Limitations of Animal Studies for Predicting Toxicity in Clinical Trials: Is it Time to Rethink Our Current Approach?

Animal models of neuropsychiatric systemic lupus erythematosus: deciphering the complexity and guiding therapeutic development

Systemic lupus erythematosus (SLE) poses formidable challenges due to its multifaceted etiology while impacting multiple tissues and organs and displaying diverse clinical manifestations. Genetic and environmental factors contribute to SLE complexity, with relatively limited approved therapeutic options. Murine models offer insights into SLE pathogenesis but do not always replicate the nuances of human disease. This review critically evaluates spontaneous and induced animal models, emphasizing their validity and relevance to neuropsychiatric SLE (NPSLE). While these models undoubtedly contribute to understanding disease pathophysiology, discrepancies persist in mimicking some NPSLE intricacies. The lack of literature addressing this issue impedes therapeutic progress. We underscore the urgent need for refining models that truly reflect NPSLE complexities to enhance translational fidelity. We encourage a comprehensive, creative translational approach for targeted SLE interventions, balancing scientific progress with ethical considerations to eventually improve the management of NPSLE patients. A thorough grasp of these issues informs researchers in designing experiments, interpreting results, and exploring alternatives to advance NPSLE research.

Occupational agents-mediated asthma: From the perspective of autophagy

Occupational asthma (OA) is a common occupational pulmonary disease that is frequently underdiagnosed and underreported. The complexity of diagnosing and treating OA creates a significant social and economic burden, making it an important public health issue. In addition to avoiding allergens, patients with OA require pharmacotherapy; however, new therapeutic targets and strategies need further investigation. Autophagy may be a promising intervention target, but there is a lack of relevant studies summarizing the role of autophagy in OA. In this review consolidates the current understanding of OA, detailing principal and novel agents responsible for its onset. Additionally, we summarize the mechanisms of autophagy in HMW and LMW agents induced OA, revealing that occupational allergens can induce autophagy disorders in lung epithelial cells, smooth muscle cells, and dendritic cells, ultimately leading to OA through involving inflammatory responses, oxidative stress, and cell death. Finally, we discuss the prospects of targeting autophagy as an effective strategy for managing OA and even steroid-resistant asthma, encompassing autophagy interventions focused on organoids, organ-on-a-chip systems, nanomaterials vehicle, and nanobubbles; developing combined exposure models, and the role of non-classical autophagy in occupational asthma. In briefly, this review summarizes the role of autophagy in occupational asthma, offers a theoretical foundation for OA interventions based on autophagy, and identifies directions and challenges for future research.

Toolbox for creating three-dimensional liver models

Research within the hepato-biliary system and hepatic function is currently experiencing heightened interest, this is due to the high frequency of relapse rates observed in chronic conditions, as well as the imperative for the development of innovative therapeutic strategies to address both inherited and acquired diseases within this domain. The most commonly used sources for studying hepatocytes include primary human hepatocytes, human hepatic cancer cell lines, and hepatic-like cells derived from induced pluripotent stem cells. However, a significant challenge in primary hepatic cell culture is the rapid decline in their phenotypic characteristics, dedifferentiation and short cultivation time. This limitation creates various problems, including the inability to maintain long-term cell cultures, which can lead to failed experiments in drug development and the creation of relevant disease models for researchers' purposes. To address these issues, the creation of a powerful 3D cell model could play a pivotal role as a personalized disease model and help reduce the use of animal models during certain stages of research. Such a cell model could be used for disease modelling, genome editing, and drug discovery purposes. This review provides an overview of the main methods of 3D-culturing liver cells, including a discussion of their characteristics, advantages, and disadvantages.

Establishment of human induced pluripotent stem cell-derived hepatobiliary organoid with bile duct for pharmaceutical research use

In vitro models of the human liver are promising alternatives to animal tests for drug development. Currently, primary human hepatocytes (PHHs) are preferred for pharmacokinetic and cytotoxicity tests. However, they are unable to recapitulate the flow of bile in hepatobiliary clearance owing to the lack of bile ducts, leading to the limitation of bile analysis. To address the issue, a liver organoid culture system that has a functional bile duct network is desired. In this study, we aimed to generate human iPSC-derived hepatobiliary organoids (hHBOs) consisting of hepatocytes and bile ducts. The two-step differentiation process under 2D and semi-3D culture conditions promoted the maturation of hHBOs on culture plates, in which hepatocyte clusters were covered with monolayered biliary tubes. We demonstrated that the hHBOs reproduced the flow of bile containing a fluorescent bile acid analog or medicinal drugs from hepatocytes into bile ducts via bile canaliculi. Furthermore, the hHBOs exhibited pathophysiological responses to troglitazone, such as cholestasis and cytotoxicity. Because the hHBOs can recapitulate the function of bile ducts in hepatobiliary clearance, they are suitable as a liver disease model and would be a novel in vitro platform system for pharmaceutical research use.

Laboratory and physiological aspects of substitute metazoan models for in vivo pharmacotoxicological analysis

New methods are essential to characterize the performance of substitute procedures for detecting therapeutic action(s) of a chemical or key signal of toxicological events. Herein, it was discussed the applications and advantages of using arthropods, worms, and fishes in pharmacological and/or toxicology assessments. First of all, the illusion of similarity covers many differences between humans and mice, remarkably about liver injury and metabolism of xenobiotics. Using invertebrates, especially earthworms (Eisenia fetida), brine shrimps (Artemia salina, Daphnia magna), and insects (Drosophila melanogaster) and vertebrates as small fishes (Oryzias latipes, Pimephales promelas, Danio rerio) has countless advantages, including fewer ethical conflicts, short life cycle, high reproduction rate, simpler to handle, and less complex anatomy. They can be used to find contaminants in organic matters and water and are easier genetically engineered with orthologous-mutated genes to explore specific proteins involved in proliferative and hormonal disturbances, chemotherapy multidrug resistance, and carcinogenicity. As multicellular embryos, larvae, and mature organisms, they can be tested in bigger-sized replication platforms with 24-, 96-, or 384-multiwell plates as cheaper and faster ways to select hit compounds from drug-like libraries to predict acute, subacute or chronic toxicity, pharmacokinetics, and efficacy parameters of pharmaceutical, cosmetic, and personal care products. Meanwhile, sublethal exposures are designed to identify changes in reproduction, body weight, DNA damages, oxidation, and immune defense responses in earthworms and zebrafishes, and swimming behaviors in A. salina and D. rerio. Behavioral parameters also give specificities on sublethal effects that would not be detected in zebrafishes by OECD protocols.

Exploration of organoids in ovarian cancer: From basic research to clinical translation

Ovarian cancer is a highly heterogeneous tumor with a poor prognosis. The lack of reliable and efficient research models that can accurately mimic heterogeneity has impeded in-depth investigations and hindered the clinical translation of research findings in ovarian cancer. Organoid models have emerged as a promising in vitro approach, demonstrating remarkable fidelity to the histological, molecular, genomic, and transcriptomic features of their tissues of origin. In recent years, organoids have contributed to advancing our understanding of ovarian cancer initiation, metastasis, and drug resistance mechanisms, as well as facilitating clinical screening of effective therapeutic agents. The establishment of high-throughput organoid culture systems, coupled with cutting-edge technologies such as organ-on-a-chip, genetic engineering, and 3D printing, has tremendous potential for accelerating ovarian cancer research translation. In this review, we present a comprehensive overview of the latest exploration of organoids in basic ovarian cancer research and clinical translation. Furthermore, we discuss the prospects and challenges associated with the use of organoids and related novel technologies in the context of ovarian cancer. This review provides insights into the application of organoids in ovarian cancer.

Status of animal experimentation in nutrition and dietetic research: Policies of 100 leading journals and new approach methodologies

Given animal research is challenged with inadequacies, e.g., animal-to-human knowledge translation, ethical considerations, and cost:benefit, new approach methodologies (NAMs) have been proposed as a replacement. With reference to the field of nutrition and dietetics, our aim was to examine the policies of its leading journals regarding human-based vs. traditional animal-based research; and to explore emerging NAMs that provide alternatives to animal experimentation. We reviewed 100 leading journals from an established database (SCImago Journal Rankings) in the nutrition and dietetics category for the year 2022. Eighty-three journals met the inclusion criteria. NAMs were extracted from a range of established sources. 9.6% (n = 8) of journals state they do not publish animal-based studies; 4.8% (n = 4) consider animal studies with qualifications, whereas the remaining 85.5% (n = 71) publish animal studies without qualification. Across sources, NAMs commonalities were identified including in vitro, in chemico, and in silico methods; and individual and population-based studies. Of leading nutrition/dietetic journals, relatively few have shifted to strictly non-animal methods. Greater attention to the increasing range of NAMs may not only reduce the need for animal research in the field, but may provide superior human-relevant outcomes. Studies are needed to establish their potential superiority.

Promising strategies in natural products treatments of psoriasis-update

Psoriasis is a chronic, relapsing, inflammatory skin disease and has been increasing year by year. It is linked to other serious illnesses, such as psoriatic arthritis, cardiometabolic syndrome, and depression, resulting in a notable decrease in the quality of life for patients. Existing therapies merely alleviate symptoms, rather than providing a cure. An in-depth under-standing of the pathogenesis of psoriasis is helpful to discover new therapeutic targets and develop effective novel therapeutic agents, so it has important clinical significance. This article reviews the new progress in the study of pathogenesis and natural products of psoriasis in recent years. These natural products were summarized, mainly classified as terpenoids, polyphenols and alkaloids. However, the translation of experimental results to the clinic takes a long way to go.

Targeting Death Receptor 5 (DR5) for imaging and treatment of primary bone and soft tissue tumors: an update of the literature

Background

Death Receptor 5 (DR5) is expressed on the surface of primary bone and soft tissue sarcoma cells, and its activation induces cell death primarily through apoptosis. The combination of DR5 agonists and commonly used chemotherapeutic agents, such as doxorubicin, can promote cell death. Currently, clinical trials are investigating the effectiveness of DR5 activation using new biological agents, such as bi-specific or tetravalent antibodies, in improving the survival of patients with relapsed or refractory cancers. Furthermore, investigations continue into the use of novel combination therapies to enhance DR5 response, for example, with inhibitor of apoptosis protein (IAP) antagonist agents [such as the second mitochondria-derived activator of caspase (SMAC) mimetics] and with immune checkpoint inhibitor anti-programmed death-ligand 1 (anti-PD-L1) or anti-programmed cell death-1 (anti-PD-1) antibodies. Other therapies include nanoparticle-mediated delivery of TRAIL plasmid DNA or TRAIL mRNA and stem cells as a vehicle for the targeted delivery of anti-cancer agents, such as TRAIL, to the tumor.

Methods

scoping review of the literature from November 2017 to March 2024, utilizing PubMed and Google Scholar.

Results

New agents under investigation include nanoTRAIL, anti-Kv10.1, multimeric IgM, and humanized tetravalent antibodies. Developments have been made to test novel agents, and imaging has been used to detect DR5 in preclinical models and patients. The models include 3D spheroids, genetically modified mouse models, a novel jaw osteosarcoma model, and patient-derived xenograft (PDX) animal models. There are currently two ongoing clinical trials focusing on the activation of DR5, namely, IGM-8444 and INBRX-109, which have progressed to phase 2. Further modifications of TRAIL delivery with fusion to single-chain variable fragments (scFv-TRAIL), directed against tumor-associated antigens (TAAs), and in the use of stem cells focus on targeted TRAIL delivery to cancer cells using bi-functional strategies.

Conclusion

In vitro, in vivo, and clinical trials, as well as advances in imaging and theranostics, indicate that targeting DR5 remains a valid strategy in the treatment of some relapsed and refractory cancers.

Ethics of Preanesthesia Mandatory Laboratory Testing

Some practices require mandatory preoperative laboratory testing for select patients presenting for anesthesia and surgery. Such mandatory preanesthesia laboratory testing has significant ethical implications related to informed consent and patient autonomy. Assumptions that a patient provides "presumed consent" by merely presenting for a test are flawed because such consents are often not informed and do not acknowledge patient autonomy. By placing a condition on access to a medical treatment, mandatory preanesthesia testing may not be ethically justifiable. Not all laboratory tests are "ethically equal"; several raise specific questions regarding informed consent, related to their potential to cause significant harm.

Three-dimensional cell culture: Future scope in cancer vaccine development

Three-dimensional (3D) cell culture techniques, which are superior to 2D methods in viability and functionality, are being used to develop innovative cancer vaccines. Tumor spheroids, which are structurally and functionally similar to actual tumors, can be developed using 3D cell culture. These spheroid vaccines have shown superior antitumor immune responses to 2D cell-based vaccines. Dendritic cell vaccines can also be produced more efficiently using 3D cell culture. Personalized cancer vaccines are being developed using 3D cell culture, providing substantial benefits over 2D methods. The more natural conditions of 3D cell culture might promote the expression of tumor antigens not expressed in 2D culture, potentially allowing for more targeted vaccines by co-culturing tumor cells with other cell types. Advanced cancer vaccines using 3D cell cultures are expected soon.

Systematic Review of Genetic Substrate Reduction Therapy in Lysosomal Storage Diseases: Opportunities, Challenges and Delivery Systems

BACKGROUND

Genetic substrate reduction therapy (gSRT), which involves the use of nucleic acids to downregulate the genes involved in the biosynthesis of storage substances, has been investigated in the treatment of lysosomal storage diseases (LSDs).

OBJECTIVE

To analyze the application of gSRT to the treatment of LSDs, identifying the silencing tools and delivery systems used, and the main challenges for its development and clinical translation, highlighting the contribution of nanotechnology to overcome them.

METHODS

A systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guidelines was performed. PubMed, Scopus, and Web of Science databases were used for searching terms related to LSDs and gene-silencing strategies and tools.

RESULTS

Fabry, Gaucher, and Pompe diseases and mucopolysaccharidoses I and III are the only LSDs for which gSRT has been studied, siRNA and lipid nanoparticles being the silencing strategy and the delivery system most frequently employed, respectively. Only in one recently published study was CRISPR/Cas9 applied to treat Fabry disease. Specific tissue targeting, availability of relevant cell and animal LSD models, and the rare disease condition are the main challenges with gSRT for the treatment of these diseases. Out of the 11 studies identified, only two gSRT studies were evaluated in animal models.

CONCLUSIONS

Nucleic acid therapies are expanding the clinical tools and therapies currently available for LSDs. Recent advances in CRISPR/Cas9 technology and the growing impact of nanotechnology are expected to boost the clinical translation of gSRT in the near future, and not only for LSDs.

High-Throughput Assay for Predicting Diarrhea Risk Using a 2D Human Intestinal Stem Cell-Derived Model

Gastrointestinal toxicities (GITs) are the most prevalent adverse events (AE) reported in clinical trials, often resulting in dose-limitations that reduce drug efficacy and delay development and treatment optimization. Preclinical animal models do not accurately replicate human GI physiology, leaving few options for early detection of GI side effects prior to human studies. Development of an accurate model that predicts GIT earlier in drug discovery programs would better support successful clinical trial outcomes. Chemotherapeutics, which exhibit high rates of clinical GIT, frequently target mitotic cells. Therefore, we hypothesized that a model utilizing proliferative cell populations derived from human intestinal crypts would predict the occurrence of clinical GITs with high accuracy. Here, we describe the development of a multiparametric assay utilizing the RepliGut® Planar system, an intestinal stem cell-derived platform cultured in an accessible high throughput Transwell™ format. This assay addresses key physiological elements of GIT by assessing cell proliferation (EdU incorporation), cell abundance (DAPI quantification), and barrier function (TEER). Using this approach, we demonstrate that primary proliferative cell populations reproducibly respond to marketed chemotherapeutics at physiologic concentrations. To determine the ability of this model to predict clinical diarrhea risk, we evaluated a set of 30 drugs with known clinical diarrhea incidence in three human donors, comparing results to known plasma drug concentrations. This resulted in highly accurate predictions of diarrhea potential for each endpoint (balanced accuracy of 91% for DAPI, 90% for EdU, 88% for TEER) with minimal variation across human donors. In vitro toxicity screening using primary proliferative cells may enable improved safety evaluations, reducing the risk of AEs in clinical trials and ultimately lead to safer and more effective treatments for patients.

Single-domain antibodies and aptamers drive new opportunities for neurodegenerative disease research

Neurodegenerative diseases (NDs) in mammals, such as Alzheimer's disease (AD), Parkinson's disease (PD), and transmissible spongiform encephalopathies (TSEs), are characterized by the accumulation of misfolded proteins in the central nervous system (CNS). Despite the presence of these pathogenic proteins, the immune response in affected individuals remains notably muted. Traditional immunological strategies, particularly those reliant on monoclonal antibodies (mAbs), face challenges related to tissue penetration, blood-brain barrier (BBB) crossing, and maintaining protein stability. This has led to a burgeoning interest in alternative immunotherapeutic avenues. Notably, single-domain antibodies (or nanobodies) and aptamers have emerged as promising candidates, as their reduced size facilitates high affinity antigen binding and they exhibit superior biophysical stability compared to mAbs. Aptamers, synthetic molecules generated from DNA or RNA ligands, present both rapid production times and cost-effective solutions. Both nanobodies and aptamers exhibit inherent qualities suitable for ND research and therapeutic development. Cross-seeding events must be considered in both traditional and small-molecule-based immunodiagnostic and therapeutic approaches, as well as subsequent neurotoxic impacts and complications beyond protein aggregates. This review delineates the challenges traditional immunological methods pose in ND research and underscores the potential of nanobodies and aptamers in advancing next-generation ND diagnostics and therapeutics.

Exogenous ECM in an environmentally-mediated in vitro model for cardiac fibrosis

Few clinical solutions exist for cardiac fibrosis, creating the need for a tunable in vitro model to better understand fibrotic disease mechanisms and screen potential therapeutic compounds. Here, we combined cardiomyocytes, cardiac fibroblasts, and exogenous extracellular matrix (ECM) proteins to create an environmentally-mediated in vitro cardiac fibrosis model. Cells and ECM were combined into 2 types of cardiac tissues- aggregates and tissue rings. The addition of collagen I had a drastic negative impact on aggregate formation, but ring formation was not as drastically affected. In both tissue types, collagen and other ECM did not severely affect contractile function. Histological analysis showed direct incorporation of collagen into tissues, indicating that we can directly modulate the cells' ECM environment. This modulation affects tissue formation and distribution of cells, indicating that this model provides a useful platform for understanding how cells respond to changes in their extracellular environment and for potential therapeutic screening.

Improved Detection of Drug-Induced Liver Injury by Integrating Predicted In Vivo and In Vitro Data

Drug-induced liver injury (DILI) has been a significant challenge in drug discovery, often leading to clinical trial failures and necessitating drug withdrawals. Over the last decade, the existing suite of in vitro proxy-DILI assays has generally improved at identifying compounds with hepatotoxicity. However, there is considerable interest in enhancing the in silico prediction of DILI because it allows for evaluating large sets of compounds more quickly and cost-effectively, particularly in the early stages of projects. In this study, we aim to study ML models for DILI prediction that first predict nine proxy-DILI labels and then use them as features in addition to chemical structural features to predict DILI. The features include in vitro (e.g., mitochondrial toxicity, bile salt export pump inhibition) data, in vivo (e.g., preclinical rat hepatotoxicity studies) data, pharmacokinetic parameters of maximum concentration, structural fingerprints, and physicochemical parameters. We trained DILI-prediction models on 888 compounds from the DILI data set (composed of DILIst and DILIrank) and tested them on a held-out external test set of 223 compounds from the DILI data set. The best model, DILIPredictor, attained an AUC-PR of 0.79. This model enabled the detection of the top 25 toxic compounds (2.68 LR+, positive likelihood ratio) compared to models using only structural features (1.65 LR+ score). Using feature interpretation from DILIPredictor, we identified the chemical substructures causing DILI and differentiated cases of DILI caused by compounds in animals but not in humans. For example, DILIPredictor correctly recognized 2-butoxyethanol as nontoxic in humans despite its hepatotoxicity in mice models. Overall, the DILIPredictor model improves the detection of compounds causing DILI with an improved differentiation between animal and human sensitivity and the potential for mechanism evaluation. DILIPredictor required only chemical structures as input for prediction and is publicly available at https://broad.io/DILIPredictor for use via web interface and with all code available for download.

Protocol to create phenotypic primary human hepatocyte cultures using the RASTRUM 3D cell model platform

To improve human hepatotoxicity prediction, in vitro liver cell models replicating hepatocyte function, drug metabolism, and toxicity are required. Here, we present a protocol for creating 3D primary human hepatocyte (PHH) cell models using the RASTRUM Platform. We describe the process for PHH model generation; procedures for characterizing the PHH model, including viability, albumin production, and CYP450 inducibility; and drug treatment using acetaminophen and troglitazone. This protocol has applications in upscaling phenotypic hepatotoxicity applications.

Targeted Cancer Therapy-on-A-Chip

Targeted cancer therapy (TCT) is gaining increased interest because it reduces the risks of adverse side effects by specifically treating tumor cells. TCT testing has traditionally been performed using two-dimensional (2D) cell culture and animal studies. Organ-on-a-chip (OoC) platforms have been developed to recapitulate cancer in vitro, as cancer-on-a-chip (CoC), and used for chemotherapeutics development and testing. This review explores the use of CoCs to both develop and test TCTs, with a focus on three main aspects, the use of CoCs to identify target biomarkers for TCT development, the use of CoCs to test free, un-encapsulated TCTs, and the use of CoCs to test encapsulated TCTs. Despite current challenges such as system scaling, and testing externally triggered TCTs, TCToC shows a promising future to serve as a supportive, pre-clinical platform to expedite TCT development and bench-to-bedside translation.

Potential Health Benefits of a Diet Rich in Organic Fruit and Vegetables versus a Diet Based on Conventional Produce: A Systematic Review

CONTEXT

Over the past decade, the production and consumption of organic food (OF) have received increasing interest. Scientific studies have shown better quality of organic fruit and vegetables (FV) in terms of nutrients and pesticide contents, but it appears difficult to conclude if there are potentially greater health benefits of these products compared with conventional food (CF).

OBJECTIVE

To determine whether the current scientific literature demonstrates that a diet rich in organic FV is healthier than 1 based on conventional produce.

METHODS

A systematic search was conducted using the PubMed and Web of Science databases for articles published between January 2003 and December 2022. Articles were analyzed uniformly by 2 reviewer, using a specific template summary sheet, and scored from 1 to 5. The level of evidence and the quality of studies in humans were assessed using the Jadad score and the French National Authority for Health method.

RESULTS

A total of 12 human studies were included. Studies often reported contradictory or even opposite results, with methodological limitations. Only 6 of the 12 studies found significant associations between OF and the health outcomes evaluated.

CONCLUSION

The current data do not enable a firm conclusion about a greater health benefit for a diet rich in FV based on products grown organically compared with conventional farming. There is a paucity of available data and considerable heterogeneity in study designs (participants, exposures, durations, health outcomes, and residual confounding factors). Well-designed interventional studies are required.

Treatments and the Perspectives of Developing a Vaccine for Chagas Disease

Chagas disease (CD) treatment and vaccine development are critical due to the significant health burden caused by the disease, especially in Latin America. Current treatments include benznidazole and nifurtimox, which are most effective in the acute phase of the disease but less so in the chronic phase, often with significant side effects. Here, using the available literature, we summarize the progress in vaccine development and new treatments that promise to reduce CD incidence and improve the quality of life for those at risk, particularly in endemic regions. New treatment options, such as posaconazole and fexinidazole, are being explored to improve efficacy and reduce adverse effects. Vaccine development for CD remains a high priority. The complex life stages and genetic diversity of Trypanosoma cruzi present challenges, but several promising vaccine candidates are under investigation. These efforts focus on stimulating a protective immune response through various innovative approaches.

Machine Learning Prediction of On/Off Target-driven Clinical Adverse Events

OBJECTIVE

Currently, 90% of clinical drug development fails, where 30% of these failures are due to clinical toxicity. The current extensive animal toxicity studies are not predictive of clinical adverse events (AEs) at clinical doses, while current computation models only consider very few factors with limited success in clinical toxicity prediction. We aimed to address these issues by developing a machine learning (ML) model to directly predict clinical AEs.

METHODS

Using a dataset with 759 FDA-approved drugs with known AEs, we first adapted the ConPLex ML model to predict IC50 values of these FDA-approved drugs against their on-target and off-target binding among 477 protein targets. Subsequently, we constructed a new ML model to predict clinical AEs using IC50 values of 759 drugs' primary on-target and off-target effects along with tissue-specific protein expression profiles.

RESULTS

The adapted ConPLex model predicted drug-target interactions for both on- and off-target effects, as shown by co-localization of the 6 small molecule kinase inhibitors with their respective kinases. The coupled ML models demonstrated good predictive capability of clinical AEs, with accuracy over 75%.

CONCLUSIONS

Our approach provides a new insight into the mechanistic understanding of in vivo drug toxicity in relationship with drug on-/off-target interactions. The coupled ML models, once validated with larger datasets, may offer advantages to directly predict clinical AEs using in vitro/ex vivo and preclinical data, which will help to reduce drug development failure due to clinical toxicity.

Microphysiological Blood-Brain Barrier Systems for Disease Modeling and Drug Development

The blood-brain barrier (BBB) is a highly controlled microenvironment that regulates the interactions between cerebral blood and brain tissue. Due to its selectivity, many therapeutics targeting various neurological disorders are not able to penetrate into brain tissue. Pre-clinical studies using animals and other in vitro platforms have not shown the ability to fully replicate the human BBB leading to the failure of a majority of therapeutics in clinical trials. However, recent innovations in vitro and ex vivo modeling called organs-on-chips have shown the potential to create more accurate disease models for improved drug development. These microfluidic platforms induce physiological stressors on cultured cells and are able to generate more physiologically accurate BBBs compared to previous in vitro models. In this review, different approaches to create BBBs-on-chips are explored alongside their application in modeling various neurological disorders and potential therapeutic efficacy. Additionally, organs-on-chips use in BBB drug delivery studies is discussed, and advances in linking brain organs-on-chips onto multiorgan platforms to mimic organ crosstalk are reviewed.

Anti-aging and immunomodulatory role of caffeine in Drosophila larvae

Drug repurposing is a promising approach to identify new pharmacological indications for drugs that have already been established. However, there is still a limitation in the availability of a high-throughput in vivo preclinical system that is suitable for screening and investigating new pharmacological indications. The aim of this study was to introduce the application of Drosophila larvae as an in vivo platform to screen drug candidates with anti-aging and immunomodulatory activities. To determine whether Drosophila larvae can be utilized for assessing anti-aging and immunomodulatory activities, phenotypical and molecular assays were conducted using wildtype and mutant lines of Drosophila. The utilization of mutant lines (PGRP-LBΔ and Psh[1];;ModSP[KO]) mimics the autoinflammatory and immunodeficient conditions in humans, thereby enabling a thorough investigation of the effects of various compounds. The phenotypical assay was carried out using survival and locomotor observation in Drosophila larvae and adult flies. Meanwhile, the molecular assay was conducted using the RT-qPCR method. In vivo survival analysis revealed that caffeine was relatively safe for Drosophila larvae and exhibited the ability to extend Drosophila lifespan compared to the untreated controls, suggesting its anti-aging properties. Further analysis using the RT-qPCR method demonstrated that caffeine treatment induced transcriptional changes in the Drosophila larvae, particularly in the downstream of NF-κB and JAK-STAT pathways, two distinct immune-related pathways homologue to humans. In addition, caffeine enhanced the survival of Drosophila autoinflammatory model, further implying its immunosuppressive activity. Nevertheless, this compound had minimal to no effect on the survival of Staphylococcus aureus-infected wildtype and immunodeficient Drosophila, refuting its antibacterial and immunostimulant activities. Overall, our results suggest that the anti-aging and immunosuppressive activities of caffeine observed in Drosophila larvae align with those reported in mammalian model systems, emphasizing the suitability of Drosophila larvae as a model organism in drug repurposing endeavors, particularly for the screening of newly discovered chemical entities to assess their immunomodulatory activities before proceedings to investigations in mammalian animal models.

Mass Spectrometry Imaging of Organoids to Improve Preclinical Research

Preclinical models are essential research tools before novel therapeutic or diagnostic methods can be applied to humans. These range from in vitro cell monocultures to vastly more complex animal models, but clinical translation to humans often fails to deliver significant results. Three-dimensional (3D) organoid systems are being increasingly studied to establish physiologically relevant in vitro platforms in a trade-off between the complexity of the research question and the complexity of practical experimental setups. The sensitivity and precision of analytical tools are yet another limiting factors in what can be investigated, and mass spectrometry (MS) is one of the most powerful analytical techniques available to the scientific community. Its innovative use to spatially resolve biological samples has opened many research avenues in the field of MS imaging (MSI). Here, this work aims to explore the current scientific landscape in the application of MSI on organoids, with an emphasis on their combined potential to facilitate and improve preclinical studies.

Advances in gut-brain organ chips

The brain and gut are sensory organs responsible for sensing, transmitting, integrating, and responding to signals from the internal and external environment. In-depth analysis of brain-gut axis interactions is important for human health and disease prevention. Current research on the brain-gut axis primarily relies on animal models. However, animal models make it difficult to study disease mechanisms due to inherent species differences, and the reproducibility of experiments is poor because of individual animal variations, which leads to a significant limitation of real-time sensory responses. Organ-on-a-chip platforms provide an innovative approach for disease treatment and personalized research by replicating brain and gut ecosystems in vitro. This enables a precise understanding of their biological functions and physiological responses. In this article, we examine the history and most current developments in brain, gut, and gut-brain chips. The importance of these systems for understanding pathophysiology and developing new drugs is emphasized throughout the review. This article also addresses future directions and present issues with the advancement and application of gut-brain-on-a-chip technologies.

Nontraditional models as research tools: the road not taken

Historical reasons resulted in the almost exclusive use of a few species, most prominently Mus musculus, as the mainstream models in biomedical research. This selection was not based on Mus's distinctive relevance to human disease but rather to the pre-existing availability of resources and tools for the species that were used as models, which has enabled their adoption for research in health sciences. Unless the utilization and range of nontraditional research models expand considerably, progress in biomedical research will remain restricted within the trajectory that has been set by the existing models and their ability to provide clinically relevant information.

What public health challenges and unmet medical needs would benefit from interdisciplinary collaboration in the EU? A survey and multi-stakeholder debate

In the past decade, significant European calls for research proposals have supported translational collaborative research on non-communicable and infectious diseases within the biomedical life sciences by bringing together interdisciplinary and multinational consortia. This research has advanced our understanding of disease pathophysiology, marking considerable scientific progress. Yet, it is crucial to retrospectively evaluate these efforts' societal impact. Research proposals should be thoughtfully designed to ensure that the research findings can be effectively translated into actionable policies. In addition, the choice of scientific methods plays a pivotal role in shaping the societal impact of research discoveries. Understanding the factors responsible for current unmet public health issues and medical needs is crucial for crafting innovative strategies for research policy interventions. A multistakeholder survey and a roundtable helped identify potential needs for consideration in the EU research and policy agenda. Based on survey findings, mental health disorders, metabolic syndrome, cancer, antimicrobial resistance, environmental pollution, and cardiovascular diseases were considered the public health challenges deserving prioritisation. In addition, early diagnosis, primary prevention, the impact of environmental pollution on disease onset and personalised medicine approaches were the most selected unmet medical needs. Survey findings enabled the formulation of some research-policies interventions (RPIs), which were further discussed during a multistakeholder online roundtable. The discussion underscored recent EU-level activities aligned with the survey-derived RPIs and facilitated an exchange of perspectives on public health and biomedical research topics ripe for interdisciplinary collaboration and warranting attention within the EU's research and policy agenda. Actionable recommendations aimed at facilitating the translation of knowledge into transformative, science-based policies are also provided.

Applications and advancements in animal models for antiviral research on mosquito-borne arboviruses

Vector-borne diseases caused by arthropod-borne viruses (arboviruses) are a considerable challenge to public health globally. Mosquito-borne arboviruses, such as Chikungunya, Dengue, and Zika viruses, cause a range of human illnesses and may be fatal. Currently, efforts to control these diseases still face challenges due to growing vector resistance towards insecticides, urbanization, and limited effective antiviral treatments and vaccines. Animal models are crucial in antiviral research on mosquito-borne arboviruses, playing a role in understanding disease mechanisms, vaccine development, and toxicity testing, but the application of animal models still faces the challenges of ethical considerations and animal-to-human translational success. Genetically engineered mouse models, hamster models and non-human primate (NHP) are currently used in arbovirus research, but new models such as tree shrews and novel humanized mice are emerging. In the context of Malaysian research, the use of long-tailed macaques as potential NHP models for arbovirus research is possible; however, it faces the ethical dilemma of using an endangered species for scientific purposes. Overall, animal models play a crucial role in advancing infectious disease research, but a balance between medical research and species conservation must be upheld.

Crisis in the gut: navigating gastrointestinal challenges in Gulf War Illness with bioengineering

Gulf War Illness (GWI) is characterized by a wide range of symptoms that manifests largely as gastrointestinal symptoms. Among these gastrointestinal symptoms, motility disorders are highly prevalent, presenting as chronic constipation, stomach pain, indigestion, diarrhea, and other conditions that severely impact the quality of life of GWI veterans. However, despite a high prevalence of gastrointestinal impairments among these veterans, most research attention has focused on neurological disturbances. This perspective provides a comprehensive overview of current in vivo research advancements elucidating the underlying mechanisms contributing to gastrointestinal disorders in GWI. Generally, these in vivo and in vitro models propose that neuroinflammation alters gut motility and drives the gastrointestinal symptoms reported in GWI. Additionally, this perspective highlights the potential and challenges of in vitro bioengineering models, which could be a crucial contributor to understanding and treating the pathology of gastrointestinal related-GWI.

Comprehensive approaches to preclinical evaluation of monoclonal antibodies and their next-generation derivatives

Biotherapeutics hold great promise for the treatment of several diseases and offer innovative possibilities for new treatments that target previously unaddressed medical needs. Despite successful transitions from preclinical to clinical stages and regulatory approval, there are instances where adverse reactions arise, resulting in product withdrawals. As a result, it is essential to conduct thorough evaluations of safety and effectiveness on an individual basis. This article explores current practices, challenges, and future approaches in conducting comprehensive preclinical assessments to ensure the safety and efficacy of biotherapeutics including monoclonal antibodies, toxin-conjugates, bispecific antibodies, single-chain antibodies, Fc-engineered antibodies, antibody mimetics, and siRNA-antibody/peptide conjugates.

Next Generation Risk Assessment approaches for advanced nanomaterials: Current status and future perspectives

This manuscript discusses the challenges of applying New Approach Methodologies (NAMs) for safe by design and regulatory risk assessment of advanced nanomaterials (AdNMs). The authors propose a framework for Next Generation Risk Assessment of AdNMs involving NAMs that is aligned to the conventional risk assessment paradigm. This framework is exposure-driven, endpoint-specific, makes best use of pre-existing information, and can be implemented in tiers of increasing specificity and complexity of the adopted NAMs. The tiered structure of the approach, which effectively combines the use of existing data with targeted testing will allow safety to be assessed cost-effectively and as far as possible with even more limited use of vertebrates. The regulatory readiness of state-of-the-art emerging NAMs is assessed in terms of Transparency, Reliability, Accessibility, Applicability, Relevance and Completeness, and their appropriateness for AdNMs is discussed in relation to each step of the risk assessment paradigm along with providing perspectives for future developments in the respective scientific and regulatory areas.

Lubricant-Coated Organ-on-a-Chip for Enhanced Precision in Preclinical Drug Testing

In drug discovery, human organ-on-a-chip (organ chip) technology has emerged as an essential tool for preclinical testing, offering a realistic representation of human physiology, real-time monitoring, and disease modeling. Polydimethylsiloxane (PDMS) is commonly used in organ chip fabrication owing to its biocompatibility, flexibility, transparency, and ability to replicate features down to the nanoscale. However, the porous nature of PDMS leads to unintended absorption of small molecules, critically affecting the drug response analysis. Addressing this challenge, the precision drug testing organ chip (PreD chip) is introduced, an innovative platform engineered to minimize small molecule absorption while facilitating cell culture. This chip features a PDMS microchannel wall coated with a perfluoropolyether-based lubricant, providing slipperiness and antifouling properties. It also incorporates an ECM-coated semi-porous membrane that supports robust multicellular cultures. The PreD chip demonstrates its outstanding antifouling properties and resistance to various biological fluids, small molecule drugs, and plasma proteins. In simulating the human gut barrier, the PreD chip demonstrates highly enhanced sensitivity in tests for dexamethasone toxicity and is highly effective in assessing drug transport across the human blood-brain barrier. These findings emphasize the potential of the PreD chip in advancing organ chip-based drug testing methodologies.

Advancing Drug Safety in Drug Development: Bridging Computational Predictions for Enhanced Toxicity Prediction

The attrition rate of drugs in clinical trials is generally quite high, with estimates suggesting that approximately 90% of drugs fail to make it through the process. The identification of unexpected toxicity issues during preclinical stages is a significant factor contributing to this high rate of failure. These issues can have a major impact on the success of a drug and must be carefully considered throughout the development process. These late-stage rejections or withdrawals of drug candidates significantly increase the costs associated with drug development, particularly when toxicity is detected during clinical trials or after market release. Understanding drug-biological target interactions is essential for evaluating compound toxicity and safety, as well as predicting therapeutic effects and potential off-target effects that could lead to toxicity. This will enable scientists to predict and assess the safety profiles of drug candidates more accurately. Evaluation of toxicity and safety is a critical aspect of drug development, and biomolecules, particularly proteins, play vital roles in complex biological networks and often serve as targets for various chemicals. Therefore, a better understanding of these interactions is crucial for the advancement of drug development. The development of computational methods for evaluating protein-ligand interactions and predicting toxicity is emerging as a promising approach that adheres to the 3Rs principles (replace, reduce, and refine) and has garnered significant attention in recent years. In this review, we present a thorough examination of the latest breakthroughs in drug toxicity prediction, highlighting the significance of drug-target binding affinity in anticipating and mitigating possible adverse effects. In doing so, we aim to contribute to the development of more effective and secure drugs.

Improved Detection of Drug-Induced Liver Injury by Integrating Predicted in vivo and in vitro Data

Drug-induced liver injury (DILI) has been significant challenge in drug discovery, often leading to clinical trial failures and necessitating drug withdrawals. The existing suite of in vitro proxy-DILI assays is generally effective at identifying compounds with hepatotoxicity. However, there is considerable interest in enhancing in silico prediction of DILI because it allows for the evaluation of large sets of compounds more quickly and cost-effectively, particularly in the early stages of projects. In this study, we aim to study ML models for DILI prediction that first predicts nine proxy-DILI labels and then uses them as features in addition to chemical structural features to predict DILI. The features include in vitro (e.g., mitochondrial toxicity, bile salt export pump inhibition) data, in vivo (e.g., preclinical rat hepatotoxicity studies) data, pharmacokinetic parameters of maximum concentration, structural fingerprints, and physicochemical parameters. We trained DILI-prediction models on 888 compounds from the DILIst dataset and tested on a held-out external test set of 223 compounds from DILIst dataset. The best model, DILIPredictor, attained an AUC-ROC of 0.79. This model enabled the detection of top 25 toxic compounds compared to models using only structural features (2.68 LR+ score). Using feature interpretation from DILIPredictor, we were able to identify the chemical substructures causing DILI as well as differentiate cases DILI is caused by compounds in animals but not in humans. For example, DILIPredictor correctly recognized 2-butoxyethanol as non-toxic in humans despite its hepatotoxicity in mice models. Overall, the DILIPredictor model improves the detection of compounds causing DILI with an improved differentiation between animal and human sensitivity as well as the potential for mechanism evaluation. DILIPredictor is publicly available at https://broad.io/DILIPredictor for use via web interface and with all code available for download and local implementation via https://pypi.org/project/dilipred/.

A deep learning based multi-model approach for predicting drug-like chemical compound's toxicity

Ensuring the safety and efficacy of chemical compounds is crucial in small-molecule drug development. In the later stages of drug development, toxic compounds pose a significant challenge, losing valuable resources and time. Early and accurate prediction of compound toxicity using deep learning models offers a promising solution to mitigate these risks during drug discovery. In this study, we present the development of several deep-learning models aimed at evaluating different types of compound toxicity, including acute toxicity, carcinogenicity, hERG_cardiotoxicity (the human ether-a-go-go related gene caused cardiotoxicity), hepatotoxicity, and mutagenicity. To address the inherent variations in data size, label type, and distribution across different types of toxicity, we employed diverse training strategies. Our first approach involved utilizing a graph convolutional network (GCN) regression model to predict acute toxicity, which achieved notable performance with Pearson R 0.76, 0.74, and 0.65 for intraperitoneal, intravenous, and oral administration routes, respectively. Furthermore, we trained multiple GCN binary classification models, each tailored to a specific type of toxicity. These models exhibited high area under the curve (AUC) scores, with an impressive AUC of 0.69, 0.77, 0.88, and 0.79 for predicting carcinogenicity, hERG_cardiotoxicity, mutagenicity, and hepatotoxicity, respectively. Additionally, we have used the approved drug dataset to determine the appropriate threshold value for the prediction score in model usage. We integrated these models into a virtual screening pipeline to assess their effectiveness in identifying potential low-toxicity drug candidates. Our findings indicate that this deep learning approach has the potential to significantly reduce the cost and risk associated with drug development by expediting the selection of compounds with low toxicity profiles. Therefore, the models developed in this study hold promise as critical tools for early drug candidate screening and selection.

The estimation and translation uncertainties in applying NOAEL to clinical dose escalation

The systemic exposure at the no-observed-adverse-effect-level (NOAEL) estimated from animals is an important criterion commonly applied to guard the safety of participants in clinical trials of investigational drugs. However, the discrepancy in toxicity profile between species is widely recognized. The objective of the work reported here was to assess, via simulation, the level of uncertainty in the NOAEL estimated from an animal species and the effectiveness of applying its associated exposure value to minimizing the toxicity risk to human. Simulations were conducted for dose escalation of an investigational new chemical entity with hypothetical exposure-response models for the dose-limiting toxicity under a variety of conditions, in terms of between-species relative sensitivity to the toxicity and the between-subject variability in the key parameters determining the sensitivity and pharmacokinetics. Results show a high uncertainty in the NOAEL estimation. Notably, even when the animal species and humans are assumed to have the same sensitivity, which may not be realistic, limiting clinical dose to the exposure at the NOAEL that has been identified in the animals carries a high risk of either causing toxicity or under-dosing, hence undermining the therapeutic potential of the drug candidate. These findings highlight the importance of understanding the mechanism of the toxicity profile and its cross-species translatability, as well as the importance of understanding the dose requirement for achieving adequate pharmacology.

Technology Readiness Level Roadmap for Developing Innovative Herbal Medicinal Products

Despite the vast global botanical diversity, the pharmaceutical development of herbal medicinal products (HMPs) remains underexploited. Of over 370,000 described plant species, only a few hundred are utilized in HMPs. Most of these have originated from traditional use, and only a minority come from megadiverse countries. Exploiting the pharmacological synergies of the hundreds of compounds found in poorly studied plant species may unlock new therapeutic possibilities, enhance megadiverse countries' scientific and socio-economic development, and help conserve biodiversity. However, extensive constraints in the development process of HMPs pose significant barriers to transforming this unsatisfactory socio-economic landscape. This paper proposes a roadmap to overcome these challenges, based on the technology readiness levels (TRLs) introduced by NASA to assess the maturity of technologies. It aims to assist research entities, manufacturers, and funding agencies from megadiverse countries in the discovery, development, and global market authorization of innovative HMPs that comply with regulatory standards from ANVISA, EMA, and FDA, as well as WHO and ICH guidelines.

Feasibility of Using a Type I IFN-Based Non-Animal Approach to Predict Vaccine Efficacy and Safety Profiles

Animal-based tests are used for the control of vaccine quality. However, because highly purified and safe vaccines are now available, alternative approaches that can replace or reduce animal use for the assessment of vaccine outcomes must be established. In vitro tests for vaccine quality control exist and have already been implemented. However, these tests are specifically designed for some next-generation vaccines, and this makes them not readily available for testing other vaccines. Therefore, universal non-animal tests are still needed. Specific signatures of the innate immune response could represent a promising approach to predict the outcome of vaccines by non-animal methods. Type I interferons (IFNs) have multiple immunomodulatory activities, which are exerted through effectors called interferon stimulated genes (ISGs), and are one of the most important immune signatures that might provide potential candidate molecular biomarkers for this purpose. This paper will mainly examine if this idea might be feasible by analyzing all relevant published studies that have provided type I IFN-related biomarkers for evaluating the safety and efficacy profiles of vaccines using an advanced transcriptomic approach as an alternative to the animal methods. Results revealed that such an approach could potentially provide biomarkers predictive of vaccine outcomes after addressing some limitations.

Validation of a functional human AD model with four AD therapeutics utilizing patterned iPSC-derived cortical neurons integrated with microelectrode arrays

Preclinical methods are needed for screening potential Alzheimer's disease (AD) therapeutics that recapitulate phenotypes found in the Mild Cognitive Impairment (MCI) stage or even before this stage of the disease. This would require a phenotypic system that reproduces cognitive deficits without significant neuronal cell death to mimic the clinical manifestations of AD during these stages. A potential functional parameter to be monitored is long-term potentiation (LTP), which is a correlate of learning and memory, that would be one of the first functions effected by AD onset. Mature human iPSC-derived cortical neurons and primary astrocytes were co-cultured on microelectrode arrays (MEA) where surface chemistry was utilized to create circuit patterns connecting two adjacent electrodes to model LTP function. LTP maintenance was significantly reduced in the presence of Amyloid-Beta 42 (Aβ42) oligomers compared to the controls, however, co-treatment with AD therapeutics (Donepezil, Memantine, Rolipram and Saracatinib) corrected Aβ42 induced LTP impairment. The results presented here illustrate the significance of the system as a validated platform that can be utilized to model and study MCI AD pathology, and potentially for the pre-MCI phase before the occurrence of significant cell death. It also has the potential to become an ideal platform for high content therapeutic screening for other neurodegenerative diseases.

Effects of Chemicals in Reporter Gene Bioassays with Different Metabolic Activities Compared to Baseline Toxicity

High-throughput cell-based bioassays are used for chemical screening and risk assessment. Chemical transformation processes caused by abiotic degradation or metabolization can reduce the chemical concentration or, in some cases, lead to the formation of more toxic transformation products. Unaccounted loss processes may falsify the bioassay results. Capturing the formation and effects of transformation products is important for relating the in vitro effects to in vivo. Reporter gene cell lines are believed to have low metabolic activity, but inducibility of cytochrome P450 (CYP) enzymes has been reported. Baseline toxicity is the minimal toxicity a chemical can have and is caused by the incorporation of the chemical into cell membranes. In the present study, we improved an existing baseline toxicity model based on a newly defined critical membrane burden derived from freely dissolved effect concentrations, which are directly related to the membrane concentration. Experimental effect concentrations of 94 chemicals in three bioassays (AREc32, ARE-bla and GR-bla) were compared with baseline toxicity by calculating the toxic ratio (TR). CYP activities of all cell lines were determined by using fluorescence-based assays. Only ARE-bla showed a low basal CYP activity and inducibility and AREc32 showed a low inducibility. Overall cytotoxicity was similar in all three assays despite the different metabolic activities indicating that chemical metabolism is not relevant for the cytotoxicity of the tested chemicals in these assays. Up to 28 chemicals showed specific cytotoxicity with TR > 10 in the bioassays, but baseline toxicity could explain the effects of the majority of the remaining chemicals. Seven chemicals showed TR < 0.1 indicating inaccurate physicochemical properties or experimental artifacts like chemical precipitation, volatilization, degradation, or other loss processes during the in vitro bioassay. The new baseline model can be used not only to identify specific cytotoxicity mechanisms but also to identify potential problems in the experimental performance or evaluation of the bioassay and thus improve the quality of the bioassay data.

Validating Well-Functioning Hepatic Organoids for Toxicity Evaluation

"Organoids", three-dimensional self-organized organ-like miniature tissues, are proposed as intermediary models that bridge the gap between animal and human studies in drug development. Despite recent advancements in organoid model development, studies on toxicity using these models are limited. Therefore, in this study, we aimed to analyze the functionality and gene expression of pre- and post-differentiated human hepatic organoids derived from induced pluripotent stem cells and utilize them for toxicity assessment. First, we confirmed the functional similarity of this hepatic organoid model to the human liver through various functional assessments, such as glycogen storage, albumin and bile acid secretion, and cytochrome P450 (CYP) activity. Subsequently, utilizing these functionally validated hepatic organoids, we conducted toxicity evaluations with three hepatotoxic substances (ketoconazole, troglitazone, and tolcapone), which are well known for causing drug-induced liver injury, and three non-hepatotoxic substances (sucrose, ascorbic acid, and biotin). The organoids effectively distinguished between the toxicity levels of substances with and without hepatic toxicity. We demonstrated the potential of hepatic organoids with validated functionalities and genetic characteristics as promising models for toxicity evaluation by analyzing toxicological changes occurring in hepatoxic drug-treated organoids.

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

The webinar series and workshop titled “Trust Your Gut: Establishing Confidence in Gastrointestinal Models – An Overview of the State of the Science and Contexts of Use” was co-organized by NICEATM, NIEHS, FDA, EPA, CPSC, DoD, and the Johns Hopkins Center for Alternatives to Animal Testing (CAAT) and hosted at the National Institutes of Health in Bethesda, MD, USA on October 11-12, 2023. New approach methods (NAMs) for assessing issues of gastrointestinal tract (GIT)- related toxicity offer promise in addressing some of the limitations associated with animal-based assessments. GIT NAMs vary in complexity, from two-dimensional monolayer cell line-based systems to sophisticated 3-dimensional organoid systems derived from human primary cells. Despite advances in GIT NAMs, challenges remain in fully replicating the complex interactions and pro­cesses occurring within the human GIT. Presentations and discussions addressed regulatory needs, challenges, and innovations in incorporating NAMs into risk assessment frameworks; explored the state of the science in using NAMs for evaluating systemic toxicity, understanding absorption and pharmacokinetics, evaluating GIT toxicity, and assessing potential allergenicity; and discussed strengths, limitations, and data gaps of GIT NAMs as well as steps needed to establish confidence in these models for use in the regulatory setting.

The application of natural language processing for the extraction of mechanistic information in toxicology

To study the ways in which compounds can induce adverse effects, toxicologists have been constructing Adverse Outcome Pathways (AOPs). An AOP can be considered as a pragmatic tool to capture and visualize mechanisms underlying different types of toxicity inflicted by any kind of stressor, and describes the interactions between key entities that lead to the adverse outcome on multiple biological levels of organization. The construction or optimization of an AOP is a labor intensive process, which currently depends on the manual search, collection, reviewing and synthesis of available scientific literature. This process could however be largely facilitated using Natural Language Processing (NLP) to extract information contained in scientific literature in a systematic, objective, and rapid manner that would lead to greater accuracy and reproducibility. This would support researchers to invest their expertise in the substantive assessment of the AOPs by replacing the time spent on evidence gathering by a critical review of the data extracted by NLP. As case examples, we selected two frequent adversities observed in the liver: namely, cholestasis and steatosis denoting accumulation of bile and lipid, respectively. We used deep learning language models to recognize entities of interest in text and establish causal relationships between them. We demonstrate how an NLP pipeline combining Named Entity Recognition and a simple rules-based relationship extraction model helps screen compounds related to liver adversities in the literature, but also extract mechanistic information for how such adversities develop, from the molecular to the organismal level. Finally, we provide some perspectives opened by the recent progress in Large Language Models and how these could be used in the future. We propose this work brings two main contributions: 1) a proof-of-concept that NLP can support the extraction of information from text for modern toxicology and 2) a template open-source model for recognition of toxicological entities and extraction of their relationships. All resources are openly accessible via GitHub (https://github.com/ontox-project/en-tox).

Characterizing Glomerular Barrier Dysfunction with Patient-Derived Serum in Glomerulus-on-a-Chip Models: Unveiling New Insights into Glomerulonephritis

Glomerulonephritis (GN) is characterized by podocyte injury or glomerular filtration dysfunction, which results in proteinuria and eventual loss of kidney function. Progress in studying the mechanism of GN, and developing an effective therapy, has been limited by the absence of suitable in vitro models that can closely recapitulate human physiological responses. We developed a microfluidic glomerulus-on-a-chip device that can recapitulate the physiological environment to construct a functional filtration barrier, with which we investigated biological changes in podocytes and dynamic alterations in the permeability of the glomerular filtration barrier (GFB) on a chip. We also evaluated the potential of GN-mimicking devices as a model for predicting responses to human GN. Glomerular endothelial cells and podocytes successfully formed intact monolayers on opposite sides of the membrane in our chip device. Permselectivity analysis confirmed that the chip was constituted by a functional GFB that could accurately perform differential clearance of albumin and dextran. Reduction in cell viability resulting from damage was observed in all serum-induced GN models. The expression of podocyte-specific marker WT1 was also decreased. Albumin permeability was increased in most models of serum-induced IgA nephropathy (IgAN) and membranous nephropathy (MN). However, sera from patients with minimal change disease (MCD) or lupus nephritis (LN) did not induce a loss of permeability. This glomerulus-on-a-chip system may provide a platform of glomerular cell culture for in vitro GFB in formation of a functional three-dimensional glomerular structure. Establishing a disease model of GN on a chip could accelerate our understanding of pathophysiological mechanisms of glomerulopathy.

The relevance of sustainable laboratory practices

Scientists are of key importance to the society to advocate awareness of the climate crisis and its underlying scientific evidence and provide solutions for a sustainable future. As much as scientific research has led to great achievements and benefits, traditional laboratory practices come with unintended environmental consequences. Scientists, while providing solutions to climate problems and educating the young innovators of the future, are also part of the problem: excessive energy consumption, (hazardous) waste generation, and resource depletion. Through their own research operations, science, research and laboratories have a significant carbon footprint and contribute to the climate crisis. Climate change requires a rapid response across all sectors of society, modeled by inspiring leaders. A broader scientific community that takes concrete actions would serve as an important step in convincing the general public of similar actions. Over the past years, grassroots movements across the sciences have recognized the overlooked impact of the scientific enterprise, and so-called Green Lab initiatives emerged seeking to address the environmental footprint of research. Driven by the voluntary efforts of researchers and staff, they educate peers, develop sustainability guidelines, write scientific publications and maintain accreditation frameworks. With this perspective we want to advocate for and spark leadership to promote a systemic change in laboratory practices and approach to research. Comprehensive evidence for the environmental impact of laboratories and their root-causes is presented, expanded with data from a current case study of the University of Groningen showcasing annual savings of 398 763 € as well as 477.1 tons of CO2e. This is followed by guidelines for sustainable lab practices and hands-on advice on how to achieve a systemic change at research institutions and industry. How can we expect industry, politics, and society to change, if we as scientists are not changing either? Scientists should lead by example and practice the change they want to see.

Liver-on-chip model and application in predictive genotoxicity and mutagenicity of drugs

Currently, there is no test system, whether in vitro or in vivo, capable of examining all endpoints required for genotoxicity evaluation used in pre-clinical drug safety assessment. The objective of this study was to develop a model which could assess all the required endpoints and possesses robust human metabolic activity, that could be used in a streamlined, animal-free manner. Liver-on-chip (LOC) models have intrinsic human metabolic activity that mimics the in vivo environment, making it a preferred test system. For our assay, the LOC was assembled using primary human hepatocytes or HepaRG cells, in a MPS-T12 plate, maintained under microfluidic flow conditions using the PhysioMimix® Microphysiological System (MPS), and co-cultured with human lymphoblastoid (TK6) cells in transwells. This system allows for interaction between two compartments and for the analysis of three different genotoxic endpoints, i.e. DNA strand breaks (comet assay) in hepatocytes, chromosome loss or damage (micronucleus assay) and mutation (Duplex Sequencing) in TK6 cells. Both compartments were treated at 0, 24 and 45 h with two direct genotoxicants: methyl methanesulfonate (MMS) and ethyl methanesulfonate (EMS), and two genotoxicants requiring metabolic activation: benzo[a]pyrene (B[a]P) and cyclophosphamide (CP). Assessment of cytochrome activity, RNA expression, albumin, urea and lactate dehydrogenase production, demonstrated functional metabolic capacities. Genotoxicity responses were observed for all endpoints with MMS and EMS. Increases in the micronucleus and mutations (MF) frequencies were also observed with CP, and %Tail DNA with B[a]P, indicating the metabolic competency of the test system. CP did not exhibit an increase in the %Tail DNA, which is in line with in vivo data. However, B[a]P did not exhibit an increase in the % micronucleus and MF, which might require an optimization of the test system. In conclusion, this proof-of-principle experiment suggests that LOC-MPS technology is a promising tool for in vitro hazard identification genotoxicants.

Microfluidic gut-axis-on-a-chip models for pharmacokinetic-based disease models

The low success rate of new drugs transitioning from animal testing to human clinical trials necessitates the development of more accurate and representative in vitro models. Recent advances in multi-organ-on-a-chip technology offer promising avenues for studying complex organ-organ interactions. Gut-liver-on-a-chip systems hold particular promise for mimicking the intricate interplay between the gut and liver, which play crucial roles in nutrient absorption, drug metabolism, detoxification, and immune response. Here, we discuss the key components of the gut-liver axis, including the gut epithelium, liver cells, gut microbiota, and their roles in the organ functions. We then explore the potential of gut-liver-on-a-chip models to replicate the intricate interactions between the two organs for pharmacokinetic studies and their expansion to more complicated multi-organ models. Finally, we provide perspectives and future directions for developing more physiologically relevant gut-liver-axis models for more efficient drug development, studying liver diseases, and personalizing treatment strategies.

Ethical Principles Do Not Support Mandatory Preanesthesia Pregnancy Screening Tests: A Narrative Review

Respect for patient autonomy is a pillar of medical ethics, manifested predominantly through informed consent. Mandatory (routine) nonconsented preoperative urine pregnancy testing does not adequately respect patient autonomy, is potentially coercive, and has the potential to cause harm medically, psychologically, socially, and financially. Inaccuracies in pregnancy testing can result in false-positive and false-negative results, especially in early pregnancy. There is substantial scientific evidence that anesthesia is not harmful to the fetus, raising the question of whether pregnancy testing provides substantial benefit to the patient. Not performing a preanesthesia pregnancy test has not been associated with significant medicolegal consequences. We review the ethical implications of mandatory preanesthesia pregnancy testing in light of these facts.

How neurobehavior and brain development in alternative whole-organism models can contribute to prediction of developmental neurotoxicity

Developmental neurotoxicity (DNT) is not routinely evaluated in chemical risk assessment because current test paradigms for DNT require the use of mammalian models which are ethically controversial, expensive, and resource demanding. Consequently, efforts have focused on revolutionizing DNT testing through affordable novel alternative methods for risk assessment. The goal is to develop a DNT in vitro test battery amenable to high-throughput screening (HTS). Currently, the DNT in vitro test battery consists primarily of human cell-based assays because of their immediate relevance to human health. However, such cell-based assays alone are unable to capture the complexity of a developing nervous system. Whole organismal systems that qualify as 3 R (Replace, Reduce and Refine) models are urgently needed to complement cell-based DNT testing. These models can provide the necessary organismal context and be used to explore the impact of chemicals on brain function by linking molecular and/or cellular changes to behavioural readouts. The nematode Caenorhabditis elegans, the planarian Dugesia japonica, and embryos of the zebrafish Danio rerio are all suited to low-cost HTS and each has unique strengths for DNT testing. Here, we review the strengths and the complementarity of these organisms in a novel, integrative context and highlight how they can augment current cell-based assays for more comprehensive and robust DNT screening of chemicals. Considering the limitations of all in vitro test systems, we discuss how a smart combinatory use of these systems will contribute to a better human relevant risk assessment of chemicals that considers the complexity of the developing brain.