014; Hong et al., 1996; Robles et al., 2011; Yi et al., 2010) reported attempts to culture embryonic stem (ES)-like cells from fish blastula-derived cells, but protocols vary between laboratories and maintaining true ES cell cultures from zebrafish is technically demanding (He et al., 2006; Collodi et al., 1992; Ma et al., 2001; Xing et al., 2008; Driever and Rangini, 1993). Additionally, gene-targeting approaches have been applied in these species to facilitate the development and characterization of such ES-like cell lines (Hong et al., 1996). The established ES-like cell lines from zebrafish support the notion that pluripotency is conserved among vertebrates (Collodi et al., 1992; Sun et al., 1995), but cultures show heterogeneity, and spontaneous differentiation is a challenge and contributes to the limited number of stem cell lines available (Goswami et al., 2022). Their ability to differentiate and self-organize into polarized aggregates have been demonstrated by specifying all three germ layers (i.e., ectoderm, mesoderm, and endoderm) (Fulton et al., 2020; Schauer et al., 2020), thereby recapitulating key aspects of early embryonic patterning and morphogenesis. These structures exhibit a strong resemblance to mammalian ES cell-derived gastruloids (Beccari et al., 2018; van den Brink and van Oudenaarden, 2021; Moris et al., 2020; Turner et al., 2017). Moreover, zebrafish primary ES cells have already been differentiated into functional cardiomyocytes exhibiting contractile kinetics and electrophysiological features (Xiao et al., 2016). Several studies demonstrated that ES cells derived from zebrafish can differentiate into both neurons and astrocytes in vitro (Ghosh et al., 1997), and primary cultures of zebrafish neural cells have been established (Patel et al., 2019). However, they typically have low survival rates in vitro, which poses challenges for long-term culture and functional studies.

3D fish brain organoids

Reports of zebrafish-derived tissue or dissociated cells forming complex, organized neural structures similar to those seen in mammals are limited. Consequently, and due to the interest in human models, the organoid field largely remained restricted to mammalian species (i.e., rodents and humans). However, Zilova et al. (2021) demonstrated the successful derivation of brain organoids from rapidly developing teleosts (i.e., zebrafish and medaka), marking an important advance in this area. This study shows that primary embryonic pluripotent cells derived from blastula-stage embryos of medaka and zebrafish can form neuroepithelial aggregates that develop into anterior neuronal organoids expressing the general neuronal marker Sox2 (Pevny and Placzek, 2005; Wegner and Stolt, 2005) and the forebrain marker Otx2 (Acampora et al., 1995; Simeone et al., 1993; Tian et al., 2002). Furthermore, expression of HuC/D, a marker of early post-mitotic neurons (Good, 1995; Kim et al., 1996; Park et al., 2000), indicates that the fish organoids show onset of neuronal differentiation. Remarkably, within just four days, these fish-derived cells undergo efficient brain differentiation and morphogenesis in culture demonstrating that brain region formation in these organoids mimics the in vivo cell migration patterns.

We reproduced their published protocol, with minor modifications (Figure 3A), confirming its reproducibility and the feasibility to generate comparable neuroepithelial structures. Our observations confirm that primary zebrafish-derived pluripotent ES cells form neuroepithelial aggregates and reproducibly differentiate into brain structures within just a few days (Figures 3B,C). Notably, while zebrafish can produce several hundred embryos per spawning (i.e., 100–300 viable embryos under optimal conditions), the manual dissection and isolation of ESCs from each embryo is labor-intensive and time-consuming. Thus, large-scale production of zebrafish organoids currently demands significant time and labor input. The fish-derived organoids are generated from aggregates of fewer than 1,000 embryonic stem cells, which is roughly half the number of cells in a single blastula-stage embryo (Kimmel et al., 1995). This means that up to three organoids can be produced from just one embryo, reducing the total number of embryos needed and supporting the 3Rs principle in animal research. Re-aggregation of dissociated primary pluripotent cells from blastula-stage zebrafish embryos is rapid (approximately 2–3 h) and highly efficient (~100%), resulting in a smooth and compacted morphology of aggregates by day 1. From day 2 onward, cells in the peripheral layer expressed neuroepithelial markers such as N-cadherin, confirming the acquisition of neuroepithelial identity. The aggregates also expressed the general neuronal marker Sox2 and the forebrain marker Otx2, indicating that the tissue adopted an anterior neuronal fate. This differentiation protocol leverages the assembly of cells into various organ-like structures, highlighting how in vitro systems provide a unique opportunity to study the fundamental principles of organ formation.

Figure 3

Figure 3. Generation of zebrafish primary pluripotent cell-derived aggregates. (A) Schematic representation of aggregate generation, its timeline and culture conditions. The protocol for blastula-stage zebrafish embryo dissociation and 3D aggregate culture was reproduced from Zilova et al. (2021) with minor modifications. The aggregates were incubated at 26 °C in the incubator without CO₂ control and Matrigel was added at 2 h post-aggregation (hpa) to a final concentration of 2%. From day 1 onward, aggregates were incubated at 26 °C and because CO₂ control was not possible, media was supplemented with 20 mM HEPES, pH = 7.4. At day 2, the aggregates were transferred to a low binding culture plate and maintained in 3D suspension culture conditions. The gross morphology of the aggregates was analyzed at days 1 and 2. KSR, knockout serum replacement; FBS, fetal bovine serum; FEE, fish embryonic extract. (B) Dark-field images of a blastula-stage embryo, a blastula-derived intact inner cell mass after cutting, blastula-derived cell suspension, re-aggregated cells and the gross morphology of aggregates at days 1 and 2 after re-aggregation. (C) Optical sectioning showing aggregate organization at day 2 visualized by immunostaining against the neuroepithelium-specific marker N-cadherin (N-cad), forebrain anterior neuronal marker Otx2, marker of early post-mitotic neurons HuC/D, general neuronal marker Sox2, and co-stained with DAPI nuclear stain. Whole-mount staining was performed as described by Zilova et al. (2021) using the same antibodies. Scale bars: 100 μm. Fixed organoid samples were imaged with Leica Sp8 confocal microscope. Gross morphology of organoids was assessed by the EVOS Floid imaging system.

Moreover, Zilova and colleagues showed that genetic factors critically influence morphological changes that mirror the in vivo situation. The high efficiency and rapid development of fish-derived organoids, combined with advanced genome editing (CRISPR/Cas9), enabled them to examine the coordinated expression of key eye field transcription factors, such as Rx3 (Chuang et al., 1999; Loosli et al., 2003), in the anterior neural plate. Their data show that fish-derived organoids form retinal neuroepithelium with multiple optic vesicles under the control of Rx3, with the onset of retinal fate being genetically timed and strictly dependent on expression of this transcription factor. Intriguingly, in a fraction of organoids, retinal and non-retinal domains showed an arrangement, resembling a simple “head with two eyes.” This demonstrates that key aspects of organogenesis, early eye development in this case, are faithfully recapitulated in vitro in a dish maintaining the same genetic and developmental programs compared to the embryo. Moreover, compared to their human and murine counterparts, zebrafish organoids develop much faster, progressing about ten times faster than murine models (Kuwahara et al., 2015; Nakano et al., 2012; Eiraku and Sasai, 2011) and closely following the in vivo developmental timeline, which reflects the species-specific differences in developmental speed.

Application potential

Compared to conventional in vivo mouse and zebrafish experiments, brain organoids offer a simplified, controllable platform that reduces ethical and logistical barriers while still capturing key aspects of vertebrate neurodevelopment. For human brain organoids, numerous standardized protocols are established, supporting a wide range of applications, including patient-specific disease modeling and neurotoxicity research. Mouse brain organoids similarly recapitulate many aspects of early neurodevelopment and have been successfully generated using several published protocols. However, their use is limited to fundamental neurodevelopmental investigations, with disease modeling applications being less established. The simple and reproducible methodology for generating zebrafish brain organoids makes this approach attractive to a wide range of research groups, both to those experienced in pluripotent stem cell culture, but lacking zebrafish expertise or aquatic facilities, and to labs working with fish models but with limited stem cell experience. By providing an accessible and consistent way to produce organized neural tissue in vitro, this protocol broadens the use of zebrafish as a model system beyond traditional whole-animal studies.

However, like all NAMs, brain organoids face practical and technical limitations (Figure 4). One of the major limitations of current brain organoids (human, mouse and fish) is that they lack vascularization leading to cell death and limited growth (Qian et al., 2019). Moreover, because stable ESC lines are not (yet) available for zebrafish, in contrast to mouse and human, organoid generation requires the use of zebrafish embryos, limiting yield to only a few organoids per embryo, restricting scalability and reproducibility of zebrafish brain organoids. While optimizing automation of blastula dissection and organoid aggregation could reduce variability and labor demands, establishing stable fish stem cell lines would be a pivotal step towards improving standardization. This would also support broader implementation across laboratories. Potentially, the number of organoids produced from just one embryo could be increased when the earlier stage totipotent blastomeres would be considered. Regardless, the availability of ES cells in culture would be most optimal. Mouse organoids (Hu et al., 2018; Lee et al., 2020; Taguchi and Nishinakamura, 2017), on the other hand, are generated from ESC or iPSC stable lines, eliminating the need to isolate ESCs from embryos for each differentiation. Therefore, they have no impact on the number of embryos used.

Figure 4

Figure 4. Comparative overview of key features, strengths, and limitations of selected New Approach Methodologies (NAMs) in neuroscience. Comparison of human, mouse and zebrafish brain organoids, and zebrafish models, illustrating differences in species relevance, systemic context, and time to produce. Differences in cost-effectiveness, throughput, genetic manipulability, technical ease of use and repeatability are indicated by circles: filled circle, high; semi-filled, intermediate; open circle, low. Ethical considerations, main limitations, and main applications are also listed. NA, not applicable; hpf, hours post-fertilization. Figure created with Biorender.com.

Although mice have a cerebral cortex, it is smaller and less complex than the human cortex. Organoids reproduce these species-specific differences with human organoids showing longer progenitor cycles and abundant outer radial glia (Li et al., 2017), while mouse organoids reflect the faster, simpler murine developmental program, making them valuable for studying brain development in vitro as mouse brain organoids are grown in a shorter time period than human ones (weeks versus months). Moreover, mouse brain organoids are widely used to compare phenotypes between in vitro mutant organoids and in vivo embryos (Lloyd-Davies Sánchez et al., 2024), generate region-specific organoids (Medina-Cano et al., 2025; Medina-Cano et al., 2022), and improve organoid models by developing and optimizing new technologies. The current fish organoid model develops even faster (days) and demonstrates the capacity of zebrafish pluripotent stem cells to self-organize into complex neural tissues. Although it is a limitation that cortical-like structures cannot be reproduced in zebrafish organoids due to the distinct forebrain architecture of zebrafish, the zebrafish pallium and subpallium are considered the functional and molecular analogs of the mammalian cortex and basal ganglia (Pang et al., 2025). Consequently, approaches could be optimized to generate organoids that model zebrafish-specific brain regions, such as the telencephalon, thereby capturing the diversity of neuronal and glial cell types and providing a faster platform to explore conserved principles of vertebrate forebrain development in a more simple model.

Furthermore, the differentiation protocol, initially designed to generate anterior neural and retinal fish organoids, holds great promise for studying a variety of other organs beyond the brain. Fish pluripotent stem cells have the capacity to differentiate into multiple tissue lineages, making them a versatile platform for modeling organ development in vitro. By adjusting culture conditions, signaling cues, and extracellular matrix components, this approach can be adapted to produce organoids representing kidney, heart, liver, gut, and other fish tissue, providing valuable insights into vertebrate organogenesis. This hence is expected to mirror the versatility observed in mouse organoid systems, where similar in vitro approaches have successfully produced kidney (Taguchi and Nishinakamura, 2017), liver (Hu et al., 2018), and heart organoids (Lee et al., 2020), highlighting the broader applicability of organoid technology for modeling diverse vertebrate tissues.

Beyond serving as a platform for in vitro organogenesis studies, as demonstrated by Zilova et al., the novel fish brain organoid model provides a scalable, cost-effective system for disease modeling, functional genomics, and high-throughput drug screening. For example, while studies have shown that human brain organoids combined with CRISPR/Cas9 gene editing (Chen et al., 2021) successfully model genetic epilepsies (De Meulemeester et al., 2024), revealing phenotypes such as neuronal hyperexcitability and disrupted network synchrony, this approach is associated with a high cost, technical complexity, and slow maturation. Zebrafish brain organoids could help address these constraints by offering a complementary model that bridges the gap between the rapid, whole-organism advantages of zebrafish larvae and organoid technology. Together, these complementary models cover a range of applications in neuroscience, including zebrafish brain organoids for scalable mechanistic and screening applications, mouse brain organoids for neurodevelopmental studies, human brain organoids for patient-specific disease modeling and translational relevance, and in vivo vertebrates animal models (zebrafish, mouse, etc.) for disease modeling and systemic, behavioral and neurotoxicity studies.

In recent years, numerous studies have been published using cerebral organoids, with the vast majority employing human PSCs. This predominance is due to the key strength of human brain organoids that they can be derived from patient-specific pluripotent stem cells, capturing an individual’s complete genetic background (Takahashi and Yamanaka, 2006). This is especially important for complex polygenic disorders, such as epilepsy, Alzheimer’s and Parkinson’s disease, where disease penetrance is highly influenced by an individual’s genetic background (Lancaster and Knoblich, 2014). The latter represents one of the main limitations of organoids derived from alternative organisms, such as fish and mice, which cannot fully capture human-specific genetic variability and disease mechanisms. However, by combining mouse and zebrafish brain organoids with advanced gene editing tools, researchers can perform targeted functional genomics studies to dissect genotype–phenotype relationships, identify novel genetic drivers of neurological disorders, and evaluate gene-targeted therapies prior to validation studies in human brain organoids. Many zebrafish models of genetic epilepsies already exist (Copmans et al., 2017), such as the larval zebrafish scn1lab^−/− mutant model of Dravet syndrome, and pluripotent cells derived from these embryos can be used to generate disease-specific brain organoids. These fish organoids would be particularly well suited for high-throughput drug screening, enabling fast and efficient assessment of drug efficacy and safety in a non-animal vertebrate context. Promising conditions identified in these screens, such as active compounds and safe concentrations, could then be tested in human brain organoids, providing a rapid pre-screening step before more resource-intensive human studies. Notably, because stable, long-term zebrafish ESC lines are not (yet) available, genome editing for zebrafish organoids must be carried out in embryos, necessitating embryonic screening, ESC isolation and subsequent organoid generation, which increases embryo use. In contrast, mouse ESCs and iPSCs are maintained as stable lines, allowing genome editing entirely in vitro, facilitating controlled studies of genetic variants in a mammalian context. While zebrafish organoids provide speed and high-throughput potential, mouse organoids provide a genetically tractable system with closer physiological relevance to humans, allowing a strategic combination of both platforms for preclinical research (Figure 4). Hence, complementing the insights gained from both whole-animal and human in vitro models.

In addition to disease modeling and drug discovery, mouse and zebrafish brain organoids also hold significant potential as an in vitro platform for neurotoxicity and ecotoxicity screening of pharmaceuticals, chemicals and environmental toxicants. Zebrafish already demonstrated strong relevance for studying ecological neurotoxicology, illustrating the interconnected pathways through which environmental pollutants impair brain health, including gut-brain axis dysregulation (Sun et al., 2025; Xu et al., 2025). In a recent study (Leekitratanapisan et al., 2025), zebrafish were used to reveal behavioral effects of complex wastewater micropollutant mixtures, further highlighting their value as a powerful vertebrate system for mechanistic and ecological assessments of environmental contaminants. These findings underscore the potential of zebrafish brain organoids as an innovative model to extend such investigations in vitro, enabling the study of neurotoxic mechanisms, dose–response relationships, and systemic neuroinflammatory pathways under controlled yet environmentally relevant exposure conditions. Notably, this emerging model aligns with the EU’s One Health approach by offering a safe, sustainable and animal-reducing alternative that addresses health risks at the human-animal-environment interface. To demonstrate their feasibility for safety and toxicity testing, however, it is crucial to systematically assess their morphological, transcriptional, and functional changes in response to test compounds. Such assessments should include for example the detection of dose-dependent toxicity, off-target effects, and developmental neurotoxicity, ensuring that these organoids show high predictive validity and reliably reflect the impact of toxic agents on brain structure and function, while providing an efficient complement to existing vertebrate and human-based NAMs.

Model validation

The importance of integrated, multi-level validation of newer organoid systems cannot be overstated to ensure their applicability. Both mouse and zebrafish brain organoids require morphological, functional, and molecular characterization, benchmarked against human brain organoids, whole mouse (brain), or whole zebrafish (brain), depending on the species. Such validation ensures that organoids are biologically faithful and translationally relevant by confirming that they accurately recapitulate in vivo neurodevelopmental processes and disease mechanisms. The characterization and demonstration of their construct (pathomechanisms), face (clinical symptoms) and predictive (treatment) validities will support their use in mechanistic studies, disease modeling, and high-throughput drug discovery.

Human brain organoids have set the precedent for validation of in vitro models (Lloyd-Davies Sánchez et al., 2024). Morphological validation includes analysis of organoid size, shape, cellular composition, and structural organization using immunohistochemistry and imaging techniques. Notably, the size, shape and viability of human brain organoids can vary significantly both within and between batches. To address this heterogeneity, a level of standardization needs to be achieved to benchmark selected protocols which can be applied to newly adopted differentiation protocols to assure the consistency of data across experiments. Researchers have focused on high-throughput imaging (Handcock et al., 2025; Deininger et al., 2023), 3D spatial single cell and proteomic-based analysis methods (Albanese et al., 2020) to assess organoid morphology. However, investigating the cellular architecture and diversity of human and mouse brain organoids typically requires sectioning prior to immunohistochemistry (IHC) (Bremond Martin et al., 2021) due to their large tissue sizes (typically thicker than 1 mm) (Pasca et al., 2015). In contrast, zebrafish brain organoids are small enough to perform whole-mount staining, eliminating the need for sectioning. However, the limited availability of validated antibodies for zebrafish tissues remains a challenge for detailed cellular characterization.

In addition, numerous studies characterized the transcriptomic (Cheroni et al., 2022; Tanaka et al., 2020) and proteomic (Elmkvist et al., 2024) profiles of human and mouse brain organoids during neuronal development to assess cellular identity, developmental dynamics, and cytoarchitecture, demonstrating that organoids largely recapitulate in vivo programs with only minor differences (Bhaduri et al., 2020). This high degree of concordance between in vitro and in vivo developmental trajectories is not limited to mammalian systems. Zebrafish brain organoids also exhibit similar fidelity as shown by Zilova et al. (2021) as pluripotent zebrafish embryonic cells self-organize into retinal tissue that mirrors early in vivo eye development. This further underscore the broader applicability of organoid systems across species for modeling conserved neurodevelopmental programs.

The electrical properties of single neurons in vitro are measured using whole-cell patch-clamp recordings, which is the gold standard in electrophysiology today. This technique enables detailed characterization of intrinsic neuronal properties, including spontaneous fluctuations in membrane potential, action potential firing, and synaptic activity. Due to their small size, zebrafish brain organoids can be patched intact (Landry et al., 2023), in contrast to larger human- and mouse brain organoids, which require slicing to access individual cells for recording (Segev et al., 2016). This offers a technical advantage for high-resolution functional studies. Multi-electrode arrays (MEAs) enable non-invasive recording of spontaneous or evoked electrical activity across networks of neurons within the organoid. This technique measures spiking rates, burst patterns, and network synchrony, reflecting functional connectivity and coordinated circuit behavior (Sit et al., 2024). The observed electrophysiological phenotypes of mouse and zebrafish brain organoids should be compared to neurons in vivo, in human brain organoid models in vitro, and even to patient-derived post-mortem brain tissue samples as a clinical reference, to assess successful recapitulation. Furthermore, if these models reliably reproduce treatment responses seen in vivo and in patients, this will provide predictive validity and the potential to complement human brain organoids and whole-animal studies for disease modeling and high-throughput drug screening.

Future integration of emerging NAMs in neuroscience

Within the growing landscape of NAMs in neuroscience, brain organoids are promising in vitro tools among others. Although the methodology for generating these organoids is optimized to ensure reproducibility, comprehensive functional validation remains essential to establish their reliability and relevance. Compared to mammalian brain organoids (human and mouse), zebrafish brain organoids offer strategic advantages, including lower cost, faster production, great scalability, and simpler protocols, making them an attractive addition to the NAMs toolkit for early discovery purposes. As novel, early-stage NAMs, both mouse and zebrafish brain organoids hold significant potential for preclinical research, yet further research is essential to rigorously assess their predictive power. To reach their complete potential, clear standards, refinements in methodology, and systematic incorporation into preclinical testing frameworks are needed. Emphasizing reproducibility, harmonization, and cross-system evaluation can help advance brain organoids toward a more predictive and ethically responsible neuroscience paradigm.

Moving forward, the scientific roadmap for brain organoids, among other NAMs, should focus on three complementary action paths that together enable their systematic validation, regulatory alignment, and integration into multi-model research pipelines. First, cross-laboratory reproducibility and shared reference datasets are essential. Coordinated inter-laboratory trials, with academic and regulatory partners such as the OECD and EURL ECVAM, should assess reproducibility of key morphological, transcriptomic, and electrophysiological endpoints. Developing openly accessible reference datasets and standardized benchmark compounds and neurotoxicants will support comparison of in vitro results with in vivo data. Consistency will further depend on quantifiable quality metrics such as organoid size distribution, cell-type composition, viability, and neural activity.

Second, alignment with OECD and regulatory validation frameworks will be critical to promote broader acceptance of available and emerging NAMs. Regulatory acceptance requires demonstrating equivalence or superiority to existing in vitro and in vivo methods. Endpoints should be mapped to existing OECD test guidelines for developmental neurotoxicity and incorporated into the OECD’s modular validation approach. Defining performance standards, including accuracy, precision, and biological relevance relative to established zebrafish and rodent data, will further support transparent regulatory pathways and harmonized implementation.

Third, integration of complementary models will strengthen translational value and predictive power. Developing mouse and zebrafish brain organoids should not aim to replace but to complement and accelerate existing human in vitro and conventional in vivo animal approaches. Simple 2D cultures are useful for mechanistic studies and screening, non-human brain organoids offer an intermediate platform, with zebrafish brain organoids as an emerging and scalable model for disease modeling and toxicity testing, and advanced human brain organoids provide patient-specific insights and translational relevance. Zebrafish embryos and larvae add the complexity of a whole organism, enabling behavioral and neurophysiological studies (high face validity) as a pre-rodent model and NAM. Used together, these models can address the limitations of any single system and create a more robust, ethically responsible pipeline for preclinical research. Parallel use of the non-mammalian zebrafish brain organoids and mammalian mouse and human organoids further enable cross-species comparisons, helping to identify conserved mechanisms of neurodevelopment. Computational modeling and quantitative adverse outcome pathways can further connect cellular perturbations observed in organoids with organismal phenotypes, improving mechanistic interpretation and supporting extrapolation to human health outcomes.

This integrated approach illustrates a flexible, multi-level framework for predictive neurotoxicity and translational research (Figure 5), spanning computational prediction to in vivo validation. Rather than a linear hierarchy, the system operates as an iterative and modular network, where insights from in silico models guide in vitro and in vivo experimentation, and in vitro and in vivo data refine computational predictions. Brain organoids occupy an intermediate and integrative position, linking cellular-level mechanisms with whole-organism responses, thus enhancing both translational relevance and regulatory confidence. This dynamic integration fosters a more predictive, ethical, and mechanistically informed preclinical research paradigm.

Figure 5

Figure 5. Integration of new approach methodologies (NAMs) across the translational spectrum. This multi-level flowchart illustrates the iterative and modular integration of NAMs, linking in silico, in vitro, and in vivo approaches through continuous feedback. In silico models generate computational predictions that guide experimental design. In vitro assays employ increasingly complex models, from simple 2D cultures for mechanistic studies to 3D organoids, including mouse and zebrafish organoids as intermediate systems, and ultimately human organoids for advanced validation. Depending on the research question, one or more in vitro or in vivo models may be selected, typically, but not necessarily, progressing from simpler to more physiologically relevant systems. In vivo data can further refine and validate predictions, reinforcing the iterative NAMs framework. Finally, integration into regulatory decision-making is supported through OECD (Organisation for Economic Co-operation and Development) guidance and validation frameworks, ensuring consistency, reliability, and international acceptance of NAM-derived data. QSAR, Quantitative Structure–Activity Relationship; PBPK, Physiologically Based Pharmacokinetic; AI/ML, Artificial Intelligence/Machine Learning. Figure created with Biorender.com.

Conclusion

In light of the growing importance of NAMs in neuroscience as ethical, human-relevant, and efficient alternatives to traditional animal testing, we critically assessed the currently available NAMs, ranging from conventional 2D cell cultures to advanced human brain organoids, non-human organoids and zebrafish, in direct comparison to mammalian models. Moreover, their respective strengths, limitations, and roles in neurodevelopmental, pathomechanistic, and neurotoxicity research have been mapped. While each model has unique strengths, combining complementary systems is essential to overcome individual limitations, supporting more robust and scalable pipelines for early-phase screening, safety assessment, disease modeling, and drug discovery. By integrating 2D, 3D, and alternative in vivo models, the field can advance toward more predictive, efficient, and ethically responsible neuroscience research. Continued research, methodological refinement, and standardization will be critical to realize the full potential of NAMs.

Author contributions

DI: Writing – review & editing, Writing – original draft. AN: Writing – review & editing, Writing – original draft. DC: Writing – review & editing, Writing – original draft.

Funding

The author(s) declare that financial support was received for the research and/or publication of this article. We acknowledge support from grants of KU Leuven (C3/24/036 (D.I.) and IOFm/16/003 (A.N.)).

Acknowledgments

We sincerely thank Prof. Peter de Witte (KU Leuven) and Prof. dr. Lieven Lagae (UZ Leuven, Pediatric Neurologist) for the thoughtful discussions and their insightful feedback that greatly contributed to this work.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declare that no Gen AI was used in the creation of this manuscript.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

Acampora, D., Mazan, S., Lallemand, Y., Avantaggiato, V., Maury, M., Simeone, A., et al. (1995). Forebrain and midbrain regions are deleted in Otx2−/− mutants due to a defective anterior neuroectoderm specification during gastrulation. Development 121, 3279–3290. doi: 10.1242/dev.121.10.3279,

PubMed Abstract | Crossref Full Text | Google Scholar

Achenbach, J. C., Leggiadro, C., Sperker, S. A., Woodland, C., and Ellis, L. D. (2020). Comparison of the zebrafish embryo toxicity assay and the general and Behavioral embryo toxicity assay as new approach methods for chemical screening. Toxics. 8:126. doi: 10.3390/toxics8040126,

PubMed Abstract | Crossref Full Text | Google Scholar

Albanese, A., Swaney, J. M., Yun, D. H., Evans, N. B., Antonucci, J. M., Velasco, S., et al. (2020). Multiscale 3D phenotyping of human cerebral organoids. Sci. Rep. 10:21487. doi: 10.1038/s41598-020-78130-7,

PubMed Abstract | Crossref Full Text | Google Scholar

Avila, A. M., Bebenek, I., Bonzo, J. A., Bourcier, T., Davis Bruno, K. L., Carlson, D. B., et al. (2020). An FDA/CDER perspective on nonclinical testing strategies: classical toxicology approaches and new approach methodologies (NAMs). Regul. Toxicol. Pharmacol. 114:104662. doi: 10.1016/j.yrtph.2020.104662,

PubMed Abstract | Crossref Full Text | Google Scholar

Baccaro, M., Barroso, J., Berggren, E., Bopp, S., and Bridio, S. (2025). Non-animal methods in science and regulation-EURL ECVAM status report 2024. Luxembourg: Publications Office of the European Union.

Google Scholar

Bagley, J. A., Reumann, D., Bian, S., Levi-Strauss, J., and Knoblich, J. A. (2017). Fused cerebral organoids model interactions between brain regions. Nat. Methods 14, 743–751. doi: 10.1038/nmeth.4304,

PubMed Abstract | Crossref Full Text | Google Scholar

Bakken, T. E., Jorstad, N. L., Hu, Q., Lake, B. B., Tian, W., Kalmbach, B. E., et al. (2021). Comparative cellular analysis of motor cortex in human, marmoset and mouse. Nature 598, 111–119. doi: 10.1038/s41586-021-03465-8,

PubMed Abstract | Crossref Full Text | Google Scholar

Bal-Price, A., Hogberg, H. T., Crofton, K. M., Daneshian, M., FitzGerald, R. E., Fritsche, E., et al. (2018). Recommendation on test readiness criteria for new approach methods in toxicology: exemplified for developmental neurotoxicity. ALTEX 35, 306–352. doi: 10.14573/altex.1712081,

PubMed Abstract | Crossref Full Text | Google Scholar

Bambino, K., and Chu, J. (2017). Zebrafish in toxicology and environmental health. Curr. Top. Dev. Biol. 124, 331–367. doi: 10.1016/bs.ctdb.2016.10.007,

PubMed Abstract | Crossref Full Text | Google Scholar

Baraban, S. C., Dinday, M. T., and Hortopan, G. A. (2013). Drug screening in Scn1a zebrafish mutant identifies clemizole as a potential Dravet syndrome treatment. Nat. Commun. 4:2410. doi: 10.1038/ncomms3410,

PubMed Abstract | Crossref Full Text | Google Scholar

Bartfeld, S., and Clevers, H. (2017). Stem cell-derived organoids and their application for medical research and patient treatment. J. Mol. Med. (Berl) 95, 729–738. doi: 10.1007/s00109-017-1531-7,

PubMed Abstract | Crossref Full Text | Google Scholar

Beccari, L., Moris, N., Girgin, M., Turner, D. A., Baillie-Johnson, P., Cossy, A. C., et al. (2018). Multi-axial self-organization properties of mouse embryonic stem cells into gastruloids. Nature 562, 272–276. doi: 10.1038/s41586-018-0578-0,

PubMed Abstract | Crossref Full Text | Google Scholar

Beed, P., Ray, S., Velasquez, L. M., Stumpf, A., Parthier, D., Swaminathan, A., et al. (2020). Species-specific differences in synaptic transmission and plasticity. Sci. Rep. 10:16557. doi: 10.1038/s41598-020-73547-6,

PubMed Abstract | Crossref Full Text | Google Scholar

Beilmann, M., Adkins, K., Boonen, H. C. M., Hewitt, P., Hu, W., Mader, R., et al. (2025). Application of new approach methodologies for nonclinical safety assessment of drug candidates. Nat. Rev. Drug Discov. 24, 705–725. doi: 10.1038/s41573-025-01182-9,

PubMed Abstract | Crossref Full Text | Google Scholar

Beilmann, M., Boonen, H., Czich, A., Dear, G., Hewitt, P., Mow, T., et al. (2019). Optimizing drug discovery by investigative toxicology: current and future trends. ALTEX 36, 289–313. doi: 10.14573/altex.1808181

Crossref Full Text | Google Scholar

Bell, L., Simonneau, C., Zanini, C., Kassianidou, E., Zundel, C., Neff, R., et al. (2025). Advanced tissue technologies of blood-brain barrier organoids as high throughput toxicity readouts in drug development. Heliyon. 11:e40813. doi: 10.1016/j.heliyon.2024.e40813,

PubMed Abstract | Crossref Full Text | Google Scholar

Bergmann, S., Lawler, S. E., Qu, Y., Fadzen, C. M., Wolfe, J. M., Regan, M. S., et al. (2018). Blood-brain-barrier organoids for investigating the permeability of CNS therapeutics. Nat. Protoc. 13, 2827–2843. doi: 10.1038/s41596-018-0066-x,

PubMed Abstract | Crossref Full Text | Google Scholar

Bhaduri, A., Andrews, M. G., Mancia Leon, W., Jung, D., Shin, D., Allen, D., et al. (2020). Cell stress in cortical organoids impairs molecular subtype specification. Nature 578, 142–148. doi: 10.1038/s41586-020-1962-0,

PubMed Abstract | Crossref Full Text | Google Scholar

Boulting, G. L., Kiskinis, E., Croft, G. F., Amoroso, M. W., Oakley, D. H., Wainger, B. J., et al. (2011). A functionally characterized test set of human induced pluripotent stem cells. Nat. Biotechnol. 29, 279–286. doi: 10.1038/nbt.1783,

PubMed Abstract | Crossref Full Text | Google Scholar

Boyd, W. A., Smith, M. V., Co, C. A., Pirone, J. R., Rice, J. R., Shockley, K. R., et al. (2016). Developmental effects of the ToxCast phase I and phase II Chemicals in Caenorhabditis elegans and corresponding responses in zebrafish, rats, and rabbits. Environ. Health Perspect. 124, 586–593. doi: 10.1289/ehp.1409645,

PubMed Abstract | Crossref Full Text | Google Scholar

Brannen, K. C., Panzica-Kelly, J. M., Danberry, T. L., and Augustine-Rauch, K. A. (2010). Development of a zebrafish embryo teratogenicity assay and quantitative prediction model. Birth Defects Res. B Dev. Reprod. Toxicol. 89, 66–77. doi: 10.1002/bdrb.20223,

PubMed Abstract | Crossref Full Text | Google Scholar

Bremond Martin, C., Simon Chane, C., Clouchoux, C., and Histace, A. (2021). Recent trends and perspectives in cerebral organoids imaging and analysis. Front. Neurosci. 15:629067. doi: 10.3389/fnins.2021.629067,

PubMed Abstract | Crossref Full Text | Google Scholar

Bult, C. J., and Sternberg, P. W. (2023). The alliance of genome resources: transforming comparative genomics. Mamm. Genome 34, 531–544. doi: 10.1007/s00335-023-10015-2,

PubMed Abstract | Crossref Full Text | Google Scholar

Burbank, M., Gautier, F., Hewitt, N., Detroyer, A., Guillet-Revol, L., Carron, L., et al. (2023). Advancing the use of new approach methodologies for assessing teratogenicity: building a tiered approach. Reprod. Toxicol. 120:108454. doi: 10.1016/j.reprotox.2023.108454,

PubMed Abstract | Crossref Full Text | Google Scholar

Cakir, B., Xiang, Y., Tanaka, Y., Kural, M. H., Parent, M., Kang, Y. J., et al. (2019). Engineering of human brain organoids with a functional vascular-like system. Nat. Methods 16, 1169–1175. doi: 10.1038/s41592-019-0586-5,

PubMed Abstract | Crossref Full Text | Google Scholar

Camp, J. G., Badsha, F., Florio, M., Kanton, S., Gerber, T., Wilsch-Brauninger, M., et al. (2015). Human cerebral organoids recapitulate gene expression programs of fetal neocortex development. Proc. Natl. Acad. Sci. USA 112, 15672–15677. doi: 10.1073/pnas.1520760112

Crossref Full Text | Google Scholar

Cao, Y. (2022). The uses of 3D human brain organoids for neurotoxicity evaluations: a review. Neurotoxicology 91, 84–93. doi: 10.1016/j.neuro.2022.05.004,

PubMed Abstract | Crossref Full Text | Google Scholar

Cassar, S., Adatto, I., Freeman, J. L., Gamse, J. T., Iturria, I., Lawrence, C., et al. (2020). Use of zebrafish in drug discovery toxicology. Chem. Res. Toxicol. 33, 95–118. doi: 10.1021/acs.chemrestox.9b00335,

PubMed Abstract | Crossref Full Text | Google Scholar

Centeno, E. G. Z., Cimarosti, H., and Bithell, A. (2018). 2D versus 3D human induced pluripotent stem cell-derived cultures for neurodegenerative disease modelling. Mol. Neurodegener. 13:27. doi: 10.1186/s13024-018-0258-4,

PubMed Abstract | Crossref Full Text | Google Scholar

Chai, Y., Qi, K., Wu, Y., Li, D., Tan, G., Guo, Y., et al. (2024). All-optical interrogation of brain-wide activity in freely swimming larval zebrafish. iScience. 27:108385. doi: 10.1016/j.isci.2023.108385,

PubMed Abstract | Crossref Full Text | Google Scholar

Chang, N., Sun, C., Gao, L., Zhu, D., Xu, X., Zhu, X., et al. (2013). Genome editing with RNA-guided Cas9 nuclease in zebrafish embryos. Cell Res. 23, 465–472. doi: 10.1038/cr.2013.45,

PubMed Abstract | Crossref Full Text | Google Scholar

Chauhdari, T., Zaidi, S. A., Su, J., and Ding, Y. (2025). Organoids meet microfluidics: recent advancements, challenges, and future of organoids-on-chip. Vitro Model 4, 71–88. doi: 10.1007/s44164-025-00086-7,

PubMed Abstract | Crossref Full Text | Google Scholar

Chen, C., Ji, W., and Niu, Y. (2021). Primate organoids and gene-editing technologies toward next-generation biomedical research. Trends Biotechnol. 39, 1332–1342. doi: 10.1016/j.tibtech.2021.03.010,

PubMed Abstract | Crossref Full Text | Google Scholar

Cheroni, C., Trattaro, S., Caporale, N., Lopez-Tobon, A., Tenderini, E., Sebastiani, S., et al. (2022). Benchmarking brain organoid recapitulation of fetal corticogenesis. Transl. Psychiatry 12:520. doi: 10.1038/s41398-022-02279-0,

PubMed Abstract | Crossref Full Text | Google Scholar

Cho, A. N., Jin, Y., An, Y., Kim, J., Choi, Y. S., Lee, J. S., et al. (2021). Microfluidic device with brain extracellular matrix promotes structural and functional maturation of human brain organoids. Nat. Commun. 12:4730. doi: 10.1038/s41467-021-24775-5,

PubMed Abstract | Crossref Full Text | Google Scholar

Chuang, J. C., Mathers, P. H., and Raymond, P. A. (1999). Expression of three Rx homeobox genes in embryonic and adult zebrafish. Mech. Dev. 84, 195–198. doi: 10.1016/s0925-4773(99)00077-5,

PubMed Abstract | Crossref Full Text | Google Scholar

Ciarpella, F., Zamfir, R. G., Campanelli, A., Pedrotti, G., Di Chio, M., Bottani, E., et al. (2023). Generation of mouse hippocampal brain organoids from primary embryonic neural stem cells. STAR Protoc. 4:102413. doi: 10.1016/j.xpro.2023.102413,

PubMed Abstract | Crossref Full Text | Google Scholar

Collodi, P., Kamei, Y., Ernst, T., Miranda, C., Buhler, D. R., and Barnes, D. W. (1992). Culture of cells from zebrafish (Brachydanio rerio) embryo and adult tissues. Cell Biol. Toxicol. 8, 43–61. doi: 10.1007/BF00119294,

PubMed Abstract | Crossref Full Text | Google Scholar

Copmans, D., Siekierska, A., and de Witte, P. A. M. (2017). “Chapter 26—zebrafish models of epilepsy and epileptic seizures” in Models of seizures and epilepsy (second edition). eds. A. Pitkänen, P. S. Buckmaster, A. S. Galanopoulou, and S. L. Moshé (Academic Press), 369–384.

Google Scholar

Csukovich, G., Pratscher, B., and Burgener, I. A. (2022). The world of organoids: gastrointestinal disease modelling in the age of 3R and one health with specific relevance to dogs and cats. Animals (Basel) 12:2461. doi: 10.3390/ani12182461,

PubMed Abstract | Crossref Full Text | Google Scholar

Csukovich, G, Pratscher, B., and Burgener, I.A. The importance of organoids for one health. Available online at: https://encyclopedia.pub/entry/27713 (2022).

Google Scholar

Cucullo, L., Marchi, N., Hossain, M., and Janigro, D. (2011). A dynamic in vitro BBB model for the study of immune cell trafficking into the central nervous system. J. Cereb. Blood Flow Metab. 31, 767–777. doi: 10.1038/jcbfm.2010.162,

PubMed Abstract | Crossref Full Text | Google Scholar

Cui, X., Li, X., Zheng, H., Su, Y., Zhang, S., Li, M., et al. (2024). Human midbrain organoids: a powerful tool for advanced Parkinson's disease modeling and therapy exploration. NPJ Parkinsons Dis. 10:189. doi: 10.1038/s41531-024-00799-8,

PubMed Abstract | Crossref Full Text | Google Scholar

Dabhekar, S. V., Dhokne, M. D., Dalal, V., Lokhande, J., Taksande, B. S., Nakhate, K. T., et al. (2024). In vitro cell line culture for brain research and its limitations. In: application of nanocarriers in brain delivery of therapeutics, ed. Alexander, A. Singapore: Springer. doi: 10.1007/978-981-97-2859-6_11

Crossref Full Text | Google Scholar

De Meulemeester, A. S., Reid, C., Auvin, S., Carlen, P. L., Cole, A. J., Szlendak, R., et al. (2024). WONOEP appraisal: Modeling early onset epilepsies. Epilepsia 65, 2553–2566. doi: 10.1111/epi.18063,

PubMed Abstract | Crossref Full Text | Google Scholar

Deininger, L., Jung-Klawitter, S., Mikut, R., Richter, P., Fischer, M., Karimian-Jazi, K., et al. (2023). An AI-based segmentation and analysis pipeline for high-field MR monitoring of cerebral organoids. Sci. Rep. 13:21231. doi: 10.1038/s41598-023-48343-7,

PubMed Abstract | Crossref Full Text | Google Scholar

Demin, K. A., Smagin, D. A., Kovalenko, I. L., Strekalova, T., and Galstyan, D. S.Kolesnikova TO, et al. (2021). CNS genomic profiling in the mouse chronic social stress model implicates a novel category of candidate genes integrating affective pathogenesis. Prog. Neuro-Psychopharmacol. Biol. Psychiatry 105:110086. doi: 10.1016/j.pnpbp.2020.110086,

PubMed Abstract | Crossref Full Text | Google Scholar

Dimos, J. T., Rodolfa, K. T., Niakan, K. K., Weisenthal, L. M., Mitsumoto, H., Chung, W., et al. (2008). Induced pluripotent stem cells generated from patients with ALS can be differentiated into motor neurons. Science 321, 1218–1221. doi: 10.1126/science.1158799,

PubMed Abstract | Crossref Full Text | Google Scholar

Dix, D. J., Houck, K. A., Martin, M. T., Richard, A. M., Setzer, R. W., and Kavlock, R. J. (2007). The ToxCast program for prioritizing toxicity testing of environmental chemicals. Toxicol. Sci. 95, 5–12. doi: 10.1093/toxsci/kfl103,

PubMed Abstract | Crossref Full Text | Google Scholar

Doorn, N., van Hugte, E. J. H., Ciptasari, U., Mordelt, A., Meijer, H. G. E., Schubert, D., et al. (2023). An in silico and in vitro human neuronal network model reveals cellular mechanisms beyond Na(V)1.1 underlying Dravet syndrome. Stem Cell Reports. 18, 1686–1700. doi: 10.1016/j.stemcr.2023.06.003,

PubMed Abstract | Crossref Full Text | Google Scholar

Dore, R., Chang, C. T., Decleve, A., Brunori, G., Ludlam, W. G., Huang, A., et al. (2025). ELFN1 deficiency: the mechanistic basis and phenotypic spectrum of a neurodevelopmental disorder with epilepsy. Genet. Med. 27:101506. doi: 10.1016/j.gim.2025.101506,

PubMed Abstract | Crossref Full Text | Google Scholar

Driever, W., and Rangini, Z. (1993). Characterization of a cell line derived from zebrafish (Brachydanio rerio) embryos. In Vitro Cell. Dev. Biol. Anim. 29, 749–754. doi: 10.1007/BF02631432,

PubMed Abstract | Crossref Full Text | Google Scholar

Eiraku, M., and Sasai, Y. (2011). Mouse embryonic stem cell culture for generation of three-dimensional retinal and cortical tissues. Nat. Protoc. 7, 69–79. doi: 10.1038/nprot.2011.429,

PubMed Abstract | Crossref Full Text | Google Scholar

Elmkvist, S. B., Bogetofte, H., Jensen, P., Jakobsen, L. A., Havelund, J. F., Ryding, M., et al. (2024). Temporal proteomic and PTMomic atlas of cerebral organoid development. bioRxiv. doi: 10.1101/2024.09.03.610941

Crossref Full Text | Google Scholar

Encinas, M., Iglesias, M., Liu, Y., Wang, H., Muhaisen, A., Cena, V., et al. (2000). Sequential treatment of SH-SY5Y cells with retinoic acid and brain-derived neurotrophic factor gives rise to fully differentiated, neurotrophic factor-dependent, human neuron-like cells. J. Neurochem. 75, 991–1003. doi: 10.1046/j.1471-4159.2000.0750991.x,

PubMed Abstract | Crossref Full Text | Google Scholar

EU. (2010). Directive 2010/63/EU of the European Parliament and of the council of 22 September 2010 on the protection of animals used for scientific purposes text with EEA relevance. http://data.europa.eu/eli/dir/2010/63/oj2010

Google Scholar

European Commission. (2021). Directorate-General for Research and Innovation HE. The EU research and innovation programme for a green, healthy, digital and inclusive Europe. Publications Office of the European Union.

Google Scholar

European Parliament and Council. (2006). Regulation (EC) no 1907/2006 of the European Parliament and of the council of 18 December 2006 concerning the registration, evaluation, authorisation and restriction of chemicals (REACH), establishing a European chemicals agency, amending directive 1999/45/EC and repealing council regulation (EEC) no 793/93 and commission regulation (EC) no 1488/94 as well as council directive 76/769/EEC and commission directives 91/155/EEC, 93/67/EEC, 93/105/EC and 2000/21/EC. Available online at: http://data.europa.eu/eli/reg/2006/1907/2025-04-22

Google Scholar

European Parliament and Council. (2009). Regulation (EC) no 1223/2009 of the European Parliament and of the council of 30 November 2009 on cosmetic products. Available online at: http://data.europa.eu/eli/reg/2009/1223/oj

Google Scholar

European Medicines Agency (EMA) (2011). EMA/CHMP/ICH/731268/1998. ICH guideline S6 (R1) – Preclinical safety evaluation of biotechnology-derived pharmaceuticals. London, UK: EMA.

Google Scholar

European Medicines Agency (EMA). (2017). EMEA/CHMP/SWP/28367/07 rev. 1: Guideline on strategies to identify and mitigate risks for first-in-human and early clinical trials with investigational medicinal products. London, UK: EMA.

Google Scholar

FAO, UNEP, WHO, and WOAH. (2022). One Health Joint Plan of Action (2022-2026). Working together for the health of humans, animals, plants and the environment. Rome. doi: 10.4060/cc2289en

Crossref Full Text | Google Scholar

Fan, P., Wang, Y., Xu, M., Han, X., and Liu, Y. (2022). The application of brain organoids in assessing neural toxicity. Front. Mol. Neurosci. 15:799397. doi: 10.3389/fnmol.2022.799397,

PubMed Abstract | Crossref Full Text | Google Scholar

Fatehullah, A., Tan, S. H., and Barker, N. (2016). Organoids as an in vitro model of human development and disease. Nat. Cell Biol. 18, 246–254. doi: 10.1038/ncb3312,

PubMed Abstract | Crossref Full Text | Google Scholar

Fitzgerald, P. J. (2009). Neuromodulating mice and men: are there functional species differences in neurotransmitter concentration? Neurosci. Biobehav. Rev. 33, 1037–1041. doi: 10.1016/j.neubiorev.2009.04.003,

PubMed Abstract | Crossref Full Text | Google Scholar

Fitzgerald, J. A., Konemann, S., Krumpelmann, L., Zupanic, A., and Vom Berg, C. (2021). Approaches to test the neurotoxicity of environmental contaminants in the zebrafish model: from behavior to molecular mechanisms. Environ. Toxicol. Chem. 40, 989–1006. doi: 10.1002/etc.4951

Crossref Full Text | Google Scholar

Forner-Piquer, I., Klement, W., Gangarossa, G., Zub, E., de Bock, F., Blaquiere, M., et al. (2021). Varying modalities of perinatal exposure to a pesticide cocktail elicit neurological adaptations in mice and zebrafish. Environ. Pollut. 278:116755. doi: 10.1016/j.envpol.2021.116755,

PubMed Abstract | Crossref Full Text | Google Scholar

Frega, M., van Gestel, S. H., Linda, K., van der Raadt, J., Keller, J., Van Rhijn, J. R., et al. (2017). Rapid neuronal differentiation of induced pluripotent stem cells for measuring network activity on micro-electrode arrays. J. Vis. Exp. 119:54900 doi: 10.3791/54900

Crossref Full Text | Google Scholar

Fulton, T., Trivedi, V., Attardi, A., Anlas, K., Dingare, C., Arias, A. M., et al. (2020). Axis specification in zebrafish is robust to cell mixing and reveals a regulation of pattern formation by morphogenesis. Curr. Biol. 30, 3063–3064. doi: 10.1016/j.cub.2020.07.022,

PubMed Abstract | Crossref Full Text | Google Scholar

Gattazzo, F., Urciuolo, A., and Bonaldo, P. (2014). Extracellular matrix: a dynamic microenvironment for stem cell niche. Biochim. Biophys. Acta 1840, 2506–2519. doi: 10.1016/j.bbagen.2014.01.010,

PubMed Abstract | Crossref Full Text | Google Scholar

Gerakis, Y., and Hetz, C. (2019). Brain organoids: a next step for humanized Alzheimer's disease models? Mol. Psychiatry 24, 474–478. doi: 10.1038/s41380-018-0343-7,

PubMed Abstract | Crossref Full Text | Google Scholar

Ghosh, C., Liu, Y., Ma, C., and Collodi, P. (1997). Cell cultures derived from early zebrafish embryos differentiate in vitro into neurons and astrocytes. Cytotechnology 23, 221–230. doi: 10.1023/A:1007915618413,

PubMed Abstract | Crossref Full Text | Google Scholar

Gjorevski, N., Avignon, B., Gerard, R., Cabon, L., Roth, A. B., Bscheider, M., et al. (2020). Neutrophilic infiltration in organ-on-a-chip model of tissue inflammation. Lab Chip 20, 3365–3374. doi: 10.1039/d0lc00417k

Crossref Full Text | Google Scholar

Good, P. J. (1995). A conserved family of elav-like genes in vertebrates. Proc. Natl. Acad. Sci. USA 92, 4557–4561. doi: 10.1073/pnas.92.10.4557,

PubMed Abstract | Crossref Full Text | Google Scholar

Goswami, M., Yashwanth, B. S., Trudeau, V., and Lakra, W. S. (2022). Role and relevance of fish cell lines in advanced in vitro research. Mol. Biol. Rep. 49, 2393–2411. doi: 10.1007/s11033-021-06997-4,

PubMed Abstract | Crossref Full Text | Google Scholar

Gribkoff, V. K., and Kaczmarek, L. K. (2017). The need for new approaches in CNS drug discovery: why drugs have failed, and what can be done to improve outcomes. Neuropharmacology 120, 11–19. doi: 10.1016/j.neuropharm.2016.03.021,

PubMed Abstract | Crossref Full Text | Google Scholar

Griffin, A., Carpenter, C., Liu, J., Paterno, R., Grone, B., Hamling, K., et al. (2021). Phenotypic analysis of catastrophic childhood epilepsy genes. Commun Biol. 4:680. doi: 10.1038/s42003-021-02221-y,

PubMed Abstract | Crossref Full Text | Google Scholar

Guglielmi, L., Lloyd-Davies-Sánchez, D., González Martínez, J., and Lancaster, M. A. (2024). A minimally guided organoid model for cross-species comparisons of cerebellar development. bioRxiv. doi: 10.1101/2024.10.02.616236

Crossref Full Text | Google Scholar

Guo, S. (2009). Using zebrafish to assess the impact of drugs on neural development and function. Expert Opin. Drug Discov. 4, 715–726. doi: 10.1517/17460440902988464,

PubMed Abstract | Crossref Full Text | Google Scholar

Gustafson, A. L., Stedman, D. B., Ball, J., Hillegass, J. M., Flood, A., Zhang, C. X., et al. (2012). Inter-laboratory assessment of a harmonized zebrafish developmental toxicology assay—progress report on phase I. Reprod. Toxicol. 33, 155–164. doi: 10.1016/j.reprotox.2011.12.004,

PubMed Abstract | Crossref Full Text | Google Scholar

Handcock, S., Richards, K., Karle, T. J., Kairath, P., Soch, A., Chavez, C. A., et al. (2025). Three-dimensional morphological characterisation of human cortical organoids using a customised image analysis workflow. Organ 4:1. doi: 10.3390/organoids4010001,

PubMed Abstract | Crossref Full Text | Google Scholar

He, S., Salas-Vidal, E., Rueb, S., Krens, S. F., Meijer, A. H., Snaar-Jagalska, B. E., et al. (2006). Genetic and transcriptome characterization of model zebrafish cell lines. Zebrafish 3, 441–453. doi: 10.1089/zeb.2006.3.441,

PubMed Abstract | Crossref Full Text | Google Scholar

He, J., Xu, P., Xu, T., Yu, H., Wang, L., Chen, R., et al. (2024). Therapeutic potential of hydrogen-rich water in zebrafish model of Alzheimer's disease: targeting oxidative stress, inflammation, and the gut-brain axis. Front. Aging Neurosci. 16:1515092. doi: 10.3389/fnagi.2024.1515092,

PubMed Abstract | Crossref Full Text | Google Scholar

Helms, H. C., Abbott, N. J., Burek, M., Cecchelli, R., Couraud, P. O., Deli, M. A., et al. (2016). In vitro models of the blood-brain barrier: An overview of commonly used brain endothelial cell culture models and guidelines for their use. J. Cereb. Blood Flow Metab. 36, 862–890. doi: 10.1177/0271678X16630991,

PubMed Abstract | Crossref Full Text | Google Scholar

Ho, S. Y., Goh, C. W., Gan, J. Y., Lee, Y. S., Lam, M. K., Hong, N., et al. (2014). Derivation and long-term culture of an embryonic stem cell-like line from zebrafish blastomeres under feeder-free condition. Zebrafish 11, 407–420. doi: 10.1089/zeb.2013.0879,

PubMed Abstract | Crossref Full Text | Google Scholar

Hoffmann, S., Marigliani, B., Akgun-Olmez, S. G., Ireland, D., Cruz, R., Busquet, F., et al. (2021). A systematic review to compare chemical Hazard predictions of the zebrafish embryotoxicity test with mammalian prenatal developmental toxicity. Toxicol. Sci. 183, 14–35. doi: 10.1093/toxsci/kfab072,

PubMed Abstract | Crossref Full Text | Google Scholar

Hong, Y., Winkler, C., and Schartl, M. (1996). Pluripotency and differentiation of embryonic stem cell lines from the medakafish (Oryzias latipes). Mech. Dev. 60, 33–44. doi: 10.1016/s0925-4773(96)00596-5,

PubMed Abstract | Crossref Full Text | Google Scholar

Hoshi, Y., Uchida, Y., Tachikawa, M., Inoue, T., Ohtsuki, S., and Terasaki, T. (2013). Quantitative atlas of blood-brain barrier transporters, receptors, and tight junction proteins in rats and common marmoset. J. Pharm. Sci. 102, 3343–3355. doi: 10.1002/jps.23575,

PubMed Abstract | Crossref Full Text | Google Scholar

Howe, K., Clark, M. D., Torroja, C. F., Torrance, J., Berthelot, C., Muffato, M., et al. (2013). The zebrafish reference genome sequence and its relationship to the human genome. Nature 496, 498–503. doi: 10.1038/nature12111,

PubMed Abstract | Crossref Full Text | Google Scholar

Hu, H., Gehart, H., Artegiani, B., Lo-I, C., Dekkers, F., Basak, O., et al. (2018). Long-term expansion of functional mouse and human hepatocytes as 3D organoids. Cell 175, 1591–606 e19. doi: 10.1016/j.cell.2018.11.013

Crossref Full Text | Google Scholar

Hwang, W. Y., Fu, Y., Reyon, D., Maeder, M. L., Tsai, S. Q., Sander, J. D., et al. (2013). Efficient genome editing in zebrafish using a CRISPR-Cas system. Nat. Biotechnol. 31, 227–229. doi: 10.1038/nbt.2501,

PubMed Abstract | Crossref Full Text | Google Scholar

Initiative IH. Available online at: https://www.ihi.europa.eu/.

Google Scholar

Kalueff, A. V., Stewart, A. M., and Gerlai, R. (2014). Zebrafish as an emerging model for studying complex brain disorders. Trends Pharmacol. Sci. 35, 63–75. doi: 10.1016/j.tips.2013.12.002,

PubMed Abstract | Crossref Full Text | Google Scholar

Kataoka, M., Niikawa, T., Nagaishi, N., Lee, T. L., Erler, A., Savulescu, J., et al. (2025). Beyond consciousness: ethical, legal, and social issues in human brain organoid research and application. Eur. J. Cell Biol. 104:151470. doi: 10.1016/j.ejcb.2024.151470,

PubMed Abstract | Crossref Full Text | Google Scholar

Kavlock, R. J., Austin, C. P., and Tice, R. R. (2009). Toxicity testing in the 21st century: implications for human health risk assessment. Risk Anal. 29, 485–487. doi: 10.1111/j.1539-6924.2008.01168.x

Crossref Full Text | Google Scholar

Kawakita, S., Mandal, K., Mou, L., Mecwan, M. M., Zhu, Y., Li, S., et al. (2022). Organ-on-A-Chip models of the blood-brain barrier: recent advances and future prospects. Small 18:e2201401. doi: 10.1002/smll.202201401,

PubMed Abstract | Crossref Full Text | Google Scholar

Kelley, K. W., and Pasca, S. P. (2022). Human brain organogenesis: toward a cellular understanding of development and disease. Cell 185, 42–61. doi: 10.1016/j.cell.2021.10.003,

PubMed Abstract | Crossref Full Text | Google Scholar

Kily, L. J., Cowe, Y. C., Hussain, O., Patel, S., McElwaine, S., Cotter, F. E., et al. (2008). Gene expression changes in a zebrafish model of drug dependency suggest conservation of neuro-adaptation pathways. J. Exp. Biol. 211, 1623–1634. doi: 10.1242/jeb.014399,

PubMed Abstract | Crossref Full Text | Google Scholar

Kim, J., Koo, B. K., and Knoblich, J. A. (2020). Human organoids: model systems for human biology and medicine. Nat. Rev. Mol. Cell Biol. 21, 571–584. doi: 10.1038/s41580-020-0259-3,

PubMed Abstract | Crossref Full Text | Google Scholar

Kim, J., Lengner, C. J., Kirak, O., Hanna, J., Cassady, J. P., Lodato, M. A., et al. (2011). Reprogramming of postnatal neurons into induced pluripotent stem cells by defined factors. Stem Cells 29, 992–1000. doi: 10.1002/stem.641,

PubMed Abstract | Crossref Full Text | Google Scholar

Kim, C. H., Ueshima, E., Muraoka, O., Tanaka, H., Yeo, S. Y., Huh, T. L., et al. (1996). Zebrafish elav/HuC homologue as a very early neuronal marker. Neurosci. Lett. 216, 109–112. doi: 10.1016/0304-3940(96)13021-4,

PubMed Abstract | Crossref Full Text | Google Scholar

Kimmel, C. B., Ballard, W. W., Kimmel, S. R., Ullmann, B., and Schilling, T. F. (1995). Stages of embryonic development of the zebrafish. Dev. Dyn. 203, 253–310. doi: 10.1002/aja.1002030302,

PubMed Abstract | Crossref Full Text | Google Scholar

Klein, C., and Westenberger, A. (2012). Genetics of Parkinson's disease. Cold Spring Harb. Perspect. Med. 2:a008888. doi: 10.1101/cshperspect.a008888,

PubMed Abstract | Crossref Full Text | Google Scholar

Krencik, R., Weick, J. P., Liu, Y., Zhang, Z. J., and Zhang, S. C. (2011). Specification of transplantable astroglial subtypes from human pluripotent stem cells. Nat. Biotechnol. 29, 528–534. doi: 10.1038/nbt.1877,

PubMed Abstract | Crossref Full Text | Google Scholar

Krewski, D., Acosta, D., Andersen, M., Anderson, H., Bailar, J. C., Boekelheide, K., et al. (2010). Toxicity testing in the 21st century: a vision and a strategy. J. Toxicol. Environ. Health B Crit. Rev. 13, 51–138. doi: 10.1080/10937404.2010.483176

Crossref Full Text | Google Scholar

Krienen, F. M., Goldman, M., Zhang, Q., Chdr, R., Florio, M., Machold, R., et al. (2020). Innovations present in the primate interneuron repertoire. Nature 586, 262–269. doi: 10.1038/s41586-020-2781-z

Crossref Full Text | Google Scholar

Kriks, S., Shim, J. W., Piao, J., Ganat, Y. M., Wakeman, D. R., Xie, Z., et al. (2011). Dopamine neurons derived from human ES cells efficiently engraft in animal models of Parkinson's disease. Nature 480, 547–551. doi: 10.1038/nature10648,

PubMed Abstract | Crossref Full Text | Google Scholar

Kroll, F., Powell, G. T., Ghosh, M., Gestri, G., Antinucci, P., Hearn, T. J., et al. (2021). A simple and effective F0 knockout method for rapid screening of behaviour and other complex phenotypes. eLife 10:10. doi: 10.7554/eLife.59683,

PubMed Abstract | Crossref Full Text | Google Scholar

Kuwahara, A., Ozone, C., Nakano, T., Saito, K., Eiraku, M., and Sasai, Y. (2015). Generation of a ciliary margin-like stem cell niche from self-organizing human retinal tissue. Nat. Commun. 6:6286. doi: 10.1038/ncomms7286,

PubMed Abstract | Crossref Full Text | Google Scholar

Lancaster, M. A., and Knoblich, J. A. (2014). Organogenesis in a dish: modeling development and disease using organoid technologies. Science 345:1247125. doi: 10.1126/science.1247125,

PubMed Abstract | Crossref Full Text | Google Scholar

Lancaster, M. A., Renner, M., Martin, C. A., Wenzel, D., Bicknell, L. S., Hurles, M. E., et al. (2013). Cerebral organoids model human brain development and microcephaly. Nature 501, 373–379. doi: 10.1038/nature12517,

PubMed Abstract | Crossref Full Text | Google Scholar

Landry, C. R., Yip, M. C., Zhou, Y., Niu, W., Wang, Y., Yang, B., et al. (2023). Electrophysiological and morphological characterization of single neurons in intact human brain organoids. J. Neurosci. Methods 394:109898. doi: 10.1016/j.jneumeth.2023.109898,

PubMed Abstract | Crossref Full Text | Google Scholar

Langhans, S. A. (2018). Three-dimensional in vitro cell culture models in drug discovery and drug repositioning. Front. Pharmacol. 9:6. doi: 10.3389/fphar.2018.00006,

PubMed Abstract | Crossref Full Text | Google Scholar

Langlieb, J., Sachdev, N. S., Balderrama, K. S., Nadaf, N. M., Raj, M., Murray, E., et al. (2023). The molecular cytoarchitecture of the adult mouse brain. Nature 624, 333–342. doi: 10.1038/s41586-023-06818-7,

PubMed Abstract | Crossref Full Text | Google Scholar

Lavado, G. J., Gadaleta, D., Toma, C., Golbamaki, A., Toropov, A. A., Toropova, A. P., et al. (2020). Zebrafish AC(50) modelling: (Q)Sar models to predict developmental toxicity in zebrafish embryo. Ecotoxicol. Environ. Saf. 202:110936. doi: 10.1016/j.ecoenv.2020.110936,

PubMed Abstract | Crossref Full Text | Google Scholar

Lee, J., Sutani, A., Kaneko, R., Takeuchi, J., Sasano, T., Kohda, T., et al. (2020). In vitro generation of functional murine heart organoids via FGF4 and extracellular matrix. Nat. Commun. 11:4283. doi: 10.1038/s41467-020-18031-5,

PubMed Abstract | Crossref Full Text | Google Scholar

Leekitratanapisan, W., Pardon, M., de Witte, P., Ny, A., Chapel, S., Cabooter, D., et al. (2025). Effect based monitoring of emerging organic micropollutant mixtures in conventional wastewater treatment plant effluents in Flanders, Belgium. Integr. Environ. Assess. Manag., (Online ahead of print). doi: 10.1093/inteam/vjaf166

Crossref Full Text | Google Scholar

Lei, T., Zhang, X., Fu, G., Luo, S., Zhao, Z., Deng, S., et al. (2024). Advances in human cellular mechanistic understanding and drug discovery of brain organoids for neurodegenerative diseases. Ageing Res. Rev. 102:102517. doi: 10.1016/j.arr.2024.102517,

PubMed Abstract | Crossref Full Text | Google Scholar

Li, Y., Muffat, J., Omer, A., Bosch, I., Lancaster, M. A., Sur, M., et al. (2017). Induction of expansion and folding in human cerebral organoids. Cell Stem Cell 20, 385–396.e3. doi: 10.1016/j.stem.2016.11.017,

PubMed Abstract | Crossref Full Text | Google Scholar

Linaro, D., Vermaercke, B., Iwata, R., Ramaswamy, A., Libe-Philippot, B., Boubakar, L., et al. (2019). Xenotransplanted human cortical neurons reveal species-specific development and functional integration into mouse visual circuits. Neuron 104, 972–986.e6. doi: 10.1016/j.neuron.2019.10.002,

PubMed Abstract | Crossref Full Text | Google Scholar

Lloyd-Davies Sánchez, D. J., Lindhout, F. W., Anderson, A. J., Pellegrini, L., and Lancaster, M. A. (2024:2024.12.21.629881). Mouse brain organoids model in vivo neurodevelopment and function and capture differences to human. bioRxiv, 12.21.629881. doi: 10.1101/2024.12.21.629881

Crossref Full Text | Google Scholar

Loosli, F., Staub, W., Finger-Baier, K. C., Ober, E. A., Verkade, H., Wittbrodt, J., et al. (2003). Loss of eyes in zebrafish caused by mutation of chokh/rx3. EMBO Rep. 4, 894–899. doi: 10.1038/sj.embor.embor919,

PubMed Abstract | Crossref Full Text | Google Scholar

Lovric, M., Malev, O., Klobucar, G., Kern, R., Liu, J. J., and Lucic, B. (2021). Predictive capability of QSAR models based on the CompTox zebrafish embryo assays: An imbalanced classification problem. Molecules 26:1617. doi: 10.3390/molecules26061617,

PubMed Abstract | Crossref Full Text | Google Scholar

Lowry, W. E., Richter, L., Yachechko, R., Pyle, A. D., Tchieu, J., Sridharan, R., et al. (2008). Generation of human induced pluripotent stem cells from dermal fibroblasts. Proc. Natl. Acad. Sci. USA 105:2883. doi: 10.1073/pnas.0711983105,

PubMed Abstract | Crossref Full Text | Google Scholar

Ma, C., Fan, L., Ganassin, R., Bols, N., and Collodi, P. (2001). Production of zebrafish germ-line chimeras from embryo cell cultures. Proc. Natl. Acad. Sci. USA 98, 2461–2466. doi: 10.1073/pnas.041449398,

PubMed Abstract | Crossref Full Text | Google Scholar

MacRae, C. A., and Peterson, R. T. (2015). Zebrafish as tools for drug discovery. Nat. Rev. Drug Discov. 14, 721–731. doi: 10.1038/nrd4627,

PubMed Abstract | Crossref Full Text | Google Scholar

Maisumu, G., Willerth, S., Nestor, M., Waldau, B., Schulke, S., Nardi, F. V., et al. (2025). Brain organoids: building higher-order complexity and neural circuitry models. Trends Biotechnol. 43, 1583–1598. doi: 10.1016/j.tibtech.2025.02.009,

PubMed Abstract | Crossref Full Text | Google Scholar

Mancuso, R., Fattorelli, N., Martinez-Muriana, A., Davis, E., Wolfs, L., Van Den Daele, J., et al. (2024). Xenografted human microglia display diverse transcriptomic states in response to Alzheimer's disease-related amyloid-beta pathology. Nat. Neurosci. 27, 886–900. doi: 10.1038/s41593-024-01600-y,

PubMed Abstract | Crossref Full Text | Google Scholar

Mansour, A. A., Goncalves, J. T., Bloyd, C. W., Li, H., Fernandes, S., Quang, D., et al. (2018). An in vivo model of functional and vascularized human brain organoids. Nat. Biotechnol. 36, 432–441. doi: 10.1038/nbt.4127,

PubMed Abstract | Crossref Full Text | Google Scholar

Marshall, J. J., and Mason, J. O. (2019). Mouse vs man: organoid models of brain development & disease. Brain Res. 1724:146427. doi: 10.1016/j.brainres.2019.146427,

PubMed Abstract | Crossref Full Text | Google Scholar

Matsui, T., and Shinozawa, T. (2021). Human organoids for predictive toxicology research and drug development. Front. Genet. 12:767621. doi: 10.3389/fgene.2021.767621,

PubMed Abstract | Crossref Full Text | Google Scholar

Medina-Cano, D., Corrigan, E. K., Glenn, R. A., Islam, M. T., Lin, Y., Kim, J., et al. (2022). Rapid and robust directed differentiation of mouse epiblast stem cells into definitive endoderm and forebrain organoids. Development 149:dev200561. doi: 10.1242/dev.200561,

PubMed Abstract | Crossref Full Text | Google Scholar

Medina-Cano, D., Islam, M. T., Petrova, V., Dixit, S., Balic, Z., Yang, M. G., et al. (2025). A mouse organoid platform for modeling cerebral cortex development and cis-regulatory evolution in vitro. Dev. Cell. doi: 10.1016/j.devcel.2025.08.001,

PubMed Abstract | Crossref Full Text | Google Scholar

Mehta, K., Maass, C., Cucurull-Sanchez, L., Pichardo-Almarza, C., Subramanian, K., Androulakis, I. P., et al. (2025). Modernizing preclinical drug development: the role of new approach methodologies. ACS Pharmacol Transl Sci. 8, 1513–1525. doi: 10.1021/acsptsci.5c00162,

PubMed Abstract | Crossref Full Text | Google Scholar

Miccoli, B., Braeken, D., and Li, Y. E. (2018). Brain-on-a-chip devices for drug screening and disease modeling applications. Curr. Pharm. Des. 24, 5419–5436. doi: 10.2174/1381612825666190220161254,

PubMed Abstract | Crossref Full Text | Google Scholar

Mina, S. G., Alaybeyoglu, B., Murphy, W. L., Thomson, J. A., Stokes, C. L., and Cirit, M. (2019). Assessment of drug-induced toxicity biomarkers in the brain microphysiological system (MPS) using targeted and untargeted molecular profiling. Front Big Data 2:23. doi: 10.3389/fdata.2019.00023,

PubMed Abstract | Crossref Full Text | Google Scholar

Moris, N., Anlas, K., van den Brink, S. C., Alemany, A., Schroder, J., Ghimire, S., et al. (2020). An in vitro model of early anteroposterior organization during human development. Nature 582, 410–415. doi: 10.1038/s41586-020-2383-9,

PubMed Abstract | Crossref Full Text | Google Scholar

Mossink, B., van Rhijn, J. R., Wang, S., Linda, K., Vitale, M. R., Zoller, J. E. M., et al. (2022). Cadherin-13 is a critical regulator of GABAergic modulation in human stem-cell-derived neuronal networks. Mol. Psychiatry 27, 1–18. doi: 10.1038/s41380-021-01117-x,

PubMed Abstract | Crossref Full Text | Google Scholar

Mueller, T., and Wullimann, M. F. (2003). Anatomy of neurogenesis in the early zebrafish brain. Brain Res. Dev. Brain Res. 140, 137–155. doi: 10.1016/s0165-3806(02)00583-7,

PubMed Abstract | Crossref Full Text | Google Scholar

Mueller, T., and Wullimann, M. F. (2009). An evolutionary interpretation of teleostean forebrain anatomy. Brain Behav. Evol. 74, 30–42. doi: 10.1159/000229011,

PubMed Abstract | Crossref Full Text | Google Scholar

Murphy-Royal, C., Johnston, A. D., Boyce, A. K. J., Diaz-Castro, B., Institoris, A., Peringod, G., et al. (2020). Stress gates an astrocytic energy reservoir to impair synaptic plasticity. Nat. Commun. 11:2014. doi: 10.1038/s41467-020-15778-9,

PubMed Abstract | Crossref Full Text | Google Scholar

Nakano, T., Ando, S., Takata, N., Kawada, M., Muguruma, K., Sekiguchi, K., et al. (2012). Self-formation of optic cups and storable stratified neural retina from human ESCs. Cell Stem Cell 10, 771–785. doi: 10.1016/j.stem.2012.05.009,

PubMed Abstract | Crossref Full Text | Google Scholar

National Academies of Sciences, Engineering, and Medicine. (2023). Building confidence in new evidence streams for human health risk assessment: Lessons learned from laboratory mammalian toxicity tests. Washington, DC: The National Academies Press.

Google Scholar

Nishimura, Y., Inoue, A., Sasagawa, S., Koiwa, J., Kawaguchi, K., Kawase, R., et al. (2016). Using zebrafish in systems toxicology for developmental toxicity testing. Congenit. Anom. 56, 18–27. doi: 10.1111/cga.12142,

PubMed Abstract | Crossref Full Text | Google Scholar

Nzou, G., Wicks, R. T., Wicks, E. E., Seale, S. A., Sane, C. H., Chen, A., et al. (2018). Human cortex spheroid with a functional blood brain barrier for high-throughput neurotoxicity screening and disease Modeling. Sci. Rep. 8:7413. doi: 10.1038/s41598-018-25603-5,

PubMed Abstract | Crossref Full Text | Google Scholar

OECD (2018). Guidance document on Good in vitro method practices (GIVIMP), OECD series on testing and assessment, no. 286. Paris: OECD publishing.

Google Scholar

OECD. Report on considerations from CASE studies on integrated approaches for testing and assessment (IATA). Environment directorate chemicals and biotechnology committee; (2022). Available online at: https://one.oecd.org/document/ENV/CBC/MONO(2022)36

Google Scholar

Oliva, M. K., Bourke, J., Kornienko, D., Mattei, C., Mao, M., Kuanyshbek, A., et al. (2024). Standardizing a method for functional assessment of neural networks in brain organoids. J. Neurosci. Methods 409:110178. doi: 10.1016/j.jneumeth.2024.110178,

PubMed Abstract | Crossref Full Text | Google Scholar

Onishi, K., and Shimogori, T. (2025). Cell type census in cerebral cortex reveals species-specific brain function and connectivity. Neurosci. Res. 214, 42–47. doi: 10.1016/j.neures.2024.11.008,

PubMed Abstract | Crossref Full Text | Google Scholar

Ormel, P. R., Vieira de Sa, R., van Bodegraven, E. J., Karst, H., Harschnitz, O., Sneeboer, M. A. M., et al. (2018). Microglia innately develop within cerebral organoids. Nat. Commun. 9:4167. doi: 10.1038/s41467-018-06684-2,

PubMed Abstract | Crossref Full Text | Google Scholar

Padilla, S., Corum, D., Padnos, B., Hunter, D. L., Beam, A., Houck, K. A., et al. (2012). Zebrafish developmental screening of the ToxCast phase I chemical library. Reprod. Toxicol. 33, 174–187. doi: 10.1016/j.reprotox.2011.10.018,

PubMed Abstract | Crossref Full Text | Google Scholar

Pallocca, G., Mone, M. J., Kamp, H., Luijten, M., Van de Water, B., and Leist, M. (2022). Next-generation risk assessment of chemicals—rolling out a human-centric testing strategy to drive 3R implementation: the RISK-HUNT3R project perspective. ALTEX 39, 419–426. doi: 10.14573/altex.2204051

Crossref Full Text | Google Scholar

Pang, M., Liu, X., Zhi, H., Huijie, Y., Kuo, Z., and Xiaoli, G. (2025). “Application of the zebrafish model in neurobiological research” in Zebrafish model in medical research. ed. G. R. Disner (London: IntechOpen).

Google Scholar

Parish, S. T., Aschner, M., Casey, W., Corvaro, M., Embry, M. R., Fitzpatrick, S., et al. (2020). An evaluation framework for new approach methodologies (NAMs) for human health safety assessment. Regul. Toxicol. Pharmacol. 112:104592. doi: 10.1016/j.yrtph.2020.104592,

PubMed Abstract | Crossref Full Text | Google Scholar

Park, H. C., Kim, C. H., Bae, Y. K., Yeo, S. Y., Kim, S. H., Hong, S. K., et al. (2000). Analysis of upstream elements in the HuC promoter leads to the establishment of transgenic zebrafish with fluorescent neurons. Dev. Biol. 227, 279–293. doi: 10.1006/dbio.2000.9898,

PubMed Abstract | Crossref Full Text | Google Scholar

Pasca, A. M., Sloan, S. A., Clarke, L. E., Tian, Y., Makinson, C. D., Huber, N., et al. (2015). Functional cortical neurons and astrocytes from human pluripotent stem cells in 3D culture. Nat. Methods 12, 671–678. doi: 10.1038/nmeth.3415,

PubMed Abstract | Crossref Full Text | Google Scholar

Patel, B. B., Clark, K. L., Kozik, E. M., Dash, L., Kuhlman, J. A., and Sakaguchi, D. S. (2019). Isolation and culture of primary embryonic zebrafish neural tissue. J. Neurosci. Methods 328:108419. doi: 10.1016/j.jneumeth.2019.108419,

PubMed Abstract | Crossref Full Text | Google Scholar

Patton, E. E., Zon, L. I., and Langenau, D. M. (2021). Zebrafish disease models in drug discovery: from preclinical modelling to clinical trials. Nat. Rev. Drug Discov. 20, 611–628. doi: 10.1038/s41573-021-00210-8,

PubMed Abstract | Crossref Full Text | Google Scholar

Peng, Y., Chu, S., Yang, Y., Zhang, Z., Pang, Z., and Chen, N. (2021). Neuroinflammatory in vitro cell culture models and the potential applications for neurological disorders. Front. Pharmacol. 12:671734. doi: 10.3389/fphar.2021.671734,

PubMed Abstract | Crossref Full Text | Google Scholar

Pevny, L., and Placzek, M. (2005). SOX genes and neural progenitor identity. Curr. Opin. Neurobiol. 15, 7–13. doi: 10.1016/j.conb.2005.01.016,

PubMed Abstract | Crossref Full Text | Google Scholar

Pognan, F., Beilmann, M., Boonen, H. C. M., Czich, A., Dear, G., Hewitt, P., et al. (2023). The evolving role of investigative toxicology in the pharmaceutical industry. Nat. Rev. Drug Discov. 22, 317–335. doi: 10.1038/s41573-022-00633-x,

PubMed Abstract | Crossref Full Text | Google Scholar

Pollen, A. A., Nowakowski, T. J., Shuga, J., Wang, X., Leyrat, A. A., Lui, J. H., et al. (2014). Low-coverage single-cell mRNA sequencing reveals cellular heterogeneity and activated signaling pathways in developing cerebral cortex. Nat. Biotechnol. 32, 1053–1058. doi: 10.1038/nbt.2967,

PubMed Abstract | Crossref Full Text | Google Scholar

Punt, A., Bouwmeester, H., Blaauboer, B. J., Coecke, S., Hakkert, B., Hendriks, D. F. G., et al. (2020). New approach methodologies (NAMs) for human-relevant biokinetics predictions. Meeting the paradigm shift in toxicology towards an animal-free chemical risk assessment. ALTEX 37, 607–622. doi: 10.14573/altex.2003242,

PubMed Abstract | Crossref Full Text | Google Scholar

Qian, X., Song, H., and Ming, G. L. (2019). Brain organoids: advances, applications and challenges. Development 146:dev166074. doi: 10.1242/dev.166074,

PubMed Abstract | Crossref Full Text | Google Scholar

Qu, L., Liu, F., Fang, Y., Wang, L., Chen, H., Yang, Q., et al. (2023). Improvement in zebrafish with diabetes and Alzheimer's disease treated with pasteurized Akkermansia muciniphila. Microbiol Spectr. 11:e0084923. doi: 10.1128/spectrum.00849-23,

PubMed Abstract | Crossref Full Text | Google Scholar

Revah, O., Gore, F., Kelley, K. W., Andersen, J., Sakai, N., Chen, X., et al. (2022). Maturation and circuit integration of transplanted human cortical organoids. Nature 610, 319–326. doi: 10.1038/s41586-022-05277-w,

PubMed Abstract | Crossref Full Text | Google Scholar

Robertson, A. S., Latif, N., Bousnina, I., Boyce, D., Carl, K., Curtis, S. P., et al. (2025). Accelerating adoption of new approach methodologies in regulatory decision making: an industry perspective. Nat. Rev. Drug Discov. 24, 401–402. doi: 10.1038/d41573-025-00038-6,

PubMed Abstract | Crossref Full Text | Google Scholar

Robles, V., Marti, M., and Izpisua Belmonte, J. C. (2011). Study of pluripotency markers in zebrafish embryos and transient embryonic stem cell cultures. Zebrafish 8, 57–63. doi: 10.1089/zeb.2010.0684,

PubMed Abstract | Crossref Full Text | Google Scholar

Rosa, J. G. S., Lima, C., and Lopes-Ferreira, M. (2022). Zebrafish larvae behavior models as a tool for drug screenings and pre-clinical trials: a review. Int. J. Mol. Sci. 23:6647. doi: 10.3390/ijms23126647,

PubMed Abstract | Crossref Full Text | Google Scholar

Roybon, L., Lamas, N. J., Garcia, A. D., Yang, E. J., Sattler, R., Lewis, V. J., et al. (2013). Human stem cell-derived spinal cord astrocytes with defined mature or reactive phenotypes. Cell Rep. 4, 1035–1048. doi: 10.1016/j.celrep.2013.06.021,

PubMed Abstract | Crossref Full Text | Google Scholar

Saavedra, L. M., and Duchowicz, P. R. (2021). Predicting zebrafish (Danio rerio) embryo developmental toxicity through a non-conformational QSAR approach. Sci. Total Environ. 796:148820. doi: 10.1016/j.scitotenv.2021.148820,

PubMed Abstract | Crossref Full Text | Google Scholar

Sabate-Soler, S., Nickels, S. L., Saraiva, C., Berger, E., Dubonyte, U., Barmpa, K., et al. (2022). Microglia integration into human midbrain organoids leads to increased neuronal maturation and functionality. Glia 70, 1267–1288. doi: 10.1002/glia.24167,

PubMed Abstract | Crossref Full Text | Google Scholar

Sahin, M., Oncu, G., Yilmaz, M. A., Ozkan, D., and Saybasili, H. (2021). Transformation of SH-SY5Y cell line into neuron-like cells: investigation of electrophysiological and biomechanical changes. Neurosci. Lett. 745:135628. doi: 10.1016/j.neulet.2021.135628,

PubMed Abstract | Crossref Full Text | Google Scholar

Sakuratani, Y., Horie, M., and Leinala, E. (2018). Integrated approaches to testing and assessment: OECD activities on the development and use of adverse outcome pathways and case studies. Basic Clin. Pharmacol. Toxicol. 123, 20–28. doi: 10.1111/bcpt.12955,

PubMed Abstract | Crossref Full Text | Google Scholar

Samarasinghe, R. A., Miranda, O. A., Buth, J. E., Mitchell, S., Ferando, I., Watanabe, M., et al. (2021). Identification of neural oscillations and epileptiform changes in human brain organoids. Nat. Neurosci. 24, 1488–1500. doi: 10.1038/s41593-021-00906-5,

PubMed Abstract | Crossref Full Text | Google Scholar

Schauer, A., Pinheiro, D., Hauschild, R., and Heisenberg, C. P. (2020). Zebrafish embryonic explants undergo genetically encoded self-assembly. eLife 9:9. doi: 10.7554/eLife.55190,

PubMed Abstract | Crossref Full Text | Google Scholar

Schmeisser, S., Miccoli, A., von Bergen, M., Berggren, E., Braeuning, A., Busch, W., et al. (2023). New approach methodologies in human regulatory toxicology—not if, but how and when! Environ. Int. 178:108082. doi: 10.1016/j.envint.2023.108082,

PubMed Abstract | Crossref Full Text | Google Scholar

Schneider, M. R., Oelgeschlaeger, M., Burgdorf, T., van Meer, P., Theunissen, P., Kienhuis, A. S., et al. (2021). Applicability of organ-on-chip systems in toxicology and pharmacology. Crit. Rev. Toxicol. 51, 540–554. doi: 10.1080/10408444.2021.1953439,

PubMed Abstract | Crossref Full Text | Google Scholar

Seeger, T., Porteus, M., and Wu, J. C. (2017). Genome editing in cardiovascular biology. Circ. Res. 120, 778–780. doi: 10.1161/CIRCRESAHA.116.310197,

PubMed Abstract | Crossref Full Text | Google Scholar

Segev, A., Garcia-Oscos, F., and Kourrich, S. (2016). Whole-cell patch-clamp recordings in brain slices. J. Vis. Exp. 112:54024. doi: 10.3791/54024,

PubMed Abstract | Crossref Full Text | Google Scholar

Shao, R., Liao, X., Wang, W., Lan, Y., Zhang, H., Du, Q., et al. (2024). Vitamin D regulates glucose metabolism in zebrafish (Danio rerio) by maintaining intestinal homeostasis. J. Nutr. Biochem. 123:109473. doi: 10.1016/j.jnutbio.2023.109473,

PubMed Abstract | Crossref Full Text | Google Scholar

Shi, Y., Sun, L., Wang, M., Liu, J., Zhong, S., Li, R., et al. (2020). Vascularized human cortical organoids (vOrganoids) model cortical development in vivo. PLoS Biol. 18:e3000705. doi: 10.1371/journal.pbio.3000705,

PubMed Abstract | Crossref Full Text | Google Scholar

Simeone, A., Acampora, D., Mallamaci, A., Stornaiuolo, A., D'Apice, M. R., Nigro, V., et al. (1993). A vertebrate gene related to orthodenticle contains a homeodomain of the bicoid class and demarcates anterior neuroectoderm in the gastrulating mouse embryo. EMBO J. 12, 2735–2747. doi: 10.1002/j.1460-2075.1993.tb05935.x,

PubMed Abstract | Crossref Full Text | Google Scholar

Simkin, D., Ambrosi, C., Marshall, K. A., Williams, L. A., Eisenberg, J., Gharib, M., et al. (2022). 'Channeling' therapeutic discovery for epileptic encephalopathy through iPSC technologies. Trends Pharmacol. Sci. 43, 392–405. doi: 10.1016/j.tips.2022.03.001,

PubMed Abstract | Crossref Full Text | Google Scholar

Sipes, N. S., Padilla, S., and Knudsen, T. B. (2011). Zebrafish: as an integrative model for twenty-first century toxicity testing. Birth Defects Res. C Embryo Today 93, 256–267. doi: 10.1002/bdrc.20214,

PubMed Abstract | Crossref Full Text | Google Scholar

Sit, T. P. H., Feord, R. C., Dunn, A. W. E., Chabros, J., Oluigbo, D., Smith, H. H., et al. (2024). MEA-NAP: a flexible network analysis pipeline for neuronal 2D and 3D organoid multielectrode recordings. Cell Rep. Methods 4:100901. doi: 10.1016/j.crmeth.2024.100901,

PubMed Abstract | Crossref Full Text | Google Scholar

Sivandzade, F., and Cucullo, L. (2018). In-vitro blood-brain barrier modeling: a review of modern and fast-advancing technologies. J. Cereb. Blood Flow Metab. 38, 1667–1681. doi: 10.1177/0271678X18788769,

PubMed Abstract | Crossref Full Text | Google Scholar

Sloan, S. A., Darmanis, S., Huber, N., Khan, T. A., Birey, F., Caneda, C., et al. (2017). Human astrocyte maturation captured in 3D cerebral cortical spheroids derived from pluripotent stem cells. Neuron 95, 779–790.e6. doi: 10.1016/j.neuron.2017.07.035,

PubMed Abstract | Crossref Full Text | Google Scholar

Sourbron, J., Smolders, I., de Witte, P., and Lagae, L. (2017). Pharmacological analysis of the anti-epileptic mechanisms of fenfluramine in scn1a mutant zebrafish. Front. Pharmacol. 8:191. doi: 10.3389/fphar.2017.00191,

PubMed Abstract | Crossref Full Text | Google Scholar

Sousa, A. M. M., Meyer, K. A., Santpere, G., Gulden, F. O., and Sestan, N. (2017). Evolution of the human nervous system function, structure, and development. Cell 170, 226–247. doi: 10.1016/j.cell.2017.06.036,

PubMed Abstract | Crossref Full Text | Google Scholar

Strahle, U., Scholz, S., Geisler, R., Greiner, P., Hollert, H., Rastegar, S., et al. (2012). Zebrafish embryos as an alternative to animal experiments--a commentary on the definition of the onset of protected life stages in animal welfare regulations. Reprod. Toxicol. 33, 128–132. doi: 10.1016/j.reprotox.2011.06.121,

PubMed Abstract | Crossref Full Text | Google Scholar

Sun, L., Bradford, C. S., Ghosh, C., Collodi, P., and Barnes, D. W. (1995). ES-like cell cultures derived from early zebrafish embryos. Mol. Mar. Biol. Biotechnol. 4, 193–199.

Google Scholar

Sun, D., Gao, W., Hu, H., and Zhou, S. (2022). Why 90% of clinical drug development fails and how to improve it? Acta Pharm. Sin. B 12, 3049–3062. doi: 10.1016/j.apsb.2022.02.002,

PubMed Abstract | Crossref Full Text | Google Scholar

Sun, D., Wu, B., Yue, J., Zeng, G., Chen, R., and Chen, J. (2025). From particle size to brain function: a zebrafish-based review of micro/nanoplastic-induced neurobehavioral toxicity and mechanistic pathways. Environ. Sci. Nano 12, 4197–4210. doi: 10.1039/D5EN00469A,

PubMed Abstract | Crossref Full Text | Google Scholar

Syvanen, S., Lindhe, O., Palner, M., Kornum, B. R., Rahman, O., Langstrom, B., et al. (2009). Species differences in blood-brain barrier transport of three positron emission tomography radioligands with emphasis on P-glycoprotein transport. Drug Metab. Dispos. 37, 635–643. doi: 10.1124/dmd.108.024745,

PubMed Abstract | Crossref Full Text | Google Scholar

Taguchi, A., and Nishinakamura, R. (2017). Higher-Order Kidney Organogenesis from Pluripotent Stem Cells. Cell Stem Cell 21, 730–746.e6. doi: 10.1016/j.stem.2017.10.011,

PubMed Abstract | Crossref Full Text | Google Scholar

Takahashi, K., Tanabe, K., Ohnuki, M., Narita, M., Ichisaka, T., Tomoda, K., et al. (2007). Induction of pluripotent stem cells from adult human fibroblasts by defined factors. Cell 131, 861–872. doi: 10.1016/j.cell.2007.11.019,

PubMed Abstract | Crossref Full Text | Google Scholar

Takahashi, K., and Yamanaka, S. (2006). Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors. Cell 126, 663–676. doi: 10.1016/j.cell.2006.07.024,

PubMed Abstract | Crossref Full Text | Google Scholar

Tanaka, Y., Cakir, B., Xiang, Y., Sullivan, G. J., and Park, I. H. (2020). Synthetic analyses of single-cell transcriptomes from multiple brain organoids and Fetal brain. Cell Rep. 30, 1682–1689.e3. doi: 10.1016/j.celrep.2020.01.038,

PubMed Abstract | Crossref Full Text | Google Scholar

Tang, H., Li, J., Li, J. K., He, S. H., Xiang, G., Rong, R., et al. (2023). BMP6 participates in the pathogenesis of adolescent idiopathic scoliosis by regulating osteopenia. J. Cell. Physiol. 238, 2586–2599. doi: 10.1002/jcp.31111,

PubMed Abstract | Crossref Full Text | Google Scholar

Thevissen, K., Ny, A., Copmans, D., Tits, J., Kamata, K., Gielis, E., et al. (2025). Clioquinol as a new therapy in epilepsy: from preclinical evidence to a proof-of-concept clinical study. Epilepsia 66, 3769–3784. doi: 10.1111/epi.18536,

PubMed Abstract | Crossref Full Text | Google Scholar

Tian, E., Kimura, C., Takeda, N., Aizawa, S., and Matsuo, I. (2002). Otx2 is required to respond to signals from anterior neural ridge for forebrain specification. Dev. Biol. 242, 204–223. doi: 10.1006/dbio.2001.0531,

PubMed Abstract | Crossref Full Text | Google Scholar

Tiraboschi, E., Martina, S., van der Ent, W., Grzyb, K., Gawel, K., Cordero-Maldonado, M. L., et al. (2020). New insights into the early mechanisms of epileptogenesis in a zebrafish model of Dravet syndrome. Epilepsia 61, 549–560. doi: 10.1111/epi.16456,

PubMed Abstract | Crossref Full Text | Google Scholar

Tomasello, D. L., and Wlodkowic, D. (2022). Noninvasive electrophysiology: emerging prospects in aquatic neurotoxicity testing. Environ. Sci. Technol. 56, 4788–4794. doi: 10.1021/acs.est.1c08471,

PubMed Abstract | Crossref Full Text | Google Scholar

Trujillo, C. A., and Muotri, A. R. (2018). Brain organoids and the study of neurodevelopment. Trends Mol. Med. 24, 982–990. doi: 10.1016/j.molmed.2018.09.005,

PubMed Abstract | Crossref Full Text | Google Scholar

Turner, D. A., Girgin, M., Alonso-Crisostomo, L., Trivedi, V., Baillie-Johnson, P., Glodowski, C. R., et al. (2017). Anteroposterior polarity and elongation in the absence of extra-embryonic tissues and of spatially localised signalling in gastruloids: mammalian embryonic organoids. Development 144, 3894–3906. doi: 10.1242/dev.150391,

PubMed Abstract | Crossref Full Text | Google Scholar

Turner, J., Pound, P., Owen, C., Hutchinson, I., Hop, M., Chau, D. Y. S., et al. (2023). Incorporating new approach methodologies into regulatory nonclinical pharmaceutical safety assessment. ALTEX 40, 519–533. doi: 10.14573/altex.2212081,

PubMed Abstract | Crossref Full Text | Google Scholar

Uchida, Y., Tachikawa, M., Obuchi, W., Hoshi, Y., Tomioka, Y., Ohtsuki, S., et al. (2013). A study protocol for quantitative targeted absolute proteomics (QTAP) by LC-MS/MS: application for inter-strain differences in protein expression levels of transporters, receptors, claudin-5, and marker proteins at the blood-brain barrier in ddY, FVB, and C57BL/6J mice. Fluids Barriers CNS 10:21. doi: 10.1186/2045-8118-10-21,

PubMed Abstract | Crossref Full Text | Google Scholar

US Congress. (2021-2022). US. S.5002—117th congress: FDA modernization act 2.0. Available online at: https://www.congress.gov/bill/117th-congress/senate-bill/50022022.

Google Scholar

van den Brink, S. C., and van Oudenaarden, A. (2021). 3D gastruloids: a novel frontier in stem cell-based in vitro modeling of mammalian gastrulation. Trends Cell Biol. 31, 747–759. doi: 10.1016/j.tcb.2021.06.007,

PubMed Abstract | Crossref Full Text | Google Scholar

van Gerven, J., and Bonelli, M. (2018). Commentary on the EMA guideline on strategies to identify and mitigate risks for first-in-human and early clinical trials with investigational medicinal products. Br. J. Clin. Pharmacol. 84, 1401–1409. doi: 10.1111/bcp.13550,

PubMed Abstract | Crossref Full Text | Google Scholar

van Hugte, E. J. H., Lewerissa, E. I., Wu, K. M., Scheefhals, N., Parodi, G., van Voorst, T. W., et al. (2023). SCN1A-deficient excitatory neuronal networks display mutation-specific phenotypes. Brain 146, 5153–5167. doi: 10.1093/brain/awad245,

PubMed Abstract | Crossref Full Text | Google Scholar

Velasco, S., Kedaigle, A. J., Simmons, S. K., Nash, A., Rocha, M., Quadrato, G., et al. (2019). Individual brain organoids reproducibly form cell diversity of the human cerebral cortex. Nature 570, 523–527. doi: 10.1038/s41586-019-1289-x,

PubMed Abstract | Crossref Full Text | Google Scholar

Verkerke, M., Berdenis van Berlekom, A., Donega, V., Vonk, D., Sluijs, J. A., Butt, N. F., et al. (2024). Transcriptomic and morphological maturation of human astrocytes in cerebral organoids. Glia 72, 362–374. doi: 10.1002/glia.24479,

PubMed Abstract | Crossref Full Text | Google Scholar

Volpato, V., and Webber, C. (2020). Addressing variability in iPSC-derived models of human disease: guidelines to promote reproducibility. Dis. Model. Mech. 13:dmm042317. doi: 10.1242/dmm.042317,

PubMed Abstract | Crossref Full Text | Google Scholar

Wang, X., Kopec, A. K., Collinge, M., David, R., Grant, C., Hardwick, R. N., et al. (2022). Application of immunocompetent microphysiological systems in drug development: current perspective and recommendations. ALTEX 40, 314–336. doi: 10.14573/altex.2205311

Crossref Full Text | Google Scholar

Wegner, M., and Stolt, C. C. (2005). From stem cells to neurons and glia: a Soxist's view of neural development. Trends Neurosci. 28, 583–588. doi: 10.1016/j.tins.2005.08.008,

PubMed Abstract | Crossref Full Text | Google Scholar

Wester, P. W., van der Ven, L. T., and Vos, J. G. (2004). Comparative toxicological pathology in mammals and fish: some examples with endocrine disrupters. Toxicology 205, 27–32. doi: 10.1016/j.tox.2004.06.063,

PubMed Abstract | Crossref Full Text | Google Scholar

Wilson, M. N., Thunemann, M., Liu, X., Lu, Y., Puppo, F., Adams, J. W., et al. (2022). Multimodal monitoring of human cortical organoids implanted in mice reveal functional connection with visual cortex. Nat. Commun. 13:7945. doi: 10.1038/s41467-022-35536-3,

PubMed Abstract | Crossref Full Text | Google Scholar

Xiang, Y., Tanaka, Y., Patterson, B., Kang, Y. J., Govindaiah, G., Roselaar, N., et al. (2017). Fusion of regionally specified hPSC-derived organoids models human brain development and interneuron migration. Cell Stem Cell 21, 383–398.e7. doi: 10.1016/j.stem.2017.07.007,

PubMed Abstract | Crossref Full Text | Google Scholar

Xiao, Y., Gao, M., Gao, L., Zhao, Y., Hong, Q., Li, Z., et al. (2016). Directed differentiation of zebrafish pluripotent embryonic cells to functional cardiomyocytes. Stem Cell Reports. 7, 370–382. doi: 10.1016/j.stemcr.2016.07.020,

PubMed Abstract | Crossref Full Text | Google Scholar

Xing, J. G., Lee, L. E., Fan, L., Collodi, P., Holt, S. E., and Bols, N. C. (2008). Initiation of a zebrafish blastula cell line on rainbow trout stromal cells and subsequent development under feeder-free conditions into a cell line, ZEB2J. Zebrafish 5, 49–63. doi: 10.1089/zeb.2007.0512,

PubMed Abstract | Crossref Full Text | Google Scholar

Xu, M., Pan, D., Yi, J., Zheng, Y., Zeng, G., Lin, J., et al. (2025). Gut-brain axis dysfunction mediates neurotoxicity of embryonic p-phenylenediamine exposure in zebrafish. J. Hazard. Mater. 497:139650. doi: 10.1016/j.jhazmat.2025.139650,

PubMed Abstract | Crossref Full Text | Google Scholar

Yamamoto, S., Kanca, O., Wangler, M. F., and Bellen, H. J. (2024). Integrating non-mammalian model organisms in the diagnosis of rare genetic diseases in humans. Nat. Rev. Genet. 25, 46–60. doi: 10.1038/s41576-023-00633-6,

PubMed Abstract | Crossref Full Text | Google Scholar

Yi, M., Hong, N., and Hong, Y. (2010). Derivation and characterization of haploid embryonic stem cell cultures in medaka fish. Nat. Protoc. 5, 1418–1430. doi: 10.1038/nprot.2010.104,

PubMed Abstract | Crossref Full Text | Google Scholar

Yu, J., Vodyanik, M. A., Smuga-Otto, K., Antosiewicz-Bourget, J., Frane, J. L., Tian, S., et al. (2007). Induced pluripotent stem cell lines derived from human somatic cells. Science 318, 1917–1920. doi: 10.1126/science.1151526,

PubMed Abstract | Crossref Full Text | Google Scholar

Zhao, W., Chen, Y., Hu, N., Long, D., and Cao, Y. (2024). The uses of zebrafish (Danio rerio) as an in vivo model for toxicological studies: a review based on bibliometrics. Ecotoxicol. Environ. Saf. 272:116023. doi: 10.1016/j.ecoenv.2024.116023,

PubMed Abstract | Crossref Full Text | Google Scholar

Zilova, L., Weinhardt, V., Tavhelidse, T., Schlagheck, C., Thumberger, T., and Wittbrodt, J. (2021). Fish primary embryonic pluripotent cells assemble into retinal tissue mirroring in vivo early eye development. eLife 10:10. doi: 10.7554/eLife.66998,

PubMed Abstract | Crossref Full Text | Google Scholar

Zurlinden, T. J., Saili, K. S., Rush, N., Kothiya, P., Judson, R. S., Houck, K. A., et al. (2020). Profiling the ToxCast library with a pluripotent human (H9) stem cell line-based biomarker assay for developmental toxicity. Toxicol. Sci. 174, 189–209. doi: 10.1093/toxsci/kfaa014,

PubMed Abstract | Crossref Full Text | Google Scholar