3S - Systematic, systemic, and systems biology and toxicology

AI and ML-based risk assessment of chemicals: predicting carcinogenic risk from chemical-induced genomic instability

Chemical risk assessment plays a pivotal role in safeguarding public health and environmental safety by evaluating the potential hazards and risks associated with chemical exposures. In recent years, the convergence of artificial intelligence (AI), machine learning (ML), and omics technologies has revolutionized the field of chemical risk assessment, offering new insights into toxicity mechanisms, predictive modeling, and risk management strategies. This perspective review explores the synergistic potential of AI/ML and omics in deciphering clastogen-induced genomic instability for carcinogenic risk prediction. We provide an overview of key findings, challenges, and opportunities in integrating AI/ML and omics technologies for chemical risk assessment, highlighting successful applications and case studies across diverse sectors. From predicting genotoxicity and mutagenicity to elucidating molecular pathways underlying carcinogenesis, integrative approaches offer a comprehensive framework for understanding chemical exposures and mitigating associated health risks. Future perspectives for advancing chemical risk assessment and cancer prevention through data integration, advanced machine learning techniques, translational research, and policy implementation are discussed. By implementing the predictive capabilities of AI/ML and omics technologies, researchers and policymakers can enhance public health protection, inform regulatory decisions, and promote sustainable development for a healthier future.

Comparative case study on NAMs: towards enhancing specific target organ toxicity analysis

Traditional risk assessment methodologies in toxicology have relied upon animal testing, despite concerns regarding interspecies consistency, reproducibility, costs, and ethics. New Approach Methodologies (NAMs), including cell culture and multi-level omics analyses, hold promise by providing mechanistic information rather than assessing organ pathology. However, NAMs face limitations, like lacking a whole organism and restricted toxicokinetic interactions. This is an inherent challenge when it comes to the use of omics data from in vitro studies for the prediction of organ toxicity in vivo. One solution in this context are comparative in vitro-in vivo studies as they allow for a more detailed assessment of the transferability of the respective NAM data. Hence, hepatotoxic and nephrotoxic pesticide active substances were tested in human cell lines and the results subsequently related to the biology underlying established effects in vivo. To this end, substances were tested in HepaRG and RPTEC/tERT1 cells at non-cytotoxic concentrations and analyzed for effects on the transcriptome and parts of the proteome using quantitative real-time PCR arrays and multiplexed microsphere-based sandwich immunoassays, respectively. Transcriptomics data were analyzed using three bioinformatics tools. Where possible, in vitro endpoints were connected to in vivo observations. Targeted protein analysis revealed various affected pathways, with generally fewer effects present in RPTEC/tERT1. The strongest transcriptional impact was observed for Chlorotoluron in HepaRG cells (increased CYP1A1 and CYP1A2 expression). A comprehensive comparison of early cellular responses with data from in vivo studies revealed that transcriptomics outperformed targeted protein analysis, correctly predicting up to 50% of in vivo effects.

The Promise and Potential of Brain Organoids

Brain organoids are 3D in vitro culture systems derived from human pluripotent stem cells that self-organize to model features of the (developing) human brain. This review examines the techniques behind organoid generation, their current and potential applications, and future directions for the field. Brain organoids possess complex architecture containing various neural cell types, synapses, and myelination. They have been utilized for toxicology testing, disease modeling, infection studies, personalized medicine, and gene-environment interaction studies. An emerging concept termed Organoid Intelligence (OI) combines organoids with artificial intelligence systems to generate learning and memory, with the goals of modeling cognition and enabling biological computing applications. Brain organoids allow neuroscience studies not previously achievable with traditional techniques, and have the potential to transform disease modeling, drug development, and the understanding of human brain development and disorders. The aspirational vision of OI parallels the origins of artificial intelligence, and efforts are underway to map a roadmap toward its realization. In summary, brain organoids constitute a disruptive technology that is rapidly advancing and gaining traction across multiple disciplines.

An entropy weight method to integrate big omics and mechanistically evaluate DILI

BACKGROUND AND AIMS

DILI accounts for more than half of acute liver failure cases in the United States and is a major health care issue for the public worldwide. As investigative toxicology is playing an evolving role in the pharmaceutical industry, mechanistic insights into drug hepatotoxicity can facilitate drug development and clinical medication.

METHODS

By integrating multisource datasets including gene expression profiles of rat livers from open TG-GATE database and DrugMatrix, drug labels from FDA Liver Toxicity Knowledge Base, and clinical reports from LiverTox, and with the employment of bioinformatic and computational tools, this study developed an approach to characterize and predict DILI based on the molecular understanding of the processes (toxicity pathways).

RESULTS

A panel of 11 pathways widely covering biological processes and stress responses was established using a training set of six positive and one negative DILI drugs from open TG-GATEs. An entropy weight method-based model was developed to weight responsive genes within a pathway, and an interpretable machine-learning (ML) model XGBoot-SHAP was trained to rank the importance of pathways to the panel activity. The panel activity was proven to differentiate between injured and noninjured sample points and characterize DILI manifestation using six training drugs. Next, the model was tested using an additional 89 drugs (61 positives + 28 negatives), and a precision of 86% and higher can be achieved.

CONCLUSIONS

This study provides a novel approach to mechanisms-driven prediction modeling, as well as big data integration for insights into pharmacology and other human biology areas.

New approach methodologies in human regulatory toxicology - Not if, but how and when!

The predominantly animal-centric approach of chemical safety assessment has increasingly come under pressure. Society is questioning overall performance, sustainability, continued relevance for human health risk assessment and ethics of this system, demanding a change of paradigm. At the same time, the scientific toolbox used for risk assessment is continuously enriched by the development of "New Approach Methodologies" (NAMs). While this term does not define the age or the state of readiness of the innovation, it covers a wide range of methods, including quantitative structure-activity relationship (QSAR) predictions, high-throughput screening (HTS) bioassays, omics applications, cell cultures, organoids, microphysiological systems (MPS), machine learning models and artificial intelligence (AI). In addition to promising faster and more efficient toxicity testing, NAMs have the potential to fundamentally transform today's regulatory work by allowing more human-relevant decision-making in terms of both hazard and exposure assessment. Yet, several obstacles hamper a broader application of NAMs in current regulatory risk assessment. Constraints in addressing repeated-dose toxicity, with particular reference to the chronic toxicity, and hesitance from relevant stakeholders, are major challenges for the implementation of NAMs in a broader context. Moreover, issues regarding predictivity, reproducibility and quantification need to be addressed and regulatory and legislative frameworks need to be adapted to NAMs. The conceptual perspective presented here has its focus on hazard assessment and is grounded on the main findings and conclusions from a symposium and workshop held in Berlin in November 2021. It intends to provide further insights into how NAMs can be gradually integrated into chemical risk assessment aimed at protection of human health, until eventually the current paradigm is replaced by an animal-free "Next Generation Risk Assessment" (NGRA).

G × E interactions as a basis for toxicological uncertainty

To transfer toxicological findings from model systems, e.g. animals, to humans, standardized safety factors are applied to account for intra-species and inter-species variabilities. An alternative approach would be to measure and model the actual compound-specific uncertainties. This biological concept assumes that all observed toxicities depend not only on the exposure situation (environment = E), but also on the genetic (G) background of the model (G × E). As a quantitative discipline, toxicology needs to move beyond merely qualitative G × E concepts. Research programs are required that determine the major biological variabilities affecting toxicity and categorize their relative weights and contributions. In a complementary approach, detailed case studies need to explore the role of genetic backgrounds in the adverse effects of defined chemicals. In addition, current understanding of the selection and propagation of adverse outcome pathways (AOP) in different biological environments is very limited. To improve understanding, a particular focus is required on modulatory and counter-regulatory steps. For quantitative approaches to address uncertainties, the concept of "genetic" influence needs a more precise definition. What is usually meant by this term in the context of G × E are the protein functions encoded by the genes. Besides the gene sequence, the regulation of the gene expression and function should also be accounted for. The widened concept of past and present "gene expression" influences is summarized here as Ge. Also, the concept of "environment" needs some re-consideration in situations where exposure timing (Et) is pivotal: prolonged or repeated exposure to the insult (chemical, physical, life style) affects Ge. This implies that it changes the model system. The interaction of Ge with Et might be denoted as Ge × Et. We provide here general explanations and specific examples for this concept and show how it could be applied in the context of New Approach Methodologies (NAM).

Systems bioengineering approaches for developmental toxicology

Developmental toxicology is the field of study that examines the effects of chemical and physical agents on developing organisms. By using principles of systems biology and bioengineering, a systems bioengineering approach could be applied to study the complex interactions between developing organisms, the environment, and toxic agents. This approach would result in a holistic understanding of the effects of toxic agents on organisms, by considering the interactions between different biological systems and the impacts of toxicants on those interactions. It would be useful in identifying key biological pathways and mechanisms affected by toxic agents, as well as in the development of predictive models to assess potential risks of exposure to toxicants during development. In this review, we discuss the relevance of systems bioengineering to the field of developmental toxicity and provide up-to-date examples that illustrate the use of engineering principles for this application.

Integrative Data Mining Approach: Case Study with Adverse Outcome Pathway Network Leading to Pulmonary Fibrosis

An adverse outcome pathway (AOP) framework can be applied as an efficient tool for the rapid screening of environmental chemicals. For the development of an AOP, a database mining approach can support an expert derivation approach by gathering a wider range of evidence than in a literature review. In this study, data from various databases were integrated and analyzed to supplement the AOP leading to pulmonary fibrosis by analyzing additional evidence using a data mining approach and establishing an application domain for chemicals. First, we collected chemicals, genes, and phenotypes that were studied and related to pulmonary fibrosis through the Comparative Toxicogenomics Database (CTD). CGPD-tetramers constructed by linking each related chemical, gene, phenotype, and disease can provide the basic components for the assembly of putative AOPs. Next, an AOP network was established by connecting eight existing AOPs for pulmonary fibrosis developed by expert derivation from the AOP Wiki. Finally, the pulmonary fibrosis AOP network was proposed by integrating the AOP network from AOP Wiki and the CGPD-tetramers from the CTD. To prioritize potential chemical stressors in the AOP network, 61 chemicals were ranked using the relevance of the chemical to the AOP and chemical exposure information from the CompTox Chemicals Dashboard. The approach proposed in this study can guide the utilization of available evidence from various databases as well as the literature in constructing AOP networks related to specific diseases.

Oligodendrogenesis and myelination tracing in a CRISPR/Cas9-engineered brain microphysiological system

Introduction

Oligodendrocytes (OLs) are the myelin-forming cells of the central nervous system (CNS). Although OLs can be differentiated from human-induced pluripotent stem cells (hiPSCs), the in vitro modeling of axon myelination in human cells remains challenging. Brain microphysiological systems (bMPS, e.g. organoids) are complex three-dimensional (3D) cultures that offer an ideal system to study this process as OLs differentiate in a more in vivo-like environment; surrounded by neurons and astrocytes, which support the myelination of axons.

Methods

Here, we take advantage of CRISPR/Cas9 technology to generate a hiPSC line in which proteolipid protein 1 (PLP1), an OLs marker, is tagged with super-fold GFP (sfGFP). While generating the PLP1-sfGFP reporter, we used reverse transfection and obtained higher Knock-In (KI) efficiency compared to forward transfection (61-72 vs. 46%).

Results

After validation of the KI and quality control of the PLP1-sfGFP line, selected clones were differentiated into bMPS, and the fidelity, specificity, and function of the tagged PLP protein were verified in this model. We tracked different stages of oligodendrogenesis in the verified lines based on PLP1-sfGFP+ cells' morphology, and the presence of PLP1-sfGFP surrounding axons during bMPS' differentiation. Finally, we challenged the bMPS with cuprizone and quantified changes in both the percentage of PLP1-sfGFP expressing cells and the intensity of GFP expression.

Discussion

This work demonstrates an efficient method for generating hiPSC KI lines and the description of a new 3D model to study OL differentiation, migration, and maturation both during in vitro neurodevelopment as well as in response to environmental chemicals or disease-associated stressors.

[Development of Microphysiological Systems (MPSs) Based on Microfluidic Technology for Drug Discovery in Japan]

Microphysiological systems (MPSs) based on microfluidic devices are attracting attention as an alternative cell assay platform to animal experiments in drug discovery. When we use microfluidic devices for cell culture, it is possible to experiment with various culture conditions that are difficult with conventional cell culture methods, such as fabrication of microstructures for cell placement, temporal and spatial control of liquid factors and adhesive conditions, and physical stimulation by flow and expansion/contraction. MPSs, which use microfluidic technology to construct the structure and function of physiological biological tissues and organs, are being commercialized and put to practical use worldwide with the entry of venture companies and pharmaceutical companies. Although research on the practical application of MPS in Japan has lagged far behind the efforts of Western countries, the Japan Agency for Medical Research and Development (AMED) launched the MPS Development and Research Project in FY2017 and established a system for MPS commercialization through industry-government-academia collaboration. The project is characterized by the formation of a consortium involving many researchers not only from academia but also from manufacturing and pharmaceutical companies with the aim of commercializing MPS devices. By FY2021, the final year of this project, several MPSs were successfully positioned in various stages of commercialization. This paper introduces two MPSs that the author was involved in commercializing in collaboration with domestic companies within the project.

The use of NAMs and omics data in risk assessment

The animal-centric approach so far predominantly employed in risk assessment has been questioned in recent years due to a number of shortcomings regarding performance, consistency, transferability of results, sustainability, costs and ethical reasons. Alternatives to animal testing, collectively termed NAMs, may have the potential to deliver sound, cost-effective, prompt and reliable information, but their regulatory acceptance has not been established yet. The main reasons behind this are mostly related to actual methodological obstacles, with particular reference to addressing complex endpoints such as repeated-dose toxicity, the issue of translating the concept of adversity to NAMs, and doubts of stakeholders about the level of chemical safety ensured by NAMs. With the aim of providing an updated view on major conceptual and methodological developments in the field of toxicology, a symposium and a workshop were organised by the German Federal Institute for Risk Assessment (Bundesinstitut für Risikobewertung, BfR) and Helmholtz Centre for Environmental Research on 15-17 November 2021 in Berlin. The conference, entitled 'Challenges in Public Health Protection in the 21st Century: New Methods, Omics and Novel Concepts in Toxicology' brought together eminent scientists with representatives from industry and regulatory authorities. The organisation, day-to-day operations and the reporting of the event main outcomes in a position paper were the main focus of the present EFSA EU-FORA work programme. Tasks pertaining to 'The use of NAMs and omics data in risk assessment' were implemented under the shared supervision of units 'Testing and Assessment Strategies Pesticides' and 'Effect-based Analytics and Toxicogenomics' of the German Federal Institute for Risk Assessment.

Microphysiological Systems Evaluation: Experience of TEX-VAL Tissue Chip Testing Consortium

Much has been written and said about the promise and excitement of microphysiological systems, miniature devices that aim to recreate aspects of human physiology on a chip. The rapid explosion of the offerings and persistent publicity placed high expectations on both product manufacturers and regulatory agencies to adopt the data. Inevitably, discussions of where this technology fits in chemical testing paradigms are ongoing. Some end-users became early adopters, whereas others have taken a more cautious approach because of the high cost and uncertainties of their utility. Here, we detail the experience of a public-private collaboration established for testing of diverse microphysiological systems. Collectively, we present a number of considerations on practical aspects of using microphysiological systems in the context of their applications in decision-making. Specifically, future end-users need to be prepared for extensive on-site optimization and have access to a wide range of imaging and other equipment. We reason that cells, related reagents, and the technical skills of the research staff, not the devices themselves, are the most critical determinants of success. Extrapolation from concentration-response effects in microphysiological systems to human blood or oral exposures, difficulties with replicating the whole organ, and long-term functionality remain as critical challenges. Overall, we conclude that it is unlikely that a rodent- or human-equivalent model is achievable through a finite number of microphysiological systems in the near future; therefore, building consensus and promoting the gradual incorporation of these models into tiered approaches for safety assessment and decision-making is the sensible path to wide adoption.

Replacement of animal testing by integrated approaches to testing and assessment (IATA): a call for in vivitrosi

Alternative methods to animal use in toxicology are evolving with new advanced tools and multilevel approaches, to answer from one side to 3Rs requirements, and on the other side offering relevant and valid tests for drugs and chemicals, considering also their combination in test strategies, for a proper risk assessment.While stand-alone methods, have demonstrated to be applicable for some specific toxicological predictions with some limitations, the new strategy for the application of New Approach Methods (NAM), to solve complex toxicological endpoints is addressed by Integrated Approaches for Testing and Assessment (IATA), aka Integrated Testing Strategies (ITS) or Defined Approaches for Testing and Assessment (DA). The central challenge of evidence integration is shared with the needs of risk assessment and systematic reviews of an evidence-based Toxicology. Increasingly, machine learning (aka Artificial Intelligence, AI) lends itself to integrate diverse evidence streams.In this article, we give an overview of the state of the art of alternative methods and IATA in toxicology for regulatory use for various hazards, outlining future orientation and perspectives. We call on leveraging the synergies of integrated approaches and evidence integration from in vivo, in vitro and in silico as true in vivitrosi.

Probabilistic risk assessment - the keystone for the future of toxicology

Safety sciences must cope with uncertainty of models and results as well as information gaps. Acknowledging this uncer-tainty necessitates embracing probabilities and accepting the remaining risk. Every toxicological tool delivers only probable results. Traditionally, this is taken into account by using uncertainty / assessment factors and worst-case / precautionary approaches and thresholds. Probabilistic methods and Bayesian approaches seek to characterize these uncertainties and promise to support better risk assessment and, thereby, improve risk management decisions. Actual assessments of uncertainty can be more realistic than worst-case scenarios and may allow less conservative safety margins. Most importantly, as soon as we agree on uncertainty, this defines room for improvement and allows a transition from traditional to new approach methods as an engineering exercise. The objective nature of these mathematical tools allows to assign each methodology its fair place in evidence integration, whether in the context of risk assessment, sys-tematic reviews, or in the definition of an integrated testing strategy (ITS) / defined approach (DA) / integrated approach to testing and assessment (IATA). This article gives an overview of methods for probabilistic risk assessment and their application for exposure assessment, physiologically-based kinetic modelling, probability of hazard assessment (based on quantitative and read-across based structure-activity relationships, and mechanistic alerts from in vitro studies), indi-vidual susceptibility assessment, and evidence integration. Additional aspects are opportunities for uncertainty analysis of adverse outcome pathways and their relation to thresholds of toxicological concern. In conclusion, probabilistic risk assessment will be key for constructing a new toxicology paradigm - probably!

Development of the SciRAP Approach for Evaluating the Reliability and Relevance of in vitro Toxicity Data

Efficient and successful integration of data generated from non-animal test methods must rely on reliable and relevant data. It is important therefore to develop tools and criteria that facilitate scientifically sound, structured, and transparent evaluation of reliability and relevance of in vitro toxicity data to efficiently inform regulatory hazard and risk assessment. The Science in Risk Assessment and Policy (SciRAP) initiative aims to promote such overarching goals. We present the work to develop and refine the SciRAP tool for evaluation of reliability and relevance of in vitro studies for incorporation on the SciRAP web-based platform (www.scirap.org). In the SciRAP approach, reliability evaluation is based on criteria for reporting quality and methodological quality, and is explicitly separated from relevance evaluation. The SciRAP in vitro tool (version 1.0) was tested and evaluated during an expert test round (April 2019-September 2020) on three in vitro studies by thirty-one experts from regulatory authorities, industry and academia from different geographical areas and with various degree of experience in in vitro research and/or human health risk assessment. In addition, the experts answered an online survey to collect their feedback about the general features and desired characteristics of the tool for further refinement. The SciRAP in vitro tool (version 2.0) was revised based on the outcome of the expert test round (study evaluation and online survey) and consists of 24 criteria for evaluating "reporting quality" (reliability), 16 criteria for "methodological quality" (reliability), and 4 items for evaluating relevance of in vitro studies. Participants were generally positive about the adequacy, flexibility, and user-friendliness of the tool. The expert test round outlined the need to (i) revise the formulation of certain criteria; (ii) provide new or revised accompanying guidance for reporting quality and methodological quality criteria in the "test compounds and controls," "test system," and "data collection and analysis" domains; and (iii) provide revised guidance for relevance items, as general measures to reduce inter-expert variability. The SciRAP in vitro tool allows for a structured and transparent evaluation of in vitro studies for use in regulatory hazard and risk assessment of chemicals.

Applicability of organ-on-chip systems in toxicology and pharmacology

Organ-on-chip (OoC) systems are microfabricated cell culture devices designed to model functional units of human organs by harboring an in vitro generated organ surrogate. In the present study, we reviewed issues and opportunities related to the application of OoC in the safety and efficacy assessment of chemicals and pharmaceuticals, as well as the steps needed to achieve this goal. The relative complexity of OoC over simple in vitro assays provides advantages and disadvantages in the context of compound testing. The broader biological domain of OoC potentially enhances their predictive value, whereas their complexity present issues with throughput, standardization and transferability. Using OoCs for regulatory purposes requires detailed and standardized protocols, providing reproducible results in an interlaboratory setting. The extent to which interlaboratory standardization of OoC is feasible and necessary for regulatory application is a matter of debate. The focus of applying OoCs in safety assessment is currently directed to characterization (the biology represented in the test) and qualification (the performance of the test). To this aim, OoCs are evaluated on a limited scale, especially in the pharmaceutical industry, with restricted sets of reference substances. Given the low throughput of OoC, it is questionable whether formal validation, in which many reference substances are extensively tested in different laboratories, is feasible for OoCs. Rather, initiatives such as open technology platforms, and collaboration between OoC developers and risk assessors may prove an expedient strategy to build confidence in OoCs for application in safety and efficacy assessment.

Drug Screening, Oral Bioavailability and Regulatory Aspects: A Need for Human Organoids

The intestinal epithelium critically contributes to oral bioavailability of drugs by constituting an important site for drug absorption and metabolism. In particular, intestinal epithelial cells (IEC) actively serve as gatekeepers of drug and nutrient availability. IECs' transport processes and metabolism are interrelated to the whole-body metabolic state and represent potential points of origin as well as therapeutic targets for a variety of diseases. Human intestinal organoids represent a superior model of the intestinal epithelium, overcoming limitations of currently used in vitro models. Caco-2 cells or rodent explant models face drawbacks such as their cancer and non-human origin, respectively, but are commonly used to study intestinal nutrient absorption, enterocyte metabolism and oral drug bioavailability, despite poorly correlative data. In contrast, intestinal organoids allow investigating distinct aspects of bioavailability including spatial resolution of transport, inter-individual differences and high-throughput screenings. As several countries have already developed strategic roadmaps to phase out animal experiments for regulatory purposes, intestinal organoid culture and organ-on-a-chip technology in combination with in silico approaches are roads to go in the preclinical and regulatory setup and will aid implementing the 3Rs (reduction, refinement and replacement) principle in basic science.

Application of the 3Rs principles in the development of pharmaceutical generics

Although the 3Rs are broadly applied in nonclinical testing, a better appreciation of the 3Rs is needed in the field of differentiated or value-added pharmaceutical generics because the minor changes in formulation, dosage form, indication, and application route often do not require additional safety testing. The US FDA and the EU EMA have comprehensive regulations for such drugs based on quality, therapeutic equivalence, and safety guidelines. However, no scientific publications on how the concept of replacement and reduction from 3Rs principles can be applied in the safety assessment of differentiated generics were found in the public domain. In this review, we discuss the application of 3Rs in nonclinical testing requirements for differentiated generics. Practical examples are provided in the form of case studies from regulated markets. We highlight the need for utilization of existing data to establish equivalence (differentiated generic vs innovator) in efficacy and safety. The case studies indicate that data requirements from animal experiments have been reduced to a large extent in some major markets without compromising quality and safety. In this context, we also highlight the problem that on a global scale, a true reduction of animal experiments will only be achieved when all countries adopt similar practices.

The Challenges of 21st Century Neurotoxicology: The Case of Neurotoxicology Applied to Nanomaterials

After a short background discussing engineered nanomaterials (ENMs) and their physicochemical properties and applications, the present perspective paper highlights the main specific points that need to be considered when examining the question of neurotoxicity of nanomaterials. It underlines the necessity to integrate parameters, specific tools, and tests from multiple sources that make neurotoxicology when applied to nanomaterials particularly complex. Bringing together the knowledge of multiple disciplines e.g., nanotoxicology to neurotoxicology, is necessary to build integrated neurotoxicology for the third decade of the 21st Century. This article focuses on the greatest challenges and opportunities offered by this specific field. It highlights the scientific, methodological, political, regulatory, and educational issues. Scientific and methodological challenges include the determination of ENMs physicochemical parameters, the lack of information about protein corona modes of action, target organs, and cells and dose– response functions of ENMs. The need of standardization of data collection and harmonization of dedicated neurotoxicological protocols are also addressed. This article highlights how to address those challenges through innovative methods and tools, and our work also ventures to sketch the first list of substances that should be urgently prioritized for human modern neurotoxicology. Finally, political support with dedicated funding at the national and international levels must also be used to engage the communities concerned to set up dedicated educational program on this novel field.

Advanced 3D Cell Culture Techniques in Micro-Bioreactors, Part II: Systems and Applications

In this second part of our systematic review on the research area of 3D cell culture in micro-bioreactors we give a detailed description of the published work with regard to the existing micro-bioreactor types and their applications, and highlight important results gathered with the respective systems. As an interesting detail, we found that micro-bioreactors have already been used in SARS-CoV research prior to the SARS-CoV2 pandemic. As our literature research revealed a variety of 3D cell culture configurations in the examined bioreactor systems, we defined in review part one “complexity levels” by means of the corresponding 3D cell culture techniques applied in the systems. The definition of the complexity is thereby based on the knowledge that the spatial distribution of cell-extracellular matrix interactions and the spatial distribution of homologous and heterologous cell–cell contacts play an important role in modulating cell functions. Because at least one of these parameters can be assigned to the 3D cell culture techniques discussed in the present review, we structured the studies according to the complexity levels applied in the MBR systems.

Biology-inspired microphysiological systems to advance patient benefit and animal welfare in drug development

The first microfluidic microphysiological systems (MPS) entered the academic scene more than 15 years ago and were considered an enabling technology to human (patho)biology in vitro and, therefore, provide alternative approaches to laboratory animals in pharmaceutical drug development and academic research. Nowadays, the field generates more than a thousand scientific publications per year. Despite the MPS hype in academia and by platform providers, which says this technology is about to reshape the entire in vitro culture landscape in basic and applied research, MPS approaches have neither been widely adopted by the pharmaceutical industry yet nor reached regulated drug authorization processes at all. Here, 46 leading experts from all stakeholders - academia, MPS supplier industry, pharmaceutical and consumer products industries, and leading regulatory agencies - worldwide have analyzed existing challenges and hurdles along the MPS-based assay life cycle in a second workshop of this kind in June 2019. They identified that the level of qualification of MPS-based assays for a given context of use and a communication gap between stakeholders are the major challenges for industrial adoption by end-users. Finally, a regulatory acceptance dilemma exists against that background. This t4 report elaborates on these findings in detail and summarizes solutions how to overcome the roadblocks. It provides recommendations and a roadmap towards regulatory accepted MPS-based models and assays for patients' benefit and further laboratory animal reduction in drug development. Finally, experts highlighted the potential of MPS-based human disease models to feedback into laboratory animal replacement in basic life science research.

Antidepressant Paroxetine Exerts Developmental Neurotoxicity in an iPSC-Derived 3D Human Brain Model

Selective serotonin reuptake inhibitors (SSRIs) are frequently used to treat depression during pregnancy. Various concerns have been raised about the possible effects of these drugs on fetal development. Current developmental neurotoxicity (DNT) testing conducted in rodents is expensive, time-consuming, and does not necessarily represent human pathophysiology. A human, in vitro testing battery to cover key events of brain development, could potentially overcome these challenges. In this study, we assess the DNT of paroxetine—a widely used SSRI which has shown contradictory evidence regarding effects on human brain development using a versatile, organotypic human induced pluripotent stem cell (iPSC)-derived brain model (BrainSpheres). At therapeutic blood concentrations, which lie between 20 and 60 ng/ml, Paroxetine led to an 80% decrease in the expression of synaptic markers, a 60% decrease in neurite outgrowth and a 40–75% decrease in the overall oligodendrocyte cell population, compared to controls. These results were consistently shown in two different iPSC lines and indicate that relevant therapeutic concentrations of Paroxetine induce brain cell development abnormalities which could lead to adverse effects.

Toward Rigorous Materials Production: New Approach Methodologies Have Extensive Potential to Improve Current Safety Assessment Practices

Advanced material development, including at the nanoscale, comprises costly and complex challenges coupled to ensuring human and environmental safety. Governmental agencies regulating safety have announced interest toward acceptance of safety data generated under the collective term New Approach Methodologies (NAMs), as such technologies/approaches offer marked potential to progress the integration of safety testing measures during innovation from idea to product launch of nanomaterials. Divided in overall eight main categories, searchable databases for grouping and read across purposes, exposure assessment and modeling, in silico modeling of physicochemical structure and hazard data, in vitro high-throughput and high-content screening assays, dose-response assessments and modeling, analyses of biological processes and toxicity pathways, kinetics and dose extrapolation, consideration of relevant exposure levels and biomarker endpoints typify such useful NAMs. Their application generally agrees with articulated stakeholder needs for improvement of safety testing procedures. They further fit for inclusion and add value in nanomaterials risk assessment tools. Overall 37 of 50 evaluated NAMs and tiered workflows applying NAMs are recommended for considering safer-by-design innovation, including guidance to the selection of specific NAMs in the eight categories. An innovation funnel enriched with safety methods is ultimately proposed under the central aim of promoting rigorous nanomaterials innovation.

Microphysiological lung models to evaluate the safety of new pharmaceutical modalities: a biopharmaceutical perspective

The lung is a complex organ; it is both the initial barrier for inhaled agents and the site of metabolism and therapeutic effect for a subset of systemically administered drugs. Comprised of more than 40 cell types that are responsible for various important functions, the lung's complexity contributes to the subsequent challenges in developing complex in vitro co-culture models (also called microphysiological systems (MPS), complex in vitro models or organs-on-a-chip). Although there are multiple considerations and limitations in the development and qualification of such in vitro systems, MPS exhibit great promise in the fields of pharmacology and toxicology. Successful development and implementation of MPS models may enable mechanistic bridging between non-clinical species and humans, and increase clinical relevance of safety endpoints, while decreasing overall animal use. This article summarizes, from a biopharmaceutical industry perspective, essential elements for the development and qualification of lung MPS models. Its purpose is to guide MPS developers and manufacturers to expedite MPS utilization for safety assessment in the biopharmaceutical industry.

Predicting toxicity of chemicals: software beats animal testing

We created earlier a large machine-readable database of 10,000 chemicals and 800,000 associated studies by natural language processing of the public parts of Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) registrations until December 2014. This database was used to assess the reproducibility of the six most frequently used Organisation for Economic Co-operation and Development (OECD) guideline tests. These tests consume 55% of all animals in safety testing in Europe, i.e. about 600,000 animals. With 350-750 chemicals with multiple results per test, reproducibility (balanced accuracy) was 81% and 69% of toxic substances were found again in a repeat experiment (sensitivity 69%). Inspired by the increasingly used read-across approach, we created a new type of QSAR, which is based on similarity of chemicals and not on chemical descriptors. A landscape of the chemical universe using 10 million structures was calculated, when based on Tanimoto indices similar chemicals are close and dissimilar chemicals far from each other. This allows placing any chemical of interest into the map and evaluating the information available for surrounding chemicals. In a data fusion approach, in which 74 different properties were taken into consideration, machine learning (random forest) allowed a fivefold cross-validation for 190,000 (non-) hazard labels of chemicals for which nine hazards were predicted. The balanced accuracy of this approach was 87% with a sensitivity of 89%. Each prediction comes with a certainty measure based on the homogeneity of data and distance of neighbours. Ongoing developments and future opportunities are discussed.

Emerging Role of Organ-on-a-Chip Technologies in Quantitative Clinical Pharmacology Evaluation

The recently enacted Prescription Drug User Fee Act (PDUFA) VI includes in its performance goals "enhancing regulatory science and expediting drug development." The key elements in "enhancing regulatory decision tools to support drug development and review" include "advancing model-informed drug development (MIDD)." This paper describes (i) the US Food and Drug Administration (FDA) Office of Clinical Pharmacology's continuing efforts in developing quantitative clinical pharmacology models (disease, drug, and clinical trial models) to advance MIDD, (ii) how emerging novel tools, such as organ-on-a-chip technologies or microphysiological systems, can provide new insights into physiology and disease mechanisms, biomarker identification and evaluation, and elucidation of mechanisms of adverse drug reactions, and (iii) how the single organ or linked organ microphysiological systems can provide critical system parameters for improved physiologically-based pharmacokinetic and pharmacodynamic evaluations. Continuous public-private partnerships are critical to advance this field and in the application of these new technologies in drug development and regulatory review.

A Human iPSC-derived 3D platform using primary brain cancer cells to study drug development and personalized medicine

A high throughput histology (microTMA) platform was applied for testing drugs against tumors in a novel 3D heterotypic glioblastoma brain sphere (gBS) model consisting of glioblastoma tumor cells, iPSC-derived neurons, glial cells and astrocytes grown in a spheroid. The differential responses of gBS tumors and normal neuronal cells to sustained treatments with anti-cancer drugs temozolomide (TMZ) and doxorubicin (DOX) were investigated. gBS were exposed to TMZ or DOX over a 7-day period. Untreated gBS tumors increased in size over a 4-week culture period, however, there was no increase in the number of normal neuronal cells. TMZ (100 uM) and DOX (0.3 uM) treatments caused ~30% (P~0.07) and ~80% (P < 0.001) decreases in the size of the tumors, respectively. Neither treatment altered the number of normal neuronal cells in the model. The anti-tumor effects of TMZ and DOX were mediated in part by selective induction of apoptosis. This platform provides a novel approach for screening new anti-glioblastoma agents and evaluating different treatment options for a given patient.

A Human iPSC-derived 3D platform using primary brain cancer cells to study drug development and personalized medicine

A high throughput histology (microTMA) platform was applied for testing drugs against tumors in a novel 3D heterotypic glioblastoma brain sphere (gBS) model consisting of glioblastoma tumor cells, iPSC-derived neurons, glial cells and astrocytes grown in a spheroid. The differential responses of gBS tumors and normal neuronal cells to sustained treatments with anti-cancer drugs temozolomide (TMZ) and doxorubicin (DOX) were investigated. gBS were exposed to TMZ or DOX over a 7-day period. Untreated gBS tumors increased in size over a 4-week culture period, however, there was no increase in the number of normal neuronal cells. TMZ (100 uM) and DOX (0.3 uM) treatments caused ~30% (P~0.07) and ~80% (P < 0.001) decreases in the size of the tumors, respectively. Neither treatment altered the number of normal neuronal cells in the model. The anti-tumor effects of TMZ and DOX were mediated in part by selective induction of apoptosis. This platform provides a novel approach for screening new anti-glioblastoma agents and evaluating different treatment options for a given patient.

A Human iPSC-derived 3D platform using primary brain cancer cells to study drug development and personalized medicine

A high throughput histology (microTMA) platform was applied for testing drugs against tumors in a novel 3D heterotypic glioblastoma brain sphere (gBS) model consisting of glioblastoma tumor cells, iPSC-derived neurons, glial cells and astrocytes grown in a spheroid. The differential responses of gBS tumors and normal neuronal cells to sustained treatments with anti-cancer drugs temozolomide (TMZ) and doxorubicin (DOX) were investigated. gBS were exposed to TMZ or DOX over a 7-day period. Untreated gBS tumors increased in size over a 4-week culture period, however, there was no increase in the number of normal neuronal cells. TMZ (100 uM) and DOX (0.3 uM) treatments caused ~30% (P~0.07) and ~80% (P < 0.001) decreases in the size of the tumors, respectively. Neither treatment altered the number of normal neuronal cells in the model. The anti-tumor effects of TMZ and DOX were mediated in part by selective induction of apoptosis. This platform provides a novel approach for screening new anti-glioblastoma agents and evaluating different treatment options for a given patient.

Microglia Increase Inflammatory Responses in iPSC-Derived Human BrainSpheres

Human induced pluripotent stem cells (iPSCs), together with 21st century cell culture methods, have the potential to better model human physiology with applications in toxicology, disease modeling, and the study of host-pathogen interactions. Several models of the human brain have been developed recently, demonstrating cell-cell interactions of multiple cell types with physiologically relevant 3D structures. Most current models, however, lack the ability to represent the inflammatory response in the brain because they do not include a microglial cell population. Microglia, the resident immunocompetent phagocytes in the central nervous system (CNS), are not only important in the inflammatory response and pathogenesis; they also function in normal brain development, strengthen neuronal connections through synaptic pruning, and are involved in oligodendrocyte and neuronal survival. Here, we have successfully introduced a population of human microglia into 3D human iPSC-derived brain spheres (BrainSpheres, BS) through co-culturing cells of the Immortalized Human Microglia – SV40 cell line with the BS model (μBS). We detected an inflammatory response to lipopolysaccharides (LPS) and flavivirus infection, which was only elicited in the model when microglial cells were present. A concentration of 20 ng/mL of LPS increased gene expression of the inflammatory cytokines interleukin-6 (IL-6), IL-10, and IL-1β, with maximum expression at 6–12 h post-exposure. Increased expression of the IL-6, IL-1β, tumor necrosis factor alpha (TNF-α), and chemokine (C-C motif) ligand 2 (CCL2) genes was observed in μBS following infection with Zika and Dengue Virus, suggesting a stronger inflammatory response in the model when microglia were present than when only astrocyte, oligodendrocyte, and neuronal populations were represented. Microglia innately develop within cerebral organoids (Nature communications)¹, our findings suggest that the μBS model is more physiologically relevant and has potential applications in infectious disease and host-pathogen interactions research.

The Emergence of Microphysiological Systems (Organs-on-chips) as Paradigm-changing Tools for Toxicologic Pathology

Microphysiological systems (MPS), commonly known as organs-on-chips, are a rapidly advancing technology that promises to impact many areas of medical and toxicological pathology. In this minireview, the history of MPS and its potential utility in safety assessment are described with the toxicologic pathologist in mind. Several MPS development focus areas are defined, and recent progress in the area is highlighted. MPS will likely become an important tool for the toxicologic pathologist as part of our role in the safety assessment process within the pharmaceutical, biotechnology, medical device, and cosmetic and agrichemical industries.

Machine Learning of Toxicological Big Data Enables Read-Across Structure Activity Relationships (RASAR) Outperforming Animal Test Reproducibility

Earlier we created a chemical hazard database via natural language processing of dossiers submitted to the European Chemical Agency with approximately 10 000 chemicals. We identified repeat OECD guideline tests to establish reproducibility of acute oral and dermal toxicity, eye and skin irritation, mutagenicity and skin sensitization. Based on 350-700+ chemicals each, the probability that an OECD guideline animal test would output the same result in a repeat test was 78%-96% (sensitivity 50%-87%). An expanded database with more than 866 000 chemical properties/hazards was used as training data and to model health hazards and chemical properties. The constructed models automate and extend the read-across method of chemical classification. The novel models called RASARs (read-across structure activity relationship) use binary fingerprints and Jaccard distance to define chemical similarity. A large chemical similarity adjacency matrix is constructed from this similarity metric and is used to derive feature vectors for supervised learning. We show results on 9 health hazards from 2 kinds of RASARs-"Simple" and "Data Fusion". The "Simple" RASAR seeks to duplicate the traditional read-across method, predicting hazard from chemical analogs with known hazard data. The "Data Fusion" RASAR extends this concept by creating large feature vectors from all available property data rather than only the modeled hazard. Simple RASAR models tested in cross-validation achieve 70%-80% balanced accuracies with constraints on tested compounds. Cross validation of data fusion RASARs show balanced accuracies in the 80%-95% range across 9 health hazards with no constraints on tested compounds.