Journal of the American Association for Laboratory Animal Science Copyright 2015 by the American Association for Laboratory Animal Science

Vol 54, No 2 March 2015 Pages 214–223

Predicting the Future: Opportunities and Challenges for the Chemical Industry to Apply 21st-Century Toxicity Testing Raja S Settivari*, Nicholas Ball, Lynea Murphy, Reza Rasoulpour, Darrell R Boverhof, and Edward W Carney Interest in applying 21st-century toxicity testing tools for safety assessment of industrial chemicals is growing. Whereas conventional toxicology uses mainly animal-based, descriptive methods, a paradigm shift is emerging in which computational approaches, systems biology, high-throughput in vitro toxicity assays, and high-throughput exposure assessments are beginning to be applied to mechanism-based risk assessments in a time- and resource-efficient fashion. Here we describe recent advances in predictive safety assessment, with a focus on their strategic application to meet the changing demands of the chemical industry and its stakeholders. The opportunities to apply these new approaches is extensive and include screening of new chemicals, informing the design of safer and more sustainable chemical alternatives, filling information gaps on data-poor chemicals already in commerce, strengthening read-across methodology for categories of chemicals sharing similar modes of action, and optimizing the design of reduced-risk product formulations. Finally, we discuss how these predictive approaches dovetail with in vivo integrated testing strategies within repeated-dose regulatory toxicity studies, which are in line with 3Rs principles to refine, reduce, and replace animal testing. Strategic application of these tools is the foundation for informed and efficient safety assessment testing strategies that can be applied at all stages of the product-development process. Abbreviations: EOGRTS, extended one-generation reproductive toxicity study; EU, European Union; MoA, mode of action; OECD, Organisation for Economic Cooperation and Development; QSAR, quantitative structure activity relationship; REACH, Registration, Evaluation, Authorization, and Restriction of Chemicals.

Since its beginnings, chemical safety assessment has been built around a core of standardized hazard identification tests conducted in whole-animal models. These tests generally involve the administration of high doses of test chemicals to animals, which then are observed for adverse effects. These tests continue to serve as the main approach for identifying potential hazards of chemicals and providing dose–response data to inform risk assessment and risk management. Although this approach generally has served the chemical industry and its stakeholders well, a number of technologic, societal, and industry trends are driving the creation of a new paradigm in chemical safety assessment. These trends include the explosion in systems biology, computational biology, and high-throughput assay development that has led to an enhanced understanding of toxicology pathways, that is, sets of key mechanistic events that are thought to play a causal role leading to the expression of adverse effects. Societal desire to decrease or eliminate the use of animals in testing is increasing and has even culminated in bans on animal testing by some regulatory agencies (for example, the 7th Amendment to the European Union [EU] Cosmetics Directive). In recent years, much attention has been placed on data-poor chemicals that are already in commerce and may have potential contributions to human diseases. Many of these have been evaluated based on extrapolation from structurally related compounds that have robust toxicity data, using an approach known as ‘read-across.’ Likewise, in the case of new chemical

Received: 13 Mar 2014. Revision requested: 27 May 2014. Accepted: 26 Aug 2014. Toxicology and Environmental Research and Consulting, The Dow Chemical Company, Midland, Michigan. *Corresponding author. Email: [email protected]

development, there is increased interest to incorporate safety assessment earlier in the development process, to increase the chances of developing products that are both efficacious and less toxic. As a result of these trends and changes in stakeholder expectations, a new paradigm often referred to as ‘Toxicity Testing in the 21st Century,’ or simply ‘Predictive Safety Assessment,’ has emerged. In predictive safety assessment, an integrated suite of in vitro, molecular, and biochemical assays is combined with cheminformatics approaches to predict the likelihood of adverse effects occurring under various exposure scenarios (Figure 1 ; Table 1). Cheminformatics refers to mathematical, chemical, structural, and statistical modeling tools to predict chemical effects on human health or the environment. This approach integrates all relevant information on a compound and its structural or substructural analogs to make preliminary assessments of potential toxicity. The structure-based (quantitative structure– activity relationship [QSAR]) prediction approach is among the first developed and most commonly used cheminformatics tools for safety assessment. Cheminformatics also involves qualitative identification of structural alerts, read-across through the identification and assessment of closely related analogs of the target chemical, and advanced data mining techniques to identify putative modes of action (MoA). In vitro biologic profiling includes the use of 2- or 3D cell models that comprise relevant morphologic and biochemical signaling processes and are designed as either one-to-one replacements of existing in vivo assays or as tools to specifically evaluate mechanistic processes, which underlie adverse effects.9 Several in vitro assays have already been developed and are accepted by regulatory authorities for predicting relatively simple

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Figure 1. Application of predictive toxicology tools and in vivo integrated testing strategies at different stages of product development. NA, not applicable.

Table 1. Comparison of predictive and conventional toxicology approaches. Predictive toxicology approaches In silico approach

In vitro biologic profiling

Conventional testing approaches

Test systems

Computational

Predominantly cell- and molecular-based

Animal-based testing

Animal usage

Not applicable

None to minimal

Extensive

$

$$

$$$$

Days

Days to weeks

Months to years Grams to kilograms

Expense (per chemical) Study duration Test material requirement

None

Micrograms to milligrams

Throughput

Moderate to high

Moderate to high

Low

Dose levels

Not applicablea

Many (5 to 10) dose levels

Typically 3

aExceptions

include physiologically based pharmacokinetic modeling and virtual tissue models

endpoints (Table 2). However, given the reductionist nature of in vitro assays, these models are less suitable for addressing more complex biologic endpoints (for example, developmental toxicity, repeat-dose toxicity). To address this limitation, integrated testing strategies are applied, where a series of computational, biochemical, and in vitro tools are applied to predict perturbations in key events leading to an adverse outcome (for example, skin sensitization).41,45 In the case of complex endpoints for which the mechanism is not well characterized (for example, reproductive toxicity), a combination of in silico, high-content ‘omics,’ and bioinformatics approaches are applied to delineate broader mechanistic pathways.22,31,32,40,42,54,73,82,86,95,96 In addition to its use for generating mechanistic information, omics profiling has been applied to classify chemicals into different toxicity classes for read-across purposes.87,97 Recently, metabolite profiling has been proposed for early identification of toxicologic MoA and for read-across purposes.88 High-throughput screening is another common predictive tool, in which large numbers of chemicals are tested by using simple biochemical or in vitro assays to query their effects on a single biologic response.73 For example, the US Environmental Protection Agency’s ToxCast program has screened nearly 2000 chemicals in more than 700 high-throughput screening assays (http://www.epa.gov/ncct/ toxcast).29,93 The National Toxicology Program of the National Institute of Environmental Health Sciences is currently testing a library of more than 8100 chemicals, each in approximately 70 assays at 15 concentrations per chemical.1,85 The millions of data points generated by these approaches are modeled by using high-end computational tools and network models for efficient safety characterization and for prioritizing chemicals for more comprehensive testing.27,78 Recently, there have been increasing calls to complement hazard characterization with

exposure assessment, to prioritize chemicals based on ‘risk.’84,91 The ExpoCast program implements multiple simple to complex high-throughput computational models to predict chemical exposures. When the ToxCast data were complemented with ExpoCast values, a chemical prioritization outcome very different from that based on hazard information alone emerged. This analysis suggests that human exposures to about 90% of the ToxCast chemicals fall several orders of magnitude below the lowest concentration eliciting a response.77,92 Many of the tools of predictive safety assessment were developed initially for the pharmaceutical industry, and the needs of the chemical industry often call for different approaches in the application of these tools (Table 3). For example, product development pipelines for new chemical products often are focused on a small number of candidates that are preselected to achieve specific functional properties in the final products (for example, surfactant, chelant, heat-transfer agent); in comparison, the pharmaceutical industry might screen hundreds or thousands of candidates selected for action on a human biologic target. Another major difference between chemical and drugsafety assessment is that human exposures to most chemicals are often many orders of magnitude lower than the doses required to cause toxicity.6,20,83 As mentioned, such exposure data can be incorporated into exposure-based prioritization schemes. Now that we have described some of the tools of predictive toxicology as well as the unique needs for assessing the safety of chemicals, we next describe the strategic application of predictive tools to meet the challenges facing the modern chemical industry (Figure 1). Herein, we review application of predictive toxicology tools for the assessment of new chemicals and sustainable alternatives and for the assessment of chemicals already in commerce. Finally, we describe in vivo integrated 215

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Table 2. In vitro assays aligned to regulatory guideline required endpoints. Toxicity endpoints Eye corrosion or irritation

In vitro or alternative assays Bovine corneal opacity and permeability test (OECD 437) Isolated chicken eye test (OECD 438) Fluorescein leakage test method for identifying ocular corrosives and severe irritants (OECD 460) Neutral red release assay33,91,98 EpiOcular 3D corneal assay28

Skin corrosion or irritation

In vitro membrane barrier test method for skin corrosion (OECD 435) In vitro skin corrosion: reconstructed human epidermis (RHE) test method (OECD 431) In vitro skin corrosion: transcutaneous electrical resistance test method (OECD 430) In vitro skin irritation: reconstructed human epidermis test method (OECD 439)

Skin sensitization

KeratinoSens assay;55,56 direct peptide reactivity assay19,57

Acute toxicity to fish

Zebrafish embryo acute toxicity test (OECD 236)

Developmental toxicity

Zebrafish developmental toxicity assay21,69,70,81

Endocrine disruption

BG1Luc estrogen receptor transactivation test method for identifying estrogen receptor agonists and antagonists (OECD 457) H295R steroidogenesis assay assays (OECD 456) Amphibian metamorphosis assay (OECD 231) Androgen receptor activation assay94

Liver toxicity

Nuclear receptor screen in primary liver cells30,44

Genetic toxicity

Bacterial reverse mutation test (OECD 471) In vitro mammalian chromosomal aberration test (OECD 473) In vitro mammalian cell gene mutation test (OECD 476) In vitro mammalian cell micronucleus test (OECD 487)

Skin absorption

Skin absorption: In vitro method (OECD 428)

Phototoxicity

3T3 neutral red uptake phototoxicity test (OECD 432)

testing strategies, which reduce overall animal use and are consistent with 3Rs principles.

Assessment of New Chemicals and Sustainable Alternatives

The chemical industry produces a diverse array of products that typically are sold to downstream businesses, which in turn transform them into finished products supplying various major market sectors, such as agriculture, electronics, transportation, housing and construction, home and personal care, energy, and so forth. In general, new chemicals are created and developed to perform highly specific and demanding functions, which affect the performance of the final product. Examples include automotive plastics that maintain structural integrity but are light and therefore improve fuel economy, materials used to make cell phone displays shine brightly yet use less electricity, and a crop-protection compound that targets a specific fungus but biodegrades rapidly. With today’s emphasis on sustainability, human safety and environmental considerations are being incorporated earlier in new-product research and development, from initial molecular design to ‘stage gate’ advancement decisions. In addition, ‘sustainable alternatives assessments’ are increasingly being performed in an effort to replace existing chemicals

that possess certain hazardous properties with compounds that still perform the desired functions but have a lower risk profile. Finding this balance is often a highly challenging endeavor and may require new tools to assess the safety side of the equation. During the early stages of new chemical development, the need is to conduct a preliminary evaluation of new candidates from which 1 or 2 are selected for further development. Testing strategies at such early stages usually involves a tiered testing approach, with interim decision points or ‘stage gates’ for further advancement of the molecule.89 The process (tier 1) begins with cheminformatics, which includes the collection and evaluation of any existing toxicity information for the chemical being evaluated as well as toxicity data on structurally related analogs. This effort is accompanied by QSAR predictions (global or local prediction models) to identify structural alerts and to generate hypotheses on toxicity and putative MoA (Figure 2). The cheminformatics approach serves well to estimate potential toxicity at such early stages where the amount of chemical available for testing can be quite small or even none (that is, only chemical structures are available), and the chemicals often have never been tested in animals. The subsequent tier in the testing strategy may involve targeted in vitro assays, which are selected based on the putative MoA and alerts identified in the first tier. This assessment may

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Table 3. Comparison of safety assessment in the pharmaceutical and chemical industries. Pharmaceutical Industry

Chemical industry

Humans

Plants, pests, insects; generally no intended human target

Low- and high-throughput screening;

Low-throughput (due to smaller pipeline);

high-content screening

high-content screening

Close to human intended use

Several magnitudes higher than potential human exposure

Human clinical trials

Generally no human testinga

False positives

Abandon promising compound

Potential marketing bans

False negatives

Potential to identify during clinical trial

Postmarketing concerns

Primary target of drug or chemical

Preferred screening

Testing dose concentrations

Testing in humans

aTargeted

testing for cosmetic and personal-care products

Figure 2. A tiered toxicity assessment approach for testing new chemicals.

include either a single or a battery of in vitro assays, depending on the complexity of the hypothesized endpoint. Many companies in the chemical industry use in vitro assays aligned to diverse endpoints including skin sensitization, skin and eye irritation, dermal absorption, genetic toxicity, endocrine activation, phototoxicity, acute toxicity to fish, and so forth (Table 2). Examples of the potential application of these in vitro tools are the development of new sustainable formulations, during which in vitro approaches typically are used to obtain toxicity information for various coformulants that have never been tested in animals (that is, fill the data gap), to test various combinations of coformulants for hazard potential to design the formulations with reduced toxicity, and to develop

‘sustainable’ formulations. Chemicals advancing through the first 2 tiers usually move on to regulatory-guideline–required in vivo studies, which can be further customized based on the information gleaned from earlier tiers. One example of a tiered approach includes the evaluation of new chemicals for skin sensitization potential, which is an important component of the safety evaluation process. The initial key step in the sensitization process includes a covalent interaction between an electrophilic moiety on the chemical sensitizer and a nucleophilic moiety on endogenous skin protein (that is, electrophilic reaction). In tier 1 of the tiered testing strategy, cheminformatics tools are applied for advanced data mining on the structurally related compounds and to evaluate 217

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for the presence of electrophilic moieties on the compound structure and substructures. This task is accompanied by predictions to evaluate the nature of electrophilic reactions (that is, soft- or hard-electrophile–nucleophile interaction) and potential outcomes of such reaction.49 The putative MoA and nature of alerts identified in tier 1 provide insight into selecting the most appropriate in vitro testing approach in tier 2. For example, the KeratinoSens assay is the preferred approach for chemicals that exhibit soft-electrophilic interaction, whereas a Direct Peptide Reactivity Assay is selected for chemicals that exhibit both types of interactions.19,55-57 Considering the complexity of the sensitization process, often the in vitro approaches are applied in combinations (integrated testing strategy), and a weight-of-evidence approach is considered for improved prediction.24,58,60,74 The in vivo studies are implemented for the purpose of confirming results from in vitro studies and for dose–response characterization.

Assessment of Chemicals Already in Commerce

Another major challenge that the chemical industry faces regards pressures to address the so-called ‘toxics information gap.’39 This term refers to the assertion by the National Academy of Science in 1984 that for 82% of chemicals in commerce there was no toxicity information available.59 Thirty years later, the perception—accurate or not—remains that there is minimal toxicologic information on the vast number of chemicals in commerce. In addition, identifying and removing hazardous chemicals from the market and replacing them with safer alternatives has become a key aspect of chemical management programs such as the EU REACH regulation and an impetus for the reform of Toxic Substances Control Act in the United States. Taking together these 2 issues leads to the situation today, where there is a desire to extensively characterize the hazards and assess the risks of all chemicals in commerce. A theoretical solution to address this issue is simply to increase conventional toxicity testing; however, considering the current regulatory framework that places heavy emphasis on hazard characterization as well as the number of chemicals in commerce, this option is unrealistic. To provide perspective on the magnitude of the challenge, the estimated costs and animal usage for the REACH program alone are as high as €9 billion and 54 million vertebrate animals, respectively.76 This animal-intensive approach has also been adopted in several other regulatory regions across Asia Pacific, including China, South Korea, and Taiwan. Therefore a significant challenge to the chemical industry and regulatory community exists: how can we generate the information to support the safe use of chemicals without resorting to extensive and resource intensive toxicology programs? With the rapid advancements in 21st-century toxicity approaches, regulatory agencies as well as external stakeholders are looking toward predictive toxicology approaches, such as the use of cheminformatics, validated in vitro assays, and the grouping of substances into categories to support the use of read-across to improve the quantity and quality of information on these chemicals and thereby to fill the data gaps.47 Of these approaches, the grouping of substances into categories and the use of read-across offers significant opportunities to reduce the need for new animal-based toxicologic studies. The prediction of hazard using read-across has been described elsewhere14,62,63 and involves the formation of a category of substances or a small group of analogs that share structural

similarities. The principal underlying the use of read-across is essentially the same as that used by QSAR tools, namely, that the activity of the substance is related to its structure. Therefore substances with similar structures or containing the same functional groups are hypothesized to have similar toxicity or to follow predictable toxicologic trends. The formation of chemical categories and use of read-across played an important role in addressing the data requirements of the Organisation for Economic Cooperation and Development’s (OECD) high-production–volume screening assessment program, which comprises more than 100 chemical categories covering more than 400 substances assessed to date. With the more recent implementation of the EU REACH regulation, read-across has continued to play a key role in the hazard characterization of substances registered, with read-across accounting for approximately one-third of all data submitted.16,17 In the Asia Pacific region, several countries (for example, Korea, Taiwan) are adopting REACH-like chemical regulation frameworks that, like the EU REACH regulations, allow the use of read-across of data between structurally similar substances to address the data requirements. Not all regions and regulatory frameworks are as accepting of the use of categories and read-across as are the EU and OECD member countries. For example, the current new substance regulation in China does not permit the use of read-across unless there are exceptional circumstances preventing the testing of the substance being registered.50 However, the chemical regulations within China continue to evolve, and it is hoped that the acceptance of alternative approaches to address data requirements, particularly the use of read-across, will feature more prominently in future regulatory frameworks. The existence of the many regulatory situations where the use of read-across has been permitted or actively promoted does not mean that hazard assessments based on the use of read-across are always accepted. The acceptance of the use of read-across by regulatory agencies therefore depends on the strength of the justification underpinning it. As such, perhaps the greatest challenge faced when using read-across is providing robust scientific justification for why read-across between analogs or within a category is acceptable and likely to be associated with minimal uncertainty in the prediction. It is insufficient to simply state that 2 substances contain the same functional groups and therefore will have similar toxicologic profiles because many examples exist in which subtle differences in structure between substances sharing the same functional groups lead to significant differences in toxicity, whether in type of effect or potency.14 There have been several recent attempts to provide additional information and guidance on how to assess and address the uncertainty associated with the use of read-across. The European Chemicals Agency has developed an exemplary case study to illustrate how to build justification for read-across and is finalizing a Read-Across Assessment Framework that will guide more consistent assessment of whether the use of read-across is acceptable or not.17,72 A recent report from the European Center for Ecotoxicology and Toxicology of Chemicals on category approaches and read-across also provides guidance on using read-across within a category or a small group of analogs and identifying and addressing uncertainty.14,71 A proposed framework for identifying suitable analogs from which to read across data formed the basis of a more recent framework for identifying and characterizing uncertainty associated with read-across.3,95 In this recent framework, the issue of uncertainty in the use of read-across is addressed by the use of uncertainty factors (1, 3, or 10), allowing the use of read across to be accepted and a subsequent risk assessment performed even in cases where there

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are minimal data supporting the read-across justification. Another possibility for using these tools to reduce the uncertainty associated with read-across is to build them into an integrated testing strategy and to make use of Bayesian networks in a ‘Bayesian Network Integrated Testing Strategy’.25 Using such an approach enables the quantification of uncertainty from heterogeneous input sources, assessment of relationships between them, and creation of a testing strategy that targets the reduction of uncertainty.26 An alternative approach to strengthening read-across justifications and reducing uncertainty is to consider the use of read-across in the context of the broader 21st-century toxicity testing paradigm. It is apparent that the formation of categories or groups of analogs based on structural similarities complements the use of the broad array of predictive toxicology tools and that these can provide support for the justification that underpins the use of read-across within the category. For example, when forming a category of substances, several in silico tools and frameworks are available to assist in the identification of analogs or category members and to provide preliminary predictions of hazards.14,95 In vitro screening assays such as cytotoxicity, protein reactivity, oral bioavailability, and receptorbinding assays can be used to demonstrate the similar behavior of category members, identify potential differences in potency (and therefore trends in toxicity), and highlight areas of potential concern where more extensive testing may be justified. These assays allow initial assessment of the overall toxicologic profile of a group of substances without the need for extensive animal test methods. In addition, the data from these assays can be used in conjunction with traditional toxicology studies to assess whether category members follow an adverse outcome pathway for a particular endpoint, thereby providing a mechanistic basis for the use of read-across.66 However, given the high specificity of adverse outcome pathways for a particular apical endpoint, their utility in supporting read-across for multiple endpoints is currently challenging, although new read-across frameworks are being developed that compare profiles of untested chemicals to ontologies of profiles for reference chemicals, which act via known adverse outcome pathways.95,96 Furthermore, the use of toxicogenomics or metabolomics provides a means to conduct global analysis of the biologic activity (large number of mechanisms) of structurally related chemicals and thus may serve to refine the structure activity relationship (SAR)-based predictions and the use of read-across. Toxicogenomic approaches have a history of use in the characterization of MoA for industrial and environmental chemicals.53 Recent studies clearly suggest that the assessment of gene expression by using in vitro models provides comparable results to in vivo models. Therefore, it is reasonable to use in vitro models to rapidly identify mechanisms of action of toxicants; this application provides further support for the grouping of substances without resorting to extensive in vivo studies.36,51,52,90 Other approaches to improving the assessment of data-poor chemicals already in commerce include the work of the US Environmental Protection Agency and other organizations which are implementing high-throughput programs (ToxCast, Tox21) to profile chemicals for biologic activity.27 In addition, programs such as ExpoCast are generating high-throughput exposure data to complement the ToxCast data for risk-based prioritization of chemicals.92 Recently, Thomas and colleagues proposed a data-driven risk-based framework that involves successive tiers of toxicity testing with margin of exposure as the primary metric.84 In this framework, the first tier of toxicity testing consists of applying high-throughput in vitro assays

(for example, ToxCast assays). Chemicals with small margins of exposure would be given high priority for progression to the next tier. The subsequent toxicity testing would consist of shorter-term and longer-term in vivo assays in tiers 2 and 3, respectively. In this approach, only a subset of chemicals would potentially be progressed to in vivo testing. The advantage of this framework is that application of high-throughput screening to dose–response evaluations at environmentally relevant concentrations generates reliable information on the chemical’s potential adverse health outcomes and reduces the time and resources needed to characterize the data-poor chemicals in commerce. For those chemicals that proceed to higher tiers of testing, the use of categories and read-across can still apply, and any new studies performed can be designed such that they maximize the amount of data generated, either by addressing multiple endpoints or supporting an MoA assessment.

In Vivo Integrated Testing and MoA Strategies

Traditionally, in vivo chemical safety assessments have used a series of separate regulatory guideline-mandated toxicity studies to investigate metabolism, acute toxicity, systemic toxicity, genetic toxicity, immunotoxicity, neurotoxicity, developmental and reproductive toxicity, and carcinogenicity in mammalian systems and to assess acute and chronic toxicity to the environment. A trophic level approach is considered to evaluate environmental toxicity, which includes investigating toxicity to algae, invertebrates, and fish. Although these studies are critical for the characterization of potential hazard and are required for the risk assessment of new chemicals, this approach is also labor-, time-, and animal-intensive. In line with 3R principles, a recent approach has been the implementation of integrated testing strategies, which allow for analysis of these endpoints, along with toxicokinetics and MoA, within a single toxicity study design.9,11 As an example for agrochemical safety assessments, the 90-d repeated-dose toxicity study (OECD 408) can be a critical regulatory requirement for agrochemical registration because it can be a key study for setting acceptable operator exposure levels and it provides valuable information regarding subchronic toxicity that is used for dose-level selection in the subsequent carcinogenicity study in rats.2,5,11,13,61 This study, along with the 28-d repeated-dose toxicity study (OECD 407), are key examples of study designs amenable to an integrated testing strategy, because multiple endpoints, including immune, genetic toxicity, neurotoxicity, toxicokinetics, and MoA endpoints, can be included in these studies.64 Toxicokinetic, MoA immune (T-cell dependent antibody response), and genetic toxicity (micronucleus) endpoints have been integrated into repeated-dose toxicity studies, and results have clearly indicated that these endpoints can be assessed appropriately within a single study.12,34,35,37,80 In particular, a recent study indicated that measurement of general, immune (T-cell dependent antibody response) and genetic (micronucleus) toxicity endpoints are compatible with each other and supports the integration of these endpoints onto a single repeated-dose study.80 The integrated study design in a repeated-dose toxicity study results markedly reduces animal use compared with that of the stand-alone guideline studies as well as decreases time and cost. Another example of refining animal use through the integration of relevant endpoints is the extended one-generation reproductive toxicity study (EOGRTS, OECD test guideline 443). This new study design uses less than half the number of animals as does the 2-generation reproductive toxicity study (OECD 416), which is a regulatory requirement for agrochemical safety 219

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assessment and has recently been accepted for evaluation of reproductive toxicity under REACH.11,67,68 EOGRTS focuses on in-depth analysis of the F1 generation and includes options for cohort groups to investigate developmental neurotoxicity and immunotoxicity.11,18,68 A recent publication on the 2,4-dichlorophenoxyacetic acid (2,4-D) EOGRTS estimated an animal use of approximately 6000 animals if reproductive and developmental (neurotoxicity and immunotoxicity), systemic, and endocrine toxicity endpoints had been evaluated separately compared with the approximately 1600 animals used in the EOGRTS.43 Along with the OECD 443 test guideline, multiple regulatory guidelines and guidance documents reference the use of toxicokinetic data in dose-level selection for carcinogenicity (OECD 451, OECD GD 116) and repeated-dose studies (REACH Chapter R. 7c 2008). 65,68 When considering 3R principles, further application of the integration of toxicokinetics into toxicity studies supports read-across arguments to waive additional in vivo testing; this approach could be strengthened dramatically by the addition of toxicokinetic data to provide information regarding systemic exposure and metabolism of the chemical(s) in question and to determine the bioequivalence of related chemicals. The value of integrated toxicokinetic data to aid in the overall understanding of the toxicity profile cannot be overlooked. The integration of toxicokinetics into toxicity studies (for example, palatability, 28-and 90-d repeated dose, developmental, reproductive, chronic and carcinogenicity studies) allows for the assessment of systemic exposure without additional animal use.79 The availability of kinetic data from short-term and subchronic toxicity studies earlier during testing supports the use of kinetically derived maximum doses in dose-level selection for subsequent studies and may result in toxicity studies that are conducted at dose levels in the linear kinetic range but that avoid saturation of kinetic processes at nonlinear, high dose levels.46,79 Integrated testing strategies can be applied to MoA assessments and can provide supporting data for MoA endpoints (that is, target organ or developmental and reproductive toxicity) that can be incorporated into the required guideline studies without delaying the original timeframe for the safety assessment.7,8,75 MoA assessments of rodent liver tumors are a specific example of the use of integrated testing strategies, because many chemicals potentially can induce rodent liver tumors and because characterization of the MoA can be critical for human health risk assessments. This type of evaluation involves the determination of specific key events (cellular, molecular, or biochemical changes) that occur in a dose-responsive and temporal manner and thus support the proposed MoA.4,23,48 Once the MoA is established, the question of human relevance of the specific MoA can be evaluated.4 Further supporting the application of integrated testing strategies, studies to determine MoA for rodent liver effects can be initiated prior to the completion of the carcinogenicity studies.37 One area with great potential for application to inform MoA evaluations is the use of in vitro profiling assays. Nuclear receptor activation can be an initial molecular event for in vivo rodent liver tumorigenesis.10 Primary hepatocytes are a relevant in vitro assay, because they possess nuclear receptors and are capable of metabolism, components that are absent or dramatically reduced in most continuously cultured cell lines.30,38,44 Using primary hepatocytes as an in vitro predictive toxicology profiling assay may provide a preliminary indication of nuclear receptor activation and allow for cross-species comparisons, because there are several species, including rat, mouse, and human, from which primary hepatocytes are commercially

available. These data can be used to inform subsequent integration of MoA endpoints, such as the inclusion of liver weight, liver histopathology, liver gene expression, and recovery groups, into in vivo regulatory studies as they allow earlier initiation of studies using technologies such as knockout or humanized rodent models to investigate the human relevance of the identified MoA. Although in vivo integrated testing strategies reduce animal use, time, and cost for results, efforts are ongoing to evaluate the compatibility of these endpoints within a single study design and to ensure that each of the endpoints can be evaluated and interpreted appropriately. In addition, fulfilling the individual guideline(s) for added endpoints such as genetic toxicity and immunotoxicity can be challenging, considering that these guidelines specify different durations of exposure, route of administration, and criteria for achieving an acceptably high dose level.

Summary

Predictive toxicology tools are constantly evolving and have great potential to provide valuable mechanistic information on and to predict the toxicity of a wide array of endpoints, which can be used for molecular design, lead optimization, and development of sustainable alternatives. Although this is an exciting prospect, it is imperative to acknowledge assay-specific limitations (including chemical applicability domain and metabolic competence of the system) when making use of these tools. An additional ongoing challenge is to integrate the use of the predictive tools, whenever possible, into strategies (for example, read-across) that provide a robust hazard characterization of existing chemicals in commerce as they reduce or eliminate the need for additional in vivo studies. Given that in vivo studies are still required for safety assessments from the regulatory perspective, the chemical industry has the demanding task of continuing to advance the science of safety assessments to include relevant predictive toxicology approaches and integrated testing strategies with a focus on replacement, refinement, and reduction of animal use as it ultimately adheres to the guidelines and regulatory requirements set forth. In this review, we have outlined the demands and expectations for applying predictive toxicology tools by using examples specific to the chemical industry to illustrate how these tools can be used for current as well as future applications. It is hoped that continuing to develop predictive toxicology capabilities will decrease the dependence of chemical safety and risk assessment on animal and resource intensive studies and increase the use of highthroughput approaches that are more relevant to human safety without being overly conservative.

Acknowledgment

We thank Dr. Craig Rowlands and Dr. Barun Bhhatarai (Dow Chemical Company) for critical review of the manuscript Dr. Edward W. Carney (1959–2015) has long been a champion for the 3Rs of animal use—reduce, refine, and replace—at The Dow Chemical Company. For many years, Ed fostered integrated study designs to consolidate multiple endpoints into a single study to reduce animal use. He was an advocate of the kinetically derived maximum dose (KMD) as a way to refine animal dosing and ensure that resulting data were relevant for risk assessment. In recent years, he crafted a vision to markedly reduce the number of animals used in toxicity testing by using 21st-century toxicology tools for a more strategic approach to product safety assessments. Toward this goal, Ed launched Dow’s Predictive Toxicology Platform. This program was developed through Ed’s ingenuity, intelligence, and ability to effectively interact with scientists from regulatory agencies, research

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organizations, industry partners, and nongovernmental organizations. Dow’s new program is a testament to Ed’s forward-thinking passion for effecting scientific change. As we at Dow move forward to implement his vision, we hope that our accomplishments will be a legacy that would make Ed proud.

References

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