Toxicity Testing in the 21st Century: A Vision and a Strategy

The approaches to quantitatively assessing the health risks of chemical exposure have not changed appreciably in the past 50 to 80 years, the focus remaining on high-dose studies that measure adverse outcomes in homogeneous animal populations. This expensive, low-throughput approach relies on conservative extrapolations to relate animal studies to much lower-dose human exposures and is of questionable relevance to predicting risks to humans at their typical low exposures. It makes little use of a mechanistic understanding of the mode of action by which chemicals perturb biological processes in human cells and tissues. An alternative vision, proposed by the U.S. National Research Council (NRC) report Toxicity Testing in the 21st Century: A Vision and a Strategy, called for moving away from traditional high-dose animal studies to an approach based on perturbation of cellular responses using well-designed in vitro assays. Central to this vision are (a) “toxicity pathways” (the innate cellular pathways that may be perturbed by chemicals) and (b) the determination of chemical concentration ranges where those perturbations are likely to be excessive, thereby leading to adverse health effects if present for a prolonged duration in an intact organism. In this paper we briefly review the original NRC report and responses to that report over the past 3 years, and discuss how the change in testing might be achieved in the U.S. and in the European Union (EU). EU initiatives in developing alternatives to animal testing of cosmetic ingredients have run very much in parallel with the NRC report. Moving from current practice to the NRC vision would require using prototype toxicity pathways to develop case studies showing the new vision in action. In this vein, we also discuss how the proposed strategy for toxicity testing might be applied to the toxicity pathways associated with DNA damage and repair.

BACKGROUND: The Ayurvedic concept of Ama refers to the accumulation of incompletely digested or metabolized substances in the body due to impaired Agni (digestive fire). Ama is described as a pathological entity that disrupts systemic homeostasis, leading to chronic metabolic and immune disorders. Modern medical science recognizes similar pathological processes, such as endotoxin accumulation, gut dysbiosis, metabolic endotoxemia, and inflammatory responses driven by advanced glycation end-products (AGEs), damage-associated molecular patterns, and oxidative stress. Despite advances in research and clinical interventions, metabolic and immune disorders like diabetes, metabolic dysfunction-associated fatty liver disease, inflammatory bowel disease, and autoimmune conditions continue to rise globally. Expanding the scope of Ama and its subtypes in relation to these disorders may provide novel insights for disease prevention, diagnostics, and therapeutic approaches. EXISTING KNOWLEDGE AND GAP: Ayurvedic texts elaborate on Ama as a primary etiological factor in disease progression, classifying it based on its origins, affinity, and systemic translocation. However, there is a lack of standardized clinical assessment tools to evaluate Ama in the context of modern disease models. Current biomedical research highlights the crucial role of gut health, intestinal permeability, microbial dysbiosis, and metabolic endotoxemia in the development of chronic diseases. Despite these parallels, there is minimal integrative research correlating Ama with measurable biochemical or molecular markers. Moreover, the role of Ama in immune activation and inflammatory disorders remains largely unexplored within a scientific framework. PROPOSED CONCEPT: This paper proposes an expanded classification of Ama , integrating Ayurvedic epistemology with modern biomedical understanding. Ama can be characterized as a gut-derived response antigen complex or gut-associated molecular complex, which includes toxic metabolites, undigested peptides, microbial toxins, and inflammatory mediators resulting from impaired digestion and absorption. The subtypes of Ama can be categorized based on the site of expression, cause of origin, specificity or affinity, Kaal , and its movement or translocation. Modern tools such as metabolomics, proteomics, transcriptomics, and computational systems biology models can be employed to validate Ama and its subtypes. Biomarkers such as HbA1c (paralleling Ama in diabetes), lipid oxidation markers, gut microbiome alterations, and inflammatory cytokines may serve as objective correlates of Ama . WAY FORWARD: Future research should focus on developing standardized clinical scales for Ama assessment, incorporating radiological, biochemical, molecular, and genetic markers. Systems biology approaches, such as network pharmacology and artificial intelligence-based predictive models, should be utilized to map the progression of Ama in metabolic and immune disorders. Ayurvedic interventions, such as Deepana, Pachana , and Shodhana therapies, should be studied for their impact on gut barrier function, microbiome modulation, and immune homeostasis. Bridging Ayurvedic concepts with modern scientific methodologies will enable the development of personalized diagnostic and therapeutic strategies for chronic diseases.

Computational Modeling of Protein Networks Predicts Treatment Outcomes in Multiple Myeloma (MM)

In the 2007 report Toxicity Testing in the 21st Century: A Vision and a Strategy, the U.S. National Academy of Sciences envisioned a major transition in toxicity testing from cumbersome, expensive, and lengthy in vivo testing with qualitative endpoints, to in vitro robotic high-throughput screening with mechanistic quantitative parameters. Recognizing the need for agencies to partner and collaborate to ensure global harmonization, standardization, quality control and information sharing, the U.S. Environmental Protection Agency is leading by example and has established an intra-agency Future of Toxicity Testing Workgroup (FTTW). This workgroup has produced an ambitious blueprint for incorporating this new scientific paradigm to change the way chemicals are screened and evaluated for toxicity. Four main components of this strategy are discussed, as follows: (1) the impact and benefits of various types of regulatory activities, (2) chemical screening and prioritization, (3) toxicity pathway-based risk assessment, and (4) institutional transition. The new paradigm is predicated on the discovery of molecular perturbation pathways at the in vitro level that predict adverse health effects from xenobiotics exposure, and then extrapolating those events to the tissue, organ, or whole organisms by computational models. Research on these pathways will be integrated and compiled using the latest technology with the cooperation of global agencies, industry, and other stakeholders. The net result will be that chemical toxicity screening will become more efficient and cost-effective, include real-world exposure assessments, and eliminate currently used uncertainty factors.

Distinguishing adaptive from adverse responses is fundamental to understanding toxicity and to implementing regulatory guidelines that are protective of human health. However, what we consider to be an adverse effect may change over time as the cultural acceptance of risk alters and new knowledge and insight accumulate. The fact that the identification of an adverse effect is subject to change is obvious, necessary, and uncomfortable. In this commentary, a framework for defining adverse effects is proposed for the emerging paradigm of toxicity testing in the 21st century-a paradigm that focuses on human cells, in vitro approaches, toxicity pathways, and high-throughput techniques. The traditional meaning of an adverse effect as a change at the organismal level is not compatible with this new system of toxicity testing. Instead, based on the experience of accident investigators, we propose that a Toxicological Factors Analysis and Classification System will use the database resulting from the high-throughput toxicity testing of the future to develop a Taxonomy of Adverse Effects. Similar to an accident, predisposing "latent failures" identified within categories of the toxicant response database will be associated with the "active failure" of an adverse effect.

In 2007, the U.S. National Academy of Sciences, National Research Council (NRC), issued the report Toxicity Testing in the 21st Century: A Vision and a Strategy. This report, which was commissioned by the U.S. Environmental Protection Agency (EPA), called for the U.S. EPA to develop a new approach for how this agency evaluates the toxicity of compounds. The report recommended that the agency move from its current testing system, which is based largely on traditional toxicology, to a testing system that is based primarily on human cell lines and in vitro systems. Successful implementation of the report's vision and strategy will require that scientists, lawyers, and policymakers work together to bridge the gap among disciplines. An important step in building this bridge requires an analysis of the U.S. legal system that frames toxicity testing. If the U.S. laws, regulations, and policies erect barriers that would prevent or impede the U.S. EPA adoption of the NRC vision and strategy, it is important to identify these challenges. At the same time, if existing laws, regulations, and policies are fertile ground for these recommendations, opportunities should be documented. This article discusses and evaluates the challenges and opportunities that arise under key provisions of one major U.S. toxics law, the Toxics Substances Control Act (TSCA).

In this article I address the interactions between biological knowledge and ideas about the kinds of entity that are suited to appropriation. I start by arguing that commodification and reductionism are closely linked, and that patenting suits entities that are discrete and isolable, such as those that are the focus of molecular biology. I then turn to the new field of systems biology, which recognizes that traditional reductionist approaches to biology are no longer adequate and attempts to provide a more integrative understanding of biological systems. In doing this, systems biology has to deal with emergent phenomena. But patenting does not suit the dynamic and interactive complexity that is the object of study in systems biology. If systems biology rejects reductionism where does that leave commodification? I examine attempts to commodify predictive computational models in systems biology. I then turn to systems biology's sister discipline, synthetic biology, which deals with emergence by reducing the complexity of biological systems. By factoring out messy contingencies, synthetic biology is, in theory, well suited to commodification. Drawing on both these examples I explore how ideas about appropriation, including open source, are influencing the nature and course of research in biology.

Correction to: Addressing barriers in comprehensiveness, accessibility, reusability, interoperability and reproducibility of computational models in systems biology.

The biological process and molecular functions involved in the cancer progression remain difficult to understand for biologists and clinical doctors. Recent developments in high-throughput technologies urge the systems biology to achieve more precise models for complex diseases. Computational and mathematical models are gradually being used to help us understand the omics data produced by high-throughput experimental techniques. The use of computational models in systems biology allows us to explore the pathogenesis of complex diseases, improve our understanding of the latent molecular mechanisms, and promote treatment strategy optimization and new drug discovery. Currently, it is urgent to bridge the gap between the developments of high-throughput technologies and systemic modeling of the biological process in cancer research. In this review, we firstly studied several typical mathematical modeling approaches of biological systems in different scales and deeply analyzed their characteristics, advantages, applications, and limitations. Next, three potential research directions in systems modeling were summarized. To conclude, this review provides an update of important solutions using computational modeling approaches in systems biology.

Toxicology in the 21st century – Working our way towards a visionary reality

A Study to Predict Response to Azacitidine or Lenalidomide/Azacitidine Combination Therapy in MDS and AML Patients Using a Computational Biological Modeling (CBM) Approach

The toxicology community is in the midst of a paradigm shift, moving from high-dose testing in animals with extrapolation to expected responses in humans to an in vitro approach based on a mechanistic understanding of key toxicity pathways. Tools such as cell-based assays that interrogate specific toxicity pathways, multi-omics technologies, bioinformatics, and computational systems modelling enable deeper understanding of human biology at the molecular level. Integration of these tools provides a powerful new approach to toxicity testing. The tools and technologies used in toxicity testing platforms are continuously emerging, evolving, and being applied in novel ways. The goal of this article is to: 1) describe recently emerged technologies; 2) highlight advances in various existing platforms; 3) provide relevant examples of how these platform components are currently being applied in toxicity testing; 4) discuss advantages and limitations of each platform and identify gaps where further developments are required.

Toxicity testing typically involves studying adverse health outcomes in animals subjected to high doses of toxicants with subsequent extrapolation to expected human responses at lower doses. The low-throughput of current toxicity testing approaches (which are largely the same for industrial chemicals, pesticides and drugs) has led to a backlog of more than 80,000 chemicals to which human beings are potentially exposed whose potential toxicity remains largely unknown. Employing new testing strategies that employ the use of predictive, high-throughput cell-based assays (of human origin) to evaluate perturbations in key pathways, referred as pathways of toxicity, and to conduct targeted testing against those pathways, we can begin to greatly accelerate our ability to test the vast 'storehouses' of chemical compounds using a rational, risk-based approach to chemical prioritization and provide test results that are more predictive of human toxicity than current methods. The NIH Transformative Research Grant project Mapping the Human Toxome by Systems Toxicology aims at developing the tools for pathway mapping, annotation and validation as well as the respective knowledge base to share this information.

Hypomethylating agents (HMA) and lenalidomide (LEN) are approved and used in the treatment of patients (pts) with MDS, though these drugs fail in most pts. No method exists to predict drug response beyond associating single actionable mutations with a single drug's response. We hypothesized that MDS pts can be clustered by similarities in genomic/molecular profiles, & that each cluster may be assigned combos of FDA-approved drugs to target their unique biomarker profile. Bone marrow cells from 88 MDS pts & the MDS-L cell line were analyzed by cytogenetics & for mutations in 14 myeloid genes using NGS. 31 pts had sufficient data for analysis. 20 profiles had similar aberrations & were grouped. Genomic data from pts and MDS-L were entered into a computational biology modeling (CBM) software, which generates a disease-specific protein network map using PubMed to create digital models and identify characteristic biomarkers unique to each pt. An algorithm was created to cluster the models based on overlapping disease-specific biomarkers. Digital drug simulations (DDS) were conducted both on MDS-L & pt simulation models by quantitatively measuring drug effect on a cell growth score (CGS), a composite of cell proliferation, viability & apoptosis. DDS identified drugs by assessing their impact on disease-specific biomarkers and calculated CGSs. Predictions were validated using MTT. 14/31 MDS pt profiles, including the MDS-L cell line, clustered into 4 groups based on biomarker characteristics.MDS-L cells harbor NRAS (G12A) mutation,-7,-12,+1,+8,+19,+20 and +21. Genes associated with increased copy number (CN) include AURKA, IGFR, PAR5, MTOR, IL6, JAK3, MDM4, MYC, MCL1, COX2, PDE4A, and RCE1; genes associated with decreased CN include DUSP1, RASA1, NR3C1, IRF1, ETV6, and SHH. CBM identified active biomarkers in MDS-L cells (90RSK, MAPK7, AKT and BTK), validated by western blot. DDS predicted nelfinavir+celecoxib to be effective in MDS-L. MDS-L cells were treated with nelfinavir, celecoxib, and nelfinavir+celecoxib with increasing doses. Nelfinavir & celecoxib reduced MDS-L viability in a dose-dependent manner, while nelfinavir+celecoxib showed additive reduction of MDS-L viability. DDS was performed on each pt to predict response to HMA and LEN. Two of the clusters (n=2/cluster) were predicted to be non-responders to any SOC therapy. A third cluster (n=3) was predicted to respond to HMA, but not LEN, and the fourth cluster (n=6) showed varying or no response to either HMA/LEN. These results use a novel concept of using genomics & CBM to cluster profiles with overlapping disease-relevant biomarkers & similar drug response predictions. CBM can identify pt populations who may benefit from certain therapeutic regimens, improving response rates, & give insights into the mechanisms by which each drug impacts the MDS-specific biomarkers Citation Format: Leylah M. Drusbosky, Kimberly E. Hawkins, Amy Meacham, Elizabeth Wise, Neeraj Kumar Singh, Chandan Kumar, Sumanth M. Vasista, Rakhi P. Suseela, Taher Abbasi, Shireen Vali, Kaoru Tohyama, Maher Albitar, Peter P. Sayeski, Christopher R. Cogle. Genomics-driven clustering of disease-related biomarkers identifies therapeutic options in myelodysplastic syndromes (MDS) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4285.

MatTek Corporation has been working diligently for over 15 years to replace traditional animal-based toxicity and efficacy tests with alternative test methods based on human-cell derived, three-dimensional (3-D) tissue models. First discussed in detail by W.M.S. Russell and R.L. Burch 50 years ago in their book, The Principles of Humane Experimental Technique, and now fully integrated into forward-looking publications such as Toxicity Testing in the 21st Century: A Vision and a Strategy, the concept of replacing animals in test procedures with human cells and/or human cell-derived in vitro 3-D tissues is being embraced by the world's research scientists and toxicologists at an ever-increasing rate. 3-D in vitro models are being utilised not only for humanitarian reasons, but also because human 3-D tissues, in particular, produce more-physiologically relevant scientific data. Early on in MatTek's efforts to develop this alternative test method, senior management sought the assistance of experts within the in vitro testing and animal rights communities, to help define the specific in vitro human 3-D tissue products needed and navigate the regulatory landscape, especially in Europe where the replacement of animal-based testing with non-animal alternative test methods was well underway. MatTek was fortunate to receive that expert assistance on both fronts from Professor Michael Balls, who at that time was the newly-elected first director of ECVAM. In 1997, with the guidance and support of Professor Balls and others in the animal rights community, MatTek began the effort to validate several of its human 3-D tissue-based alternative test methods. Today, two MatTek human cell-derived 3-D tissue-based test methods are validated as full replacements for existing animal-based tests, with more tests in the validation pipeline. In addition, MatTek in vitro tissue models are in use worldwide by chemical, pharmaceutical and consumer product companies, as evidenced by citations in hundreds of patents and scientific articles from these industries. This article concludes with MatTek's thoughts on the direction that human 3-D tissue-based in vitro testing will take in the future.