or reproductive toxicity.

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Contents lists available at ScienceDirect

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A strategy for safety assessment of chemicals with data gaps for developmental and/or reproductive toxicity Karen Blackburn a,⇑, George Daston a, Joan Fisher a, Cathy Lester a, Jorge M. Naciff a, Echoleah S. Rufer b, Sharon B. Stuard a, Kara Woeller c a b c

Central Product Safety Department, The Procter & Gamble Company, Mason Business Center, 8700 Mason Montgomery Road, Cincinnati, OH 45040, United States Central Product Safety Department, The Procter & Gamble Company, Sharon Woods Innovation Center, 11530 Reed Hartman Highway, Cincinnati, OH 45241, United States Central Product Safety Department, The Procter & Gamble Company, Winton Hill Business Center, 6110 Center Hill Avenue, Cincinnati, OH 45224, United States

a r t i c l e

i n f o

Article history: Received 3 March 2015 Available online xxxx Keywords: Risk assessment Uncertainty factors Developmental toxicity Reproductive toxicity

a b s t r a c t Alternative methods for full replacement of in vivo tests for systemic endpoints are not yet available. Read across methods provide a means of maximizing utilization of existing data. A limitation for the use of read across methods is that they require analogs with test data. Repeat dose data are more frequently available than are developmental and/or reproductive toxicity (DART) studies. There is historical precedent for using repeat dose data in combination with a database uncertainty factor (UF) to account for missing DART data. We propose that use of the DART decision tree (Wu et al., 2013), in combination with a database UF, provides a path forward for DART data gap filling that better utilizes all of the data. Our hypothesis was that chemical structures identified by the DART tree as being related to structures with known DART toxicity would potentially have lower DART NOAELs compared to their respective repeat dose NOAELs than structures that lacked this association. Our analysis supports this hypothesis and as a result also supports that the DART decision tree can be used as part of weight of evidence in the selection of an appropriate DART database UF factor. Ó 2015 Elsevier Inc. All rights reserved.

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41 42

1. Background

43

Read across is one actionable alternative to fill data gaps for developmental and reproductive toxicity (DART) endpoints (Wu et al., 2010). However, in our experience many chemicals lack sufficient analog DART data to support read across assessments. On the other hand, a subset of chemicals that lack DART data have repeat dose toxicity information. This is in part due to the absence of explicit requirements for DART testing of cosmetic ingredients (Adler et al., 2011) and the high tonnage triggers for DART testing in the European Union (European Chemicals Agency, 2014). As such, a repeat dose test may be the only in vivo systemic toxicity test data available for a chemical that has not undergone extensive evaluation. We do not see the approach proposed here to address DART data gaps as limited to cosmetic ingredients; however, our work was stimulated by the combination of the animal testing ban in the European Union for cosmetic ingredients, combined with our observations regarding the availability of repeat dose data

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⇑ Corresponding author. E-mail address: [email protected] (K. Blackburn).

for chemicals that lack either DART data or adequate analogs for read across. There is a long history of using repeat dose toxicity data as a part of the weight of evidence to establish acceptable exposures to chemicals even in the absence of specific studies to address the DART potential of the compound of interest. This is based on the premise that the no observed adverse effect levels (NOAELs) for both developmental and reproductive effects are in general correlated with the NOAEL for repeat dose endpoints. Ritter et al. (2007) summarize the use of database UFs (sometimes called modifying factors) by authoritative bodies. In addition to the US EPA factors discussed below, they note that World Health Organization (WHO) and Health Canada have recommended a default factor of up to 10 for assessments based on incomplete datasets, including missing DART studies. Mitchell et al. (2004) summarized best practices for reproductive and developmental toxicity risk assessment for chemicals for Naval personnel as developed by the National Research Council. They concluded that ‘‘In cases in which the data set is incomplete or insufficient, evaluators should assume that susceptibility to reproductive or developmental toxicity may be greater than susceptibility to any known toxicity of the agent, and apply additional uncertainty

http://dx.doi.org/10.1016/j.yrtph.2015.04.006 0273-2300/Ó 2015 Elsevier Inc. All rights reserved.

Please cite this article in press as: Blackburn, K., et al. A strategy for safety assessment of chemicals with data gaps for developmental and/or reproductive toxicity. Regul. Toxicol. Pharmacol. (2015), http://dx.doi.org/10.1016/j.yrtph.2015.04.006

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factors to reflect the degree of uncertainty attributable to missing data’’. Specific numerical values were not suggested. The use of a database uncertainty factor to account for the lack of reproductive and/or developmental toxicity data, as applied by the US Environmental Protection Agency’s (EPA) IRIS (Integrated Risk Information System), is reviewed in US EPA (2002a). In contrast to registration programs (e.g., EPA FIFRA (Federal Insecticide Fungicide and Rodenticide Act) for pesticides), IRIS reviews begin with an assessment of available data in the public domain, rather than mandating required testing. The resulting risk assessments do not equate to regulatory statutes which are implemented through the US EPA’s program offices. As such, the reviews are weight of the evidence based, rather than regulatory study check list based, and are not targeted to chemicals used in specific industries or applications. The US EPA rationale is discussed in more detail here than the other precedent policies because there is a more extensive published supporting rationale: From US EPA (2011a) ‘‘The database UF is intended to account for the potential for deriving an under protective RfD/RfC as a result of an incomplete characterization of the chemical’s toxicity. In addition to identifying toxicity information that is lacking, review of existing data may also suggest that a lower reference value might result if additional data were available. Consequently, in deciding to apply this factor to account for deficiencies in the available data set and in identifying its magnitude, the assessor should consider both the data lacking and the data available for particular organ systems as well as life stages. . . . If the RfD/RfC is based on animal data, a factor of 3 is often applied if either a prenatal toxicity study or a two-generation reproduction study is missing, or a factor of 10 may be applied if both are missing (Dourson et al., 1996)’’. Dourson et al. (1992) examined the use of the database UF by analyzing ratios of NOAELs for chronic dog, rat, and mouse studies and reproductive and developmental toxicity studies in rats and rabbits. They concluded that DART studies provide useful information for establishing the lowest NOAEL for a chemical and if one or more studies are missing a factor should be used to address this additional uncertainty. Dourson et al. (1996) noted that investigation of NOAEL ratios from chronic dog, mouse and rat studies and DART studies in rats generally yielded similar values, but that for some chemicals availability and use of the DART data for the risk assessment would have resulted in a more conservative point of departure than the repeat dose data, hence the recommendation for the application of a database UF. Additional evaluations of the relationship between repeat dose NOAELs and DART NOAELs outside of the context of specific authoritative body recommendations are summarized in the subsequent paragraphs. Gadagbui (2005) expanded on the work of Dourson et al. (1996) by examining NOAELs from 150 chemicals for chronic toxicity, developmental and reproductive toxicity. This compilation included studies from dogs, rats, mice (chronic studies) and rabbits, mice and rats (reproductive and developmental) with the dataset heavily represented by pesticides. The analysis of these data is through the lens of pesticides, presuming that a complete dataset would include tests in a minimum of two species for each endpoint. In agreement with previous work, a relationship between repeat dose and DART NOAELs was supported. It is becoming clearer that many chemicals are quite non-selective hitting many targets at similar doses, thus one would expect NOAELs for multiple endpoints to show concordance (Thomas, 2015). There are a minority of chemicals that interact with specific targets at doses significantly lower than those at which they interact with many targets. These are the chemicals that an additional UF is intended to address. Janer et al. (2007) examined the relationship between subchronic repeat dose NOAELs and reproductive NOAELs in the context of the value of the EU requirement for a two generation

reproductive toxicity test. This evaluation compared 90-day NOAELs to NOAELs from two generation reproductive toxicity tests in rats for 45 reproductive and 75 non-reproductive toxicants. These authors concluded that there was less than a twofold difference for most of the NOAEL comparisons between the rat twogeneration studies and the rat subchronic studies. Larger differences (up to 10) were found for some chemicals, but the authors note that differences of this magnitude also occur between NOAELs of subchronic studies for the same chemical. A review by the International Life Sciences Institute (ILSI) Europe, in the context of the Threshold of Toxicological Concern dataset (Kroes et al., 2004) showed that, for the subset of chemicals that they reviewed, the population of NOAELs for subchronic target organ toxicity showed a similar range as the NOAELs for developmental and reproductive toxicity, and the analyses of van Ravenzwaay et al. (2011), Bernauer et al. (2008) reached similar conclusions. In conclusion, there appears to be consensus that repeat dose and DART (both reproductive and developmental) NOAELs are generally correlated, but there is the potential for a DART endpoint to be more sensitive and hence there is a need to address this in some manner in a risk assessment that is based on an incomplete dataset. The goal of the present work was to evaluate the hypothesis that the results of the DART decision tree (Wu et al., 2013) can be useful in informing the appropriate magnitude of a database uncertainty factor to account for a missing reproductive and/or developmental toxicity study when repeat dose data are available. We anticipated that similar to previous evaluations, there would be concordance between repeat dose NOAELs and DART NOAELs for most chemicals (both those determined to have a relationship to structures with DART toxicity and those that did not have a relationship to structures with DART toxicity), but that the results of the DART tree could be used to identify structures that had the potential to be outliers, i.e. to have much lower DART NOAELs than repeat dose NOAELs. In addition, in contrast to previous evaluations, we wanted to evaluate the utility of this approach in the context of the data most likely to be available for chemicals with a sparse dataset. In our experience (and in part due to the absence of regulatory requirements for DART studies except at high tonnage triggers as previously stated), chemicals with sparse data sets are more likely to have a repeat dose study than a developmental or a reproductive toxicity study. In addition, these sparse datasets are also likely to have data from a single species and that species in the vast majority of cases is the rat. Net, the most common scenario that we encounter is a repeat dose study in the rat and when data are available for either DART endpoint those studies are most frequently in the rat. We also wanted to evaluate the results in terms of the practical implications for final risk assessment results following the application of a full set of relevant UFs (specifically the inclusion of UFs for study duration) given that, unlike pesticides, many chemicals lack chronic studies. While there has been broad use of database UFs and there is general agreement that for most chemicals there is a strong correlation between repeat dose NOAELs and DART NOAELs, there remains residual concern about the potential for outliers. The hypothesis being evaluated in this work is that the DART decision tree can be used to distinguish chemicals that have structural similarity to chemicals with DART precedent and this group of chemicals identified as being structurally related to chemicals with DART precedent would contain the exceptions to the general rule of concordance between repeat dose and DART NOAELs, i.e., could be used to identify the potential outliers to this relationship. We intended to use the resulting dataset as the basis to propose a practical framework for addressing DART data gaps using the results of our recently published DART decision tree (Wu et al., 2013) in combination with a database UF, if the dataset supported our


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hypothesis. We propose that using the DART decision tree to inform the magnitude of an appropriate UF will contribute to greater confidence in use of a database UF to account for a missing DART study. Particularly in the context of the EU ban on animal testing for cosmetics, exploring ways to maximize use of existing data becomes increasingly important.

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2. Methods

220

Three datasets resulting in a total of 181 chemicals were examined:

221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237

(1) Gadagbui (2005) for which we focused on the rat data and went back to the original sources to determine what effects (if any) were shown at the reported NOAEL levels (130 chemicals). (2) The intersection of Laufersweiler et al. (2012) and the COSMOS database (http://www.cosmostox.eu/what/databases/ online, 2015) using the rat NOAEL values for DART endpoints from Laufersweiler et al. (2012), and using the COSMOS database as a pointer to the existence of repeat dose data which were then reviewed in the context of the original literature reports or authoritative reviews (29 chemicals). (3) A list of challenge chemicals developed by our in house DART experts that they identified as having DART effects of concern and moderate to high potency for those effects (22 chemicals).

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The Gadagbui (2005) dataset is the largest published dataset developed specifically to address the question of an appropriate UF to apply to address a missing DART study. This dataset was drawn from IRIS and ATSDR (Agency for Toxic Substances and Disease Registry) assessments and as such focused on environmental contaminants. The dataset was heavily biased towards pesticides because pesticides had more complete DART data due to registration requirements. Given that our intent was to develop a system that we could apply to chemicals that could be candidates for consumer product/cosmetic applications we wanted to explicitly add relevant chemical structures. Although it may be anticipated that pesticides would be more toxic, our goal was not necessarily to expand the dataset to lower toxicity chemicals, but to make sure that we had included an appropriate chemical space. The Laufersweiler et al. (2012) dataset was the result of an intensive search for available DART data, irrespective of chemical class or chemical use. Therefore, we thought this would be the best starting point to locate cosmetic/consumer product relevant chemicals with DART data. We then needed to locate repeat dose data on these same chemicals for the comparisons. Much of the repeat dose data on these types of ingredients is difficult to find in the primary literature so we used the COSMOS database as a means to determine which of the chemicals in Laufersweiler et al. (2012) had repeat dose data. Since the COSMOS dataset was explicitly constructed to include chemicals associated with cosmetics (ingredients or contaminants) we considered this a good way to expand the chemical domain beyond environmental chemicals. The third dataset was developed based on the expert opinions of our internal DART endpoint experts who have spent many years reviewing DART toxicity. Our challenge to them was to create a list of chemicals that they felt represented known ‘‘worst case’’ DART toxicants without consideration of the chemical structure of the toxicant. For this dataset we assessed the repeat dose NOAELs blinded from the DART NOAELs so that one numerical finding would not influence the interpretation of the others.

3

The resulting composite list of 181 chemicals was assessed using an automated version of the DART decision tree (in house automation) based on Wu et al. (2013). For the organic chemical space (excluding the organophosphates which were not evaluated in the construction of the tree due to time constraints as well as because this data rich class should be readily addressed using SAR), chemicals for which a specific structure can be drawn may be determined by the tree to be within the chemical domain of the tree or outside the chemical domain of the tree (i.e., if the chemical scaffold structure does not overlap with any of the structures considered in the development of the tree). This ability to broadly evaluate chemical scaffolds is one of a number of advantages to applying the automated version of the tree. Our automation program uses Pipeline Pilot (AccelrysÒ) and enumerates all possible structural variants defined by each tree rule which in turn facilitates determining if a chemical falls outside of the domain of structures used to develop the tree. A publically available version of the automated DART tree was released in October of 2014 as a component of the OECD QSAR Toolbox (http://www.qsartoolbox. org/). This tool is designed to identify the same structural precedents as our in house version. One limitation of the QSAR Toolbox version is that it does not assess the match of the underlying chemical scaffold of the compound of interest compared to structures addressed by the DART decision tree. As a result, determination of whether or not a chemical is in or outside of the chemical domain of the tree needs to be done manually by inspection of the chemical space of the tree based on the identified rules compared to the structure of interest. Metals were also not included in the design of the tree so would always be considered to be out of the domain of the tree. Chemicals in the three datasets which lacked at least one paired value of a repeat dose study and a developmental or reproductive study conducted in rats were not included. This resulted in 181 chemicals with at least one ratio (rat repeat dose NOAEL/rat reproductive or rat developmental NOAEL). When chronic rat studies could not be located, subchronic or subacute studies were included after application of a duration extrapolation factor (noted in the table footnotes). In addition, when NOAEL values could not be located, LOAEL values were included after adjustment using an additional uncertainty factor for LOAEL-to-NOAEL extrapolation (noted in the table footnotes). Default UFs were applied for the purposes of this exercise (IPCS, 1999; US EPA, 1993). Different UFs may be considered appropriate in the context of a complete weight of the evidence assessment for a quantitative risk assessment for any given chemical. We have operationally included multi-generation studies under the reproductive toxicity heading without regard to whether effects were on reproductive function of parental animals or effects were observed in offspring. Studies under the developmental toxicity heading are primarily those that focused effects on the developing conceptus after dosing of the dam. We collectively refer to DART effects in this document and the DART decision tree does not distinguish between developmental and reproductive effects. However, a complete dataset does need to include an assessment of both types of endpoints and we have assessed the ratios to repeat dose NOAELs separately for the two types of studies. We have limited our analysis to rat data given that rat repeat dose data are what are most commonly available in sparse datasets and they represent the bulk of the available data for repeat dose and reproductive toxicology studies of non-drug chemicals. We realize that the rabbit has historically been considered more sensitive than the rat and preferred as a second species for developmental toxicity studies required for drug safety investigations and at high tonnage triggers under REACH (European Chemicals Agency, 2014). The requirement for testing developmental toxicity in two species is linked to the thalidomide tragedy. The limb defects that


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were observed in infants after thalidomide use in pregnancy could be reproduced to some extent in rabbits but not in rats and therefore it was concluded that the rabbit might be a better predictor of human developmental toxicity than the rat. Thalidomide caused fetal death in the rat at doses similar to those causing limb malformations in the rabbit and hence if developmental toxicity based on all endpoints had been evaluated a similar potency for rats and rabbits would have been concluded (Theunissen et al., 2014). These authors further conclude that the general picture emerging from the many developmental toxicity studies is that in most cases a second species does not have a significant impact on the conclusions related to the developmental hazard. The lowest observed adverse effect level (LOAEL) for developmental toxicity between species usually differs less than a factor of 10 between which the authors note can be assumed to represent general biological variation. Of note, the intent of Theunissen et al. 2014 was to evaluate potential changes in the requirements for rabbit data for pharmaceuticals. Significant additional work is planned for that effort given that for pharmaceuticals exposure in a pharmacological active range is required, as opposed to the paradigm for non-pharmaceutical chemicals where intra-species differences can be addressed through the use of UFs. While drugs and other highly regulated chemicals have required toxicological evaluations in a rodent and a non-rodent species, this standard has not been generally applied to risk assessments on most types of chemicals. The US EPA (2002a) describes the minimum dataset required for development of a RfD to be a single subchronic study (which is separate from statutory requirements, e.g. for pesticides). From a review of RfD values on IRIS there does not appear to be a requirement for a non-rodent DART study to draw conclusions about DART toxicity, nor does there appear to be an explicit requirement for DART testing in multiple species by IPCS (1999). In addition, review of publically available risk assessments, such as High Production Volume Chemical assessments (http://iaspub.epa.gov/oppthpv/public_search. html_page), JECFA (Joint Expert Committee on Food Additives) reviews (http://www.inchem.org/), do not show the expectation of non-rodent data for DART endpoints. Rabbit data have not been required for cosmetic ingredient safety assessment, and according to Adler et al., 2011 ‘‘it can be concluded that in most cases an in vivo developmental toxicity study in the rat . . . submitted by the manufacturer as the only study on reproductive toxicity was considered sufficient by the SCCS as the minimum requirement’’. Therefore our analysis focused on repeat dose and DART ratios in the rat as the predominant available actionable data for risk assessment and to allow for direct comparisons of DART and repeat dose sensitivity within a single species. In the discussion section of this paper, we will address the implications of not including available rabbit data in the overall analysis, and in the results section we will provide specific examples of outcomes where rabbit data are explicitly considered.

392

3. Results

393

Using the criteria described in the methods, comparative data for the lowest rat repeat dose chronic NOAELs (or extrapolated surrogates) and rat DART NOAELs were located for 181 chemicals. These NOAELs, along with the DART tree conclusions (i.e., ‘match’ or ‘no match’ for chemicals that fall within the chemical domain of the tree, or ‘out of domain’), are shown in Table 1. The range of the ratios for chronic rat NOAELs (whether directly from chronic studies or derived from subacute/subchronic studies with application of duration adjustment uncertainty factors) divided by either rat reproductive toxicity NOAELs or rat developmental toxicity NOAELs show higher ratios for chemicals whose structures are

394 395 396 397 398 399 400 401 402 403

consistent with DART precedent than those that lack DART precedent according to the DART decision tree. Both groups illustrate that for the majority of the chemicals using the repeat dose NOAEL (chronic or extrapolated to chronic) as the point of departure for a risk assessment would be protective for DART endpoints. As expected, the chemicals identified as structurally related to chemicals with DART precedent had the highest ratios of chronic NOAEL to DART NOAEL. The chemicals identified as structures related to chemicals with DART precedents included all of the chemicals with divergent ratios (i.e., ratios >3) (Fig. 1). This suggests that the results of the DART tree can be helpful in assessing whether a chemical that has repeat dose data, but lacks DART data, is potentially an outlier to the predominant concordant relationship between repeat dose and DART NOAELs and that this information can be used to determine an appropriate database UF. In the process of reviewing the dataset, the values from Gadagbui (2005) were updated if more recent information was located. These changes are noted by adding a reference in the data tables. The majority of these changes were based on recent authoritative reviews. Since Gadagbui (2005) cited most of their values from IRIS and the preponderance of these DART data are from unpublished studies on pesticides summarized with only a single line of text we felt it was appropriate to update these if authoritative reviews were available that critically reviewed the studies and provided an in depth summary. In limited cases more recent studies from the peer reviewed literature were located that provided more appropriate information (e.g., studies that defined both an NOAEL and LOAEL to replace free standing NOAEL values) and in some instances values were added that were missing from the Gadagbui (2005) work based on a broader literature review. While primary toxicological databases were searched to identify any newer data, exhaustive literature searches were not conducted for all chemicals. An emphasis was placed on evaluating newer data for chemicals with the largest chronic NOAEL/DART NOAEL ratios given that these would be the values that would ultimately drive the database UF recommendation. Literature searches used SciFinder, Toxnet and Scopus as well as Google (particularly to identify authoritative reviews from regulatory bodies). While all of the changes to the NOAEL values from Gadagbui (2005) are documented in Table 1, a few of the changes were less straight-forward and therefore required additional clarification.

404

3.1. Dibutyl phthalate

445

For dibutyl phthalate (DBP) we calculated revised ratios of 3.4 for both reproductive and developmental effects. The selection of a reproductive/developmental NOAEL for DBP is controversial. We have chosen to use the lowest reported LOAEL (52 mg/kg/day) from a multi-generation study (NTP, 2002), considering both the expert panel review (Kavlock et al., 2002) and an in depth review of the literature by our internal DART experts. In this study fewer live pups per litter were reported in the F1 generation with lower pup body weights in the F2 generation. We believe that treating this LOAEL of 52 mg/kg/day as the critical point of departure for the risk assessment and applying a UF of 10 to extrapolate from an LOAEL to an NOAEL is conservative, given that the bulk of the data support NOAELs higher than this LOAEL. We chose not to use the controversial LOAEL from Lee et al. (2004) of 2 mg/kg/day given that it is inconsistent with the rest of the dataset on DBP and because of a number of issues with study design and analysis. In the Lee study, there were not clear dose response relationships for the critical effects, the histopathological evaluations were not done blindly and were subjective, the statistical analysis did not appear to account for severity, and there were not functional correlates that would have been expected from the findings (e.g., delay in puberty). Consistent with our internal review, the U.S.

446


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447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467

Rat chronic NOAEL

Part A: Chemicals with DART values from Gadagbui (2005)1 Acifluorfen, sodium 62476-59-9 1.302E+00 Acrolein 107-02-8 5.00E02 Acrylic acid 79-10-7 3.31E+02 Acrylonitrile 107-13-1 4.20E+00 Aldicarb 116-06-3 3.00E01 Aldicarb sulfone 1646-88-4 – Assure 76578-14-8 9.00E01 Asulam 3337-71-1 3.60E+01 3

Rat repro NOAEL

Rat develop NOAEL

Chronic/ repro

Chronic/ develop

DART tree result

References for chronic NOAEL and DART (if not from Gadagbui et al.)

1.30E+00 2.50E+00 5.30E+01 1.10E+01 3.00E01 2.40E+00 1.30E+00 5.00E+01

2.00E+01 6.00E+00 2.50E+02 1.00E+01 1.30E01 9.60E+00 3.00E+02 1.50E+03*

1.00E+00 2.00E02 1.6E01 3.8E001 1.00E+00 – 6.92E01 7.20E+00– 01

3.00E01 8.33E03 7.5E01 4.20E01 2.31E+00 – 3.00E03 2.40E02

Match Match Match Match Match Match Match Match

US EPA (1989)

Match

European Agency for the Evaluation of Medicinal Products (2002)

Avermectin B1

65195-55-3

–

–

Baygon Bayleton Baythroid Benomyl

114-26-1 43121-43-3 68359-37-5 17804-35-2

1.00E+01 2.50E+00 2.50E+00 1.50E+01

– 2.50E+00 2.50E+00 2.80E+01

Bromoxynil Carbofuran Carbosulfan Chlorobenzene Cyhalothrin/Karate Cypermethrin4 Di(2-ethylhexyl)adipate Dicamba 1,2-Dichloroethane 1,1-Dichloroethylene 1,2-Dichloropropane 1,4-Dichlorobenzene 2,4-Dinitrotoluene Di-2-ethylhexylphthalate Endosulfan Endrin Formaldehyde* Haloxyfop-methyl Iprodione Methomyl Methoxychlor Mirex

Thiram Trifluralin 1,3,5-Trinitrobenzene Amdro Ally

19044-88-3 87-86-5 67747-09-5 60207-90-1 88671-89-0 23564058 137-26-8 1582-09-8 99-35-4 67485-29-4 74223-64-6

5.00E+00 1.00E+00 1.00E+00 6.00E+01 2.50E+00

1.50E+01 1.00E+00 1.00E+00 1.70E+02 1.50E+00

7.00E+02 1.70E+02 1.20E+02* 3.50E+01 4.30E+01 4.30E+01 9.00E+00 3.00E+01* 6.00E+01 1.00E+02 1.50E+02 1.00E+03 3.90E+00 5.00E+00 29.0E+01 4.80E+00 7.00E01 1.10E+00 5.00E02 3.00E01 2.00E+00 4.00E+01 1.00E01 6.5E02 5.00E+01 2.50E+01 5.00E+00 5.00E+00* See Table 1 Part C below for updated 7.50E02 5.0E025

– 1.00E+00 1.00E+00 6.00E01

2.00E01 5.00E02 8.33E02 5.00E01

Match Match Match Match

1.50E+01 1.00E+00 2.00E+00 2.20E+02 1.50E+01*

3.33E01 1.00E+00 1.00E+00 3.53E01 1.67E+00

3.33E01 1.00E+00 5.00E01 2.73E01 1.67E01

1.70E+02 4.00E+02 1.60E+02 4.00E+01 3.00E+01 2.50E+02 – 4.80E+00 – 5.00E01 1.00E+01 1.00E+00 – – assessment 3.10E026

4.12E+00 3.4E+00 1.00E+00 3.00E01 6.00E01 1.50E01 7.80E01 6.00E+00 6.36E01 1.67E01 5.00E02 1.54E+00 2.00E+00 1.00E+00

4.12E+00 3.00E01 2.69E01 2.25E01 2.00E+00 6.00E01 – 6.00E+00 – 1.00E01 2.00E01 1.00E01 – –

1.50E+00

2.42E00

Match Match Match Match Match Match Match Match Match Match Match Match Match Match Match Match Match Match Match Match Match Match

1.15E+00 3.00E01 2.53E01 2.00E01 1.09E+00 1.00E+00

6.52E02 7.50E01 3.65E01 1.67E01 8.62E02 6.15E02

Match Match Match Match Match Match

1.67E01 1.00E01 9.00E01 1.00E+00 1.00E01

– 2.08E02 6.00E02 2.50E01 2.50E02

Match Match Match No match No match

1.50E+01 3.00E+00 1.90E+00 5.00E+00 2.50E+00 8.00E+00

1.30E+01 1.00E+007 7.50E+00 2.50E+01 2.30E+00 8.00E+00

2.30E+02 4.00E+00 5.20E+00 3.00E+01 2.90E+01 1.30E+02

5.00E+00 1.00E+01 2.70E+00 2.50E+00 2.50E+01

3.00E+01 1.00E+02 14.00E+008 2.50E+00 2.50E+02*

4.00E+01 4.80E+02 4.50E+01 1.00E+01 1.00E+03

*

US EPA IRIS Friedman and Beliles (2002)

US EPA (2002b)

California Environmental Protection Agency (1999)

US EPA (2007)

EFSA (2011a)

European Chemicals Bureau (2008b)

WHO (2006)

US EPA IRIS Yarbrough et al. (1981), Chu et al. (1981)


Oryzalin Pentachlorophenol Prochloraz Propiconazole Systhane Thiophanate-methyl

1689-84-5 1563-66-2 55285-14-8 108-90-7 68085-85-8 52315-07-8 103-23-1 1918-00-9 75-34-3 75-35-4 78-87-5 106-46-7 121-14-2 117-81-7 115-29-7 72-20-8 50-00-0 69806-40-2 36734-19-7 16752-77-5 72-43-5 2385-85-5

*

5.00E+01 5.00E+01 3.00E+01* 3.00E+01

YRTPH 3269

CAS

21 April 2015

Chemical name


(continued on next page) 5


Table 1 Comparison of rat chronic repeat dose NOAELs to rat reproductive and developmental NOAELs.

6

Rat repro NOAEL

Rat develop NOAEL

Chronic/ repro

Chronic/ develop

DART tree result

Amitraz Apollo Atrazine Bentazon Biphenthrin Butylate Captafol Captan Carboxin Chlorimuron-ethyl Chloral hydrate Chloromethane Chlorsulfuron Cyromazine Dacthal Danitol 1,3-Dichloropropene Dimethipin Diquat Express

33089-61-1 74115-24-5 1912-24-9 25057-89-0 82657-04-3 2008-41-5 2425-06-1 133-06-2 5234-68-4 90982-32-4 302-17-0 74-87-3 64902-72-3 66215-27-8 1861-32-1 39515-41-8 542-75-6 55290-64-7 85-00-7 101200-480 100-41-4 759-94-4 59756-60-4 56425-91-3 69409-94-5 79277-27-3 70-30-4 121-82-4

2.50E+00 2.00E+00 3.50E+00 9.00E+00 2.50E+00 5.00E+01 2.80E+00 2.5E+01 1.00E+01 1.30E+01 1.60E+02 2.20E+02 5.00E+00 1.50E+00 1.00E+00 7.20E+00 2.00E+01 2.00E+00 1.90E01 1.30E+00

1.60E+00 2.00E+01 3.50E+00 1.50E+01 1.50E+00* 5.00E+0110 6.00E+01* 1.30E+01 1.00E+01 1.7E+01 1.60E+0211 2.20E+02 2.50E+01* 5.00E+01 1.80E+01 3.00E+00 9.00E+01* 1.00E+01 2.50E+01 1.30E+00

– 3.20E+03 1.00E+01 1.00E+02 1.00E+009 5.00E+01 3.00E+01 – 4.00E+01* 3.00E+01 1.50E+02 4.80E+02 1.30E+02 – 2.50E+03* 1.00E+01* 1.50E+02* 1.60E+02 2.50E+01 2.00E+01

1.56E+00 1.00E01 1.00E+00 6.00E01 1.67E+00 1.00E+00 4.67E02 1.92E+00 1.00E+00 7.67E-01 1.00E+00 1.00E+00 2.00E01 3.00E02 5.56E02 2.40E+00 2.22E01 2.00E01 7.60E03 1.00E+00

– 6.25E04 3.50E01 9.00E02 2.50E+00 1.00E+00 9.33E02 – 2.50E01 4.33E-01 1.07E+00 4.58E01 3.85E02 – 4.00E04 7.20E01 1.33E01 1.25E02 7.60E03 6.50E02

No No No No No No No No No No No No No No No No No No No No

match match match match match match match match match match match match match match match match match match match match

2.50E+02 5.00E+00 8.00E+00 3.60E+00 1.00E+00 1.30E+00 1.00E+00 3.00E01

2.50E+02 2.50E+00 3.30E+01 1.80E+00 1.00E+00 1.30E+02* 1.00E+00 5.00E+00

9.70E+01 1.00E+02 3.00E+02 1.00E+01 1.00E+01 1.60E+02 – 2.00E+00

1.00E+00 2.00E+00 2.42E01 2.00E+00 1.00E+00 1.00E02 1.00E+00 6.00E02

2.58E+00 5.00E02 2.67E02 3.60E01 1.00E01 8.13E03 – 1.50E01

No No No No No No No No

match match match match match match match match

51235-04-2 81335-37-7 82558-50-7 77501-63-4

1.00E+01 5.00E+02 5.00E+00 2.00E+00

1.30E+02* 1.00E+03* 1.30E+02 2.60E+00

– 5.00E+02 3.20E+02 5.00E+01

7.69E02 5.00E01 3.85E02 7.69E01

– 1.00E+00 1.56E02 4.00E02

83055-99-6 24307-26-4 57837-19-1 1634-04-4 21087-64-9 51218-45-2 15299-99-7 27314-13-2 42874-03-3 1910-42-5 52645-53-1 13684-63-4 108-95-2 1918-02-1 139-40-2 81335-77-5 78587-05-0

3.00E+01 5.00E+00 1.30E+01 4.00E+02 5.00E+00 1.50E+01 3.00E+01 1.90E+01 1.8E+01 1.30E+00 5.00E+00 2.50E+01 3.2E+0114 2.00E+01 5.00E+00 5.00E+02 2.30E+01

3.10E+02* 3.40E+02* 6.30E+01* 2.50E+03 1.50E+01* 1.50E+01 3.00E+01 1.90E+01 3.3E+01 7.50E+00 2.50E+0112 2.50E+01 7.10E+0115 – 5.00E+00 – 3.50E+01

1.30E+03* 3.40E+02* 5.00E+01 4.00E+02* 1.00E+02* 3.60E+02* 4.00E+02 4.00E+02* 1.80E+01 1.00E+00* 2.00E+02*13 – 1.20E+02 1.00E+03* – 1.10E+03* 2.40E+02

9.68E02 1.47E02 2.06E01 1.60E01 3.33E02 1.00E+00 1.00E+00 1.00E+00 5.45E01 1.73E01 – 1.00E+00 4.57E01 – 1.00E+00 – 6.57E01

2.31E02 1.47E02 2.60E01 1.00E+00 5.00E02 4.17E02 7.50E02 4.75E02 1.00E+00 1.30E+00 2.50E02 – 2.67E01 2.00E02 – 4.50E01 9.58E02

No match No match No match No match Metabolite is a match No match No match No match No match No match No match No match No match No match No match No match No match No match No match No match No match No match

Ethylbenzene* S-ethyl dipropylthiocarbamate Fluridone Flurprimidol Fluvalinate Harmony Hexachlorophene Hexahydro-1,3,5-trinitro-1,3,5triazine Hexazinone Imazaquin Isoxaben Lactofen

Londax Mepiquat chloride Metalaxyl Methyl tert-butyl ether Metribuzin Metolachlor Napropamide Norflurazon Oxyfluorfen Paraquat Permethrin Phenmedipham Phenol Picloram Propazine Pursuit Savey


EFSA (2009c) US EPA (2009) US EPA (2000)

US EPA (2003)

US EPA (2001) US EPA IRIS US EPA (2002c)


Rat chronic NOAEL

YRTPH 3269

CAS

21 April 2015

Chemical name



Table 1 (continued)

CAS

Rat chronic NOAEL

Rat repro NOAEL

Rat develop NOAEL

Chronic/ repro

Chronic/ develop

DART tree result

Sethoxydim Simazine Styrene Terbutryn Thiobencarb Tralomethrin Tridiphane Vinyl acetate Acephate Aluminum Boric acid (as boron) Bromate Chlorine Chlorine dioxide Chlorpyrifos Chromium (VI) Diazinon Dichlorvos Dimethoate Disulfoton Ethion Fenamiphos Fosetyl-Al Glyphosate Malathion Methidation Monochloramine Nickel Nitrate Nustar Phosmet Pirimiphos-methyl Quinalphos Tetrachlorovinphos Tributyltin oxide

74051-80-2 122-34-9 100-42-5 886-50-0 28249-77-6 66841-25-6 58138-08-2 108-05-4 30560-19-1 7429-90-5 11113-50-1 15541-45-4 7782-50-5 10049-04-4 2921-88-2 18540-29-9 333-41-5 62-73-7 60-51-5 298-04-4 563-12-2 22224-92-6 39148-24-8 1071-83-6 121-75-5 950-37-8 10599-90-3 7440-02-0 14797-55-8 85509-19-9 732-11-6 29232-93-7 13593-03-8 961-11-5 56-35-9

1.80E+01 5.20E01 2.10E+01 1.00E01 1.00E+00 7.50E01 3.00E+00 2.40E+02 2.50E+00 6.00E01 1.75E+01 1.10E+00 1.40E+01 1.3E+0017 1.00E0118 2.50E+00 7.00E0216 2.30E01 1.30E+00 4.00E0220 2.00E01 5.00E01 1.00E+02 1.40E+00 3.50E+01 2.00E01 9.50E+00 1.00E01 3.7E+0222 4.60E-01 2.00E+00 1.50E+01 1.00E+00 6.30E+00 1.90E01

5.40E+01* 2.90E+01 1.35E+02 1.50E+01 – 7.50E01 1.00E+00 1.00E+02*,16 2.50E+00 5.20E+01 1.75E+01 7.70E+00 5.00E+00* 3.00E+00 1.00E+00 3.70E+01 5.00E01 2.50E+01* 7.50E+00* 3.00E0221 1.30E+00* 5.00E01* 3.00E+02 1.00E+01 8.00E+02 2.50E01 1.00E+01* 3.90E+00 4.10E+01* – 4.00E+00* 5.00E+00* 5.00E01* 1.70E+01 4.40E+00

2.50E+02* – 3.00E+02* 5.00E+01 2.50E+01 1.80E+01* 3.00E+01 2.05E+0213 2.00E+02 1.10E+02 1.03E+1 2.20E+01 1.50E+01* 3.00E+00 3.00E0219 3.70E+01 2.00E+01 2.10E+01* 1.80E+01* 9.00E03 6.00E01 – 1.00E+03 1.00E+03 1.50E+02 2.30E+00* 1.50E+01* 8.00E01 4.10E+01* 2.00E+00 – 1.50E+02* – – 3.40E01

3.33E01 1.79E02 1.05E01 6.67E03 – 1.00E+00 3.00E+00 2.40E+00 1.00E+00 1.15E02 1.00E+00 1.43E01 2.80E+00 4.30E01 1.00E01 6.76E02 1.40E01 9.20E03 1.73E01 1.33E+00 1.54E01 1.00E+00 3.33E01 1.40E01 4.38E02 8.00E01 9.50E01 2.56E02 4.88E02 – 5.00E01 3.00E+00 2.00E+00 3.71E01 4.32E02

7.20E02 – 7.00E02 2.00E03 4.00E02 4.17E02 1.00E01 1.17E+00 1.25E02 5.45E03 1.70E+00 5.00E02 9.33E01 4.30E01 3.33E+00 6.76E02 3.50E02 1.10E02 7.22E02 4.00E+00 3.33E01 – 1.00E01 1.40E03 2.33E01 8.70E02 6.33E01 1.25E01 4.88E02 2.30E01 – 1.00E01 – – 5.59E01

No match No match No match No match No match No match No match No Match Out of domain Out of domain Out of domain Out of domain Out of domain Out of domain Out of domain Out of domain Out of domain Out of domain Out of domain Out of domain Out of domain Out of domain Out of domain Out of domain Out of domain Out of domain Out of domain Out of domain Out of domain Out of domain Out of domain Out of domain Out of domain Out of domain Out of domain

Chemical name

CAS

Rat chronic NOAEL

Rat repro NOAEL

Rat develop NOAEL

Chronic/ repro

Chronic/ develop

DART tree result

Reference for rat chronic NOAEL and additional DART endpoints not cited in Laufersweiler et al. (2012)

5.00 E+01 4.00E+03

– 2.00E+03

1.30E+02 4.00E+03

2.00E+00

3.80E01 1.00E+00

Match Match

US EPA (2006) EFSA (2013)

2.00E01 6.23E+00 1.00E01

8.60E03 2.00E02 2.57E+00 –

US EPA IRIS Daston (2004), NTP (2005) OECD (2002a) US EPA, IRIS

1.00E+00

4.50E03 1.50E01

Match Match Match Match Match Match Match

1.58E01 7.01E02

9.40E01 1.42E01

Match Match

OECD (2002b) NTP (2004)

1.25E+0124 1.45E+03 2.00E+0224 1.00E+01 1.00E+02 2.6E+01 4.17E+0025 1.01E+01 1.80E+01 1.80E+01 – See Table 1 Part C below for updated assessment 5.00E+0024 – 1.12E+03* 3.00+0127 2.00E+02 3.00E+0126 2.5E+01* 7.10E+0128

5.0E+1* 1.00E+03

1.58E+02 5.00E+02

European Commission (2011), US EPA (1994)

John-Greene et al. (1987) ECB (2008b)

US EPA, IRIS (updated)

EFSA (2014), US EPA (2011a) US EPA (2004), WHO, Undated a

US EPA IRIS; ATSDR (1995)

WHO, Undated b


Part B: Chemicals from Laufersweiler et al. (2012)23 2-Ethyl-1-hexanol 104-76-7 Aspartame 22839-470 Butyl alcohol 71-36-3 butyl paraben 94-26-8 Caffeine 58-08-2 Cyclohexylamine 108-91-8 Dibutyl phthalate 84-74-2 Diethylene glycol 111-46-6 Diethylene glycol monomethyl 111-77-3 ether Ethylene dicholoride 107-06-2 Ethylene glycol 107-21-1


YRTPH 3269

21 April 2015

Chemical name


SCCP (2008) European Chemicals Bureau (2000)

(continued on next page) 7


Table 1 (continued)

8

Rat chronic NOAEL

Rat repro NOAEL

Rat develop NOAEL

Chronic/ repro

Chronic/ develop

DART tree result

Reference for rat chronic NOAEL and additional DART endpoints not cited in Laufersweiler et al. (2012)

Ethylene glycol monoethyl ether Ethylenediamine Eugenyl methyl ester Isoeugenol Musk ketone Benzenethiol

110-80-5 107-15-3 93-15-2 97-54-1 81-14-1 108-98-5

1.09E+0129 2.00E+01 1.00E+0030 1.50E+02 2.40E+0024 4.00E01

9.3E+01 5.00E+02* 3.00E+0131 5.00E+02 2.50E+00 1.00E+01

2.30E+01 2.50E+02 2.00E+02 2.30E+02 4.5E+01 2.00E+01

1.17E01 4.00E02 3.00E02 3.00E01 1.00E+00 4.00E02

4.74E01 8.00E02 5.00E02 6.50E01 5.60E02 2.00E02

Match Match Match Match Match No match

7.50E+0224 1.00E+0133 1.00E+0234 1.00E+02

5.00E+0232 2.90E+01 2.50E+02 1.00E+02

1.00E+00 3.10E01 1.39E01 1.00E+00

1.60E+00 1.07E01 5.56E02 1.00E+00

No No No No

match match match match

European Chemicals Bureau (2008c) OECD (2001a) NTP (2000) NTP (2010) ECB (2005) Japan Existing Chemicals Database, online; SCF (2002) OECD (2001b) EFSA (2009a) US EPA IRIS EFSA (2011b)

1.00E+02 1.00E+03 2.00E+02 6.95E+02

4.00E+02

6.30E02

5.46E+02

2.50E01 3.33E01 1.00E+00 1.00E+00

1.30E+00

No No No No

match match match match

OECD (2002c) ECB (2002) US EPA (2005) EFSA (2009b)

– 5.00E+03* 1.50E+03

1.00E+02 5.00E+03* 2.00E+03

– 5.00E01 1.00E+00

5.30E02 5.00E01 7.50E01

No match No match No match

SCCS (2012) Japanese Food Safety Commission (2007) SCF (2000)

2.96E+03* 8.85E+02

– 1.00E+02

1.11E+00 7.80E04

– 6.90E03

Out of domain No match

Kojima (1974) US EPA IRIS

Benzoic acid Benzophenone Biphenyl Butylated hydroxyanisole

65-85-0 8.00E+02 119-61-9 3.10E+00 92-52-4 1.39E+01 25013-161.00E+02 5 Butylated hydroxytoluene 128-37-0 2.50E+01 Ethyl acetoacetate 141-97-9 3.33E+026 Ethyl maltol 4940-11-8 2.00E+02* FDC red 40 25956-176.95E+02 6 Furfuraldhyde 98-01-1 5.30E+0024 Polysorbate 80 (Tween) 9005-65-6 2.5E+03 Sucralose 56038-131.50E+03 2 Disodium inosinate 4691-65-0 3.25E+03 Ethylene glycol monobutyl ether 111-76-2 6.90E+0-135 Part C: Chemicals selected by internal experts 2,3,7,8-Tetrachlorodibenzo1746-01- 7.00E0633 1.30E05 p-dioxin 6 Aminopterin 54-62-6 4.20E0536 Busulfan Carbamazepine Cyclophosphamide Dibutyl phthalate Diethylstilbestrol Dipenylhydantoin Ethylene glycol monomethyl ether Isotretinoin

Propylthiouracil Tamoxifen Thalidomide Trenbolone Valproic acid Vinclozolin Lithium carbonate

5.38E01

Match

NTP (2006), US EPA (2011), Greene et al. (2003)

3.36E02

Match

55-98-1 298-46-4 6055-192 84-74-2 56-53-1 57-41-0 109-86-4

1.70E02 2.5E+0033 6.70E0326

4.80E+01 2.00E01

1.50E+00 4.80E+01 2.00E01

5.2E02 3.35E02

1.13E02 5.2E02 3.35E02

Match Match Match

Oleson et al. (1948), Committee on Toxicity of Chemicals in Food, Consumer Products and the Environment (2014) Sakurada (2009) FDA (1973) Tanaka et al. (1992)

1.77E+0133 2.00E0333 2.50E+0038 7.00E0135

5.2E+0037 6.5E0433 4.00E+0039 9.00E01

5.2E+00 4.50E03 5.00E+01 1.6E+00

3.40E+00 3.07E+00 6.25E01 7.89E01

3.4E+00 4.44E01 5.00E02 4.38E01

Match Match Match Match

ECB (2004), Kavlock et al. (2002) Gibson et al. (1967), Wardell et al. (1982), Odum et al. (2002) Jang et al. (1987), Kim et al. (2012), NTP (1993) WHO (2009), Gulati et al. (1990), Nelson et al. (1989)

4759-482 330-55-2 60-56-0 59-05-2 72-43-5 5912246-2 51-52-5 1054029-1 50-35-1 1016133-8 99-66-1 5047144-8 554-13-2

2.00E0133

3.20E+01

5.00E+01

6.25E02

4.00E03

Match

Hoffmann-La Roche Limited (2014)

2.50E0133 1.00E0233 2.00E0326 2.00E+00 1.60E01

1.25E+00 1.00E0140 6.00E0241 6.00E01 4.00E01

3.12E+01* 1.00E01 5.00E0242 6.00E01 1.60E+00

2.00E01 1.00E01 5.00E02 3.33E+00 4.00E01

8.01E03 1.00E01 4.00E02 3.33E+00 1.00E01

Match Match Match Match Match

US EPA, IRIS Fegert et al. (2012) Murakami (1998), Tshibangu, et al. (1975), Patel et al. (2014) US EPA, IRIS; Aoyama et al. (2012) Kotsonis et al. (1985), Esaki et al. (1985)

3.3E0343 7.00E0444

1.00E02 1.00E03

1.00E02 1.00E03

3.33E01 7.00E01

3.33E01 7.00E01

Match Match

Mellert et al. (2003) Watanabe et al. (1980), NTP (1997)

3.00E+0124 4.00E0324

3.00E03

5.0E+0033 3.00E03

1.33E+00

6.00E+00 1.33E+00

Match Match

Teo et al. (1999), Newman et al. (1993) WHO (1990), Mantovani (1992)

1.57E+0124 2.5E0126

2.50E+02 6.4E+01

1.00E+0133 2.3E0123

6.28E01 3.90E03

1.57E+00 1.09E+00

Match Match

Abbott Laboratories (1981), Narotsky et al. (1994), Nishimura et al. (2000) Matsuura et al. (2005)

1.00E+0026

1.40E+01

9.40E+00

7.14E02

1.06E01

Out of domain

US EPA (2011), OEHHA (2003)

26

1.25E03

5.38E01 33


Linuron Methimazole Methotrexate Methoxychlor Misoprostol

1.30E05

YRTPH 3269

CAS

21 April 2015

Chemical name



Table 1 (continued)

YRTPH 3269

21 April 2015

Denotes free standing NOAEL (no effects noted at highest dose tested). Values that have been updated from those in Gadagbui (2005) are indicated by listing the references. US EPA replaced the rat chronic value with the NOAEL from a three generation study because the three generation study showed the same NOAEL for parental animals and offspring and because the NOAEL was lower than that from the previously used chronic study. 3 Newer data support that rodent reproductive and developmental toxicity studies are inappropriate for human risk assessment and that DART effects are not the critical effects for the risk assessment. 4 Newer data available, see entry in Table 1Part C. 5 Mirex is both a male and female reproductive toxicant, NOAELs are poorly defined, studies are old and data are fragmentary. The lowest LOAEL of 0.5 mg/kg/day is adjusted using a 10 UF. 6 The IRIS summary indicates that 0.3 mg/kg/day (cited as an NOAEL in Gadagbui (2005)) is a frank effect level (FEL) for cataract development in offspring, however, a variety of other studies show this effect only at higher levels, normally an FEL could not be adjusted to estimate an NOAEL, but given that the majority of the studies show this effect only at higher doses it is considered acceptable to apply an additional UF of 10. 7 Gadagbui (2005) cite 10 mg/kg, but this is an LOAEL, converted to NOAEL applying a 10 factor. 8 Gadagbui (2005) reported NOAEL for systemic tox (spleen) in F0 animals, changed to NOAEL for testicular effects. No effects on reproductive performance or offspring noted. 9 Equivocal effects at the highest does tested (2 mg/kg) according to US EPA IRIS. Original study not available for review. 10 Listed as 105 in Gadagbui (2005), but liver weights interpreted differently for chronic NOAEL vs reproductive NOAEL (non-adverse compared to adverse) so the interpretation between the two studies was harmonized. 11 Based on EPA’s review of the entire database and their conclusion about threshold level rather than a single study. 12 US EPA IRIS cites this as an LOAEL, however, offspring effects similar in type seen in parental animals so ratio not calculated. 13 No value listed in Gadagbui (2005). 14 US EPA applied a database UF of 3 and did not apply a duration correction. 15 US EPA notes that effects at LOAEL likely driven by decreased water consumption. 16 The source of the value cited in Gadagbui (2005) could not be determined. 17 Gadagbui (2005) incorrectly cite the dose from US EPA IRIS as 10 mg/kg/day correct value is 10 mg/l or 1.3 mg/kg/day. 18 Newer data provide lower value than Gadagbui (2005). 19 US EPA IRIS cites this as an LOAEL, however, offspring effects similar in type and severity in parental animals. 20 Value from Gadagbui (2005) does not match with IRIS citation, dose corrected based on IRIS. 21 Source of value from Gadagbui (2005) unclear, US EPA IRIS cited repro study inadequate (EPA assessment) cited from ATSDR. 22 Source of data cited by Gadagbui (2005) unclear, value not used. 23 DART NOAELs from Laufersweiler et al. (2012) unless otherwise noted. 24 Subchronic NOAEL adjusted using 10. 25 Minimal LOAEL adjusted using 3. 26 Subacute NOAEL adjusted using 30. 27 No repro study available, testicular effects appear to be critical effect from repeat dose studies. 28 Subchronic NOAEL not adjusted given chronic NOAEL of 200 mg/kg reasons for divergence not clear. 29 Subchronic LOAEL adjusted by 100. 30 Subchronic NOAEL adjusted using 10, this value was used instead of the chronic NOAEL since the bioassay was missing clinical chemistry, hematology etc. 31 Based on subchronic study that included sperm motility, estrous cycle and reproductive organ evaluations. 32 Laufersweiler et al. cite a third party review that refers to an abstract of a TSCA 8E report. In fact the TSCA 8E report is associated with a totally different chemical (US EPA, 2011b) although the text of the abstract incorrectly refers to benzoic acid, the CAS number clearly points to a different chemical, hence a value for benzoic acid was substituted. 33 LOAEL adjusted by 10. 34 EFSA (2011a,b) discounted the effects cited in Laufersweiler et al. (2012) and defaulted to a 10 higher NOAEL for all DART endpoints. 35 Subchronic LOAEL adjusted by 100. 36 Study inadequate for risk assessment, but clearly shows adverse effects. Subacute LOAEL adjusted by 3000. 37 One value chosen as reflective of both developmental and reproductive endpoints. LOAEL adjusted by 10. 38 Subchronic NOAEL adjusted by 10, chronic studies did not include clinical pathological endpoints. 39 Not a standard reproductive tox study design, females only dosed then F1 evaluated. 40 No DART effects, offspring thyroid effects similar to parental generation. 41 NOAEL for testicular effects, no reproductive study found. 42 Intraperitoneal injection (IP) LOAEL. An IP dose would not be considered appropriate for risk assessment, but in this situation it can be considered worst case and supports that fetal effects occur only at doses where parental toxicity occurs. 43 Subacute NOAEL adjusted by 30. Note that thyroid hormone effects were shown at this dose level, but since these measurements would not necessarily be included in a standard repeat dose study they were not included in the evaluation of the NOAEL. 44 Subchronic NOAEL adjusted by 10. Note that this is in Japanese and could not be critically reviewed. Use of newer subacute data would have resulted in lower estimated NOAELs. Retaining the higher NOAEL based on subchronic data is conservative in this analysis. 2



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Fig. 1. Rations of rat chronic NOAELs to rat developmental and reproductive NOAELS by DART tree result.

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Consumer Product Safety Commission (2014) noted that the number of animals per group in the Lee et al. (2004) study was inadequate to use this study to estimate a NOAEL and also commented on the inappropriateness of using the fetus rather than the litter as the unit for statistical analysis. The U.S. Consumer Product Safety Commission chose the rat NOAEL of 50 mg/kg/day as an appropriate point of departure for their risk assessment and extensive literature on DBP consistently identifies NOAELs/LOAELs in the range of 50 mg/kg, supporting that our use of the value of 52 mg/ kg/day as a LOAEL is conservative.

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The reproductive toxicity value for acrylonitrile was also revised and that revision involved some interpretation. Gadagbui (2005) cited a reproductive toxicity NOAEL of 0.14 mg/kg/day based on the Agency for Toxic Substances and Disease Registry (ATSDR) (1990). This unpublished study was not summarized in detail and the range of doses was not given, but ATSDR notes that there were reported increases in testes weight in rats exposed to 14 mg/kg/day acrylonitrile in a two year drinking water study and they list the NOAEL from this study as 0.14 mg/kg/day. ATSDR states that the effects observed at 14 mg/kg/day are of questionable significance in that they are not reported in other repeat dose exposure studies for rats. Subsequent to the study cited by ATSDR, a three generation reproductive study in rats has been reported that showed no impact on reproductive performance at the highest dose tested of 11 mg/kg/day (Friedman and Beliles, 2002) and a rat oral chronic study showed no effects on rat testes weight or histology at a dose of 10 mg/kg/day (Johannsen and Levinskas, 2002). Hence the low NOAEL from ATSDR (1990) cited by Gadagbui (2005) is not supported by more recent literature and therefore in this analysis a reproductive

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toxicity NOAEL of 11 mg/kg/day was used. It is also appropriate to use this NOAEL since it is below the reported LOAEL of 14 mg/ kg/day.

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The revision of the reproductive toxicity value for benomyl also required some interpretation. The NOAEL (5 mg/kg) from Gadagbui (2005) was based on an older (1987) US EPA IRIS assessment that cites an unpublished three generation study from 1968 that reported decreases in pup body weights at higher doses. No further details of the study are provided. The WHO (1995) cites a higher reproductive toxicity NOAEL (37 mg/kg/day) from a more recent unpublished study (1990) that is described in much greater detail, but without access to the original study reviewed by US EPA or more details about its conduct we did not feel that we could discount the NOAEL of 5 mg/kg selected by EPA. However, the California Environmental Protection Agency (CalEPA) (1999) reviewed all of the available benomyl data based on the full study reports in the context of the US EPA review. The CalEPA concluded that the study used by the US EPA for the point of departure for the risk assessment was not suitable for use in risk assessment: ‘‘The US EPA RfD of 0.05 mg/kg-day was based on a NOEL of 5 mg/kgday for decreased weanling weights from a three-generation rat reproduction study (Sherman, 1968). The study was not acceptable to California Department of Pesticide Regulation under FIFRA guidelines because of inadequate group size and lack of feed analysis despite demonstrable instability of the test article’’. Based on both the CalEPA review and the observation that the NOAEL selected by the US EPA is out of line with the rest of the toxicological database on benomyl, we used the NOAEL for reproductive toxicity of benomyl recommended by the CalEPA (1999) of 28 mg/ kg/day. In addition, this same agency recommends that the

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NOAEL for chronic toxicity of 15 mg/kg/day be used as the point of departure for the risk assessment. While technically this value is based on a dog study rather than determined in the rat, it is chosen in the context of the conclusion by the State of California. The State of California concluded that the toxicity of benomyl is similar for both the dog and the rat and across both subchronic to chronic exposure durations, and the 15 mg/kg/day dose best represents the point of departure for chronic repeat dose toxicity considering the totality of the dataset. Additional perspective on DART study results for chemicals not associated with structures known to have DART activity in the DART decision tree, but that had the highest ratios of chronic NOAEL/reproductive NOAEL in this non-DART precedent group, is elaborated in the following paragraphs. Tridiphane showed a high ratio for chronic NOAEL/reproductive NOAEL when the values cited in Gadagbui (2005) based on IRIS were used. The IRIS assessment for this chemical cites an unpublished Dow Chemical two generation study and concludes that the reproductive NOAEL is 1 mg/kg/day, based on decreases in maternal body weight and fertility index in the 5 and 30 mg/ kg/day dose groups. This NOAEL of 1 mg/kg/day is then adjusted downwards by the US EPA to 0.33 mg/kg/day based on a reduction in the dietary admixture concentration during gestation and lactation. However, the published version of this study (John-Greene et al., 1987) clearly indicates that the reduction in dietary admixture concentration was made to provide a constant dose per unit of body weight for pregnant and lactating dams and maturing pups. Net, the US EPA adjustment of the NOAEL appears to be inappropriate based on the published study. In addition, the published study contends that the observed effects on fertility index are not test article related but are well within the historical variability and that while there is maternal toxicity at the top dose of 30 mg/ kg/day, there are no relevant effects on reproductive parameters at any dose (John-Greene et al., 1987). Based on the published version of the study, the reproductive NOAEL could be set at 5 mg/kg based on toxicity in the pregnant dams, but we conservatively used the 1 mg/kg/day dose to represent the reproductive NOAEL and compared that to the chronic repeat dose NOAEL of 3 mg/kg/day, resulting in the ratio of 3 that is included in our analysis. The ratio for captan was 7.69 when calculated from the Gadagbui (2005) publication. For captan, Gadagbui (2005) cite a chronic rat NOAEL of 100 mg/kg from IRIS. This appears to be an incorrect entry since IRIS clearly describes effects (decreased parental body weight and a decrease in pup litter weights in a 3generation study) at this dose. The rat chronic NOAEL should be 25 mg/kg since there was no decrease in parental body weight in the 3-generation study at this dose nor any effects observed in a chronic study conducted at doses up to 25 mg/kg/day. The NOAEL of 25 mg/kg/day is also consistent with the conclusion of the European Food Safety Authority (EFSA) (2009c). Using the correct rat chronic NOAEL of 25 mg/kg/day results in a revised ratio of 1.9. Other changes that did not require any substantive interpretation are simply noted by adding a new reference to Table 1. The resulting ratios by the DART tree group are shown in Fig. 1. The first point that Fig. 1 makes is that for the majority of the chemicals the chronic NOAELs (or their corrected surrogate values) were lower than the majority of either the reproductive or developmental NOAELs (ratios less than one are those where the repeat dose NOAEL was lower than the developmental or reproductive NOAEL), in some cases by 3–4 orders of magnitude. Chemicals with distinctive/marked effects (teratogens, hormonal effects, male reproductive toxicants) segregated into the group identified as being associated with chemical structures with known DART precedent activity. Note that some evidence of high dose DART toxicity by chemicals not flagged by the DART tree is

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not unexpected given that the tree focuses primarily on chemicals with selective DART toxicity and if the dose is pushed high enough many chemicals will display some effects on developmental parameters along with parental toxicity.

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This analysis supports the conclusion that chemicals with structural features that are similar to structures that are known to have DART activity as defined by the DART decision tree rules (Wu et al., 2013) have the potential to have NOAELs for DART endpoints that are more divergent from repeat dose NOAELs than are chemicals not associated with structures known to have DART precedent. Consistent with previous opinions, we propose that when repeat dose toxicity data are available but DART data are lacking, that this data gap can be accounted for in the context of an overall risk assessment with the application of a database UF. We propose that for chemicals related to structures with DART precedent, as defined by the DART decision tree, a database UF of 10 be applied as a starting point in a weight of the evidence assessment. This is protective for both developmental and reproductive toxicity based on the range of ratios observed (see Table 1 and Fig. 1) and consistent with previous database UF recommendations. While we collectively refer to DART effects in this document, and the DART decision tree does not distinguish between developmental and reproductive effects. However, from a risk assessment point of view they are distinct endpoints. Therefore in our analysis we evaluated and reported reproductive and developmental NOAELs separately and we have assessed the ratios of repeat dose NOAELs to the two endpoints separately. In our analysis of reproductive toxicity NOAELs, the highest ratios of extrapolated chronic NOAELs/reproductive NOAELs are: caffeine (ratio of 6.23); di(2-ethylhexyl)phthalate (ratio of 6.00); di(2-ethylhexyl)adipate (ratio of 4.1). For caffeine, the DART NOAEL is based on reductions in offspring weight gain, total litter weight, and litter size at the lowest dose tested (12.5 mg/kg/day). At this dose of caffeine, a 3 factor was used to extrapolate from the LOAEL in the reproductive toxicity study because the pup weight reductions were small (7%), did not show a dose response at higher doses, and were associated with maternal body weight reductions. In addition, body weight loss is a generalized effect observed in nearly all repeated dose studies with caffeine and was not more pronounced in studies with longer exposure duration. Therefore, we considered a default full 10X to extrapolate from the LOAEL to a NOAEL as overly conservative. Rabbit developmental toxicity evaluations of caffeine have provided mixed results with an NOAEL of 125 mg/kg and an LOAEL of 100 mg/kg (separate studies) (OECD, 2002a) so including rabbit data would not have resulted in a lower developmental toxicity value. Di(2-ethylhexyl)phthalate had a ratio of 6 for both developmental and reproductive toxicity using values from a recent authoritative review (European Chemicals Bureau, 2008b). The chronic NOAEL chosen was 29 mg/kg/day and the NOAEL of 4.8 mg/kg/day was chosen for both reproductive and developmental endpoints based on what was described as ‘‘minimal testes atrophy’’ at the next highest dose in a three generation reproductive toxicity study. Di(2-ethylhexyl)adipate had the next highest ratio of chronic NOAEL/reproductive NOAEL at 4.1. This ratio is the result of a high chronic NOAEL of 700 mg/kg/day compared to a reproductive toxicity NOAEL of 170 mg/kg/day based on effects at the next considerably higher dose of 1080 mg/kg/day which included reductions in offspring weight gain and total litter weight but no loss in viability (US EPA, IRIS). It is likely that the true NOAEL for these developmental effects was higher than 170 mg/kg/day given the observed pup effects at high dose (higher than a limit dose)

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were relatively minimal and were associated with parental effects of reduced body weight gain. In our analysis of developmental toxicity NOAELs, the highest ratios of extrapolated chronic NOAELs/developmental NOAELs are: thalidomide (ratio of 6) and di(2-ethylhexyl)adipate (ratio of 4.1). The chronic NOAEL/developmental NOAEL ratio for thalidomide, an established potent developmental toxicant, is based on intra-uterine growth retardation observed at 50 mg/kg described by the authors as a minimal LOAEL (Newman et al., 1993). We applied a 10 factor to this developmental LOAEL to derive a rat developmental NOAEL of 5 mg/kg/day, which is conservative since the authors estimated the NOAEL to be 25 mg/kg and went further to estimate that the NOAEL in the rabbit would be 12 mg/kg. The ratio of 4.1 for di(2-ethylhexyl)adipate is based on reduced ossification and kinked or dilated ureters in the fetus (US EPA, 1992). All other extrapolated chronic NOAELs/developmental NOAELs were below 4. Therefore, this analysis supports that a 10 factor would be sufficiently protective to cover all observed ratios for DART decision tree match chemicals. In our analysis, for chemicals that are not related to structures with DART precedent as defined by the DART decision tree but are in domain of the tree (as assessed by scaffold overlap), the largest chronic NOAEL/DART NOAEL ratios were lower. For these chemicals, the highest ratios of extrapolated chronic NOAELs/reproductive NOAELs are: Tridiphane (ratio of 3) based on a questionable decrease in fertility index; Danitol (ratio of 2.4) based on body tremors and increased mortality (note that the NOAEL for parental toxicity in this three generation study was the same based on the same effects); and vinyl acetate (ratio of 2.4) based on a free standing NOAEL at the highest dose tested. All other ratios were 62. Therefore we propose that a default database UF of 3 could be applied for data gaps in either DART endpoints based on the range of ratios observed. As explained in the methods section we choose to focus on rat NOAEL values. We would like to further elaborate on the question of potential impact of rabbit NOAELs for teratogenicity by focusing on the chemicals for which there are significant differences between rat, rabbit and human thresholds as the most critical examples. The Committee on Toxicity of Chemicals in Food, Consumer Products and the Environment (2014) has presented a comprehensive analysis of LOAEL values for developmental toxicity of drugs in rats, rabbits and humans focusing on chemicals with divergent thresholds between humans and the most sensitive animal species. This committee report was most concerned with ratios of greater than 30 between the human LOAEL and the most sensitive animal LOAEL: Misoprostol: They list a human LOAEL of 0.0033 mg/kg/day, a rat LOAEL of 1.6 mg/kg (based on the reproductive study in our table) and a rabbit LOAEL of 1 mg/kg. Thus, the rat and rabbit values were not different. In our analysis we list a chronic rat NOAEL of 0.16 mg/day based on vaginal dilation and discharge (prostaglandin effects). We agree with the chosen LOAEL which was the next higher dose on the dose response curve. Using the paradigm that we are suggesting, if DART data were missing for Misoprostol we would have adjusted the repeat dose NOAEL by a factor of 10 as a database UF resulting in a value of 0.016 mg/ kg/day. This would then have been further adjusted by an interspecies and an intraspecies uncertainty factor in the final risk assessment which would yield a final RfD of less than the reported human LOAEL. The next chemical of concern that they list is phenobarbitol (not included in our analysis). The rat NOAEL was 80 mg/kg and the rabbit NOAEL was 50 mg/kg. The next chemical on their list of concern is phenytoin (diphenylhydantoin). They list a rat LOAEL of 100 mg/kg and a

rabbit LOAEL of 75 mg/kg with a human LOAEL of 1.67 mg/kg. Our review of the literature focused on the rat reproductive NOAEL of 4 mg/kg and developmental NOAEL of 50 mg/kg (different studies). We would have applied a database UF of 10 to the adjusted rat chronic NOAEL of 2.5 mg/kg/day which would have resulted in a point of departure of 0.25 mg/kg/day that would subsequently have been adjusted by intraspecies and interspecies UFs in the final risk assessment. The next chemical in their cohort of concern is thalidomide which we have already discussed and for which the rat and rabbit NOAELs are essentially the same. Other chemicals in their cohort of concern based on large differences between animal and human NOAELs/LOAELs appear to have similar rat and rabbit LOAELs. Examining individual data tables from The Committee on Toxicity of Chemicals in Food, Consumer Products and the Environment (2014) paper, for chemicals with divergent rat and rabbit values that are covered in our analysis, the paper shows isotretinoin with a human LOAEL of 0.17 mg/kg, a rat LOAEL of 30 mg/kg and a rabbit LOAEL of 3 mg/kg. Our analysis of isotretinoin cites a rat chronic NOAEL of 0.2 mg/kg/day, a rat reproductive NOAEL of 32 mg/kg/day and a rat developmental NOAEL of 50 mg/kg/day. The Committee on Toxicity of Chemicals in Food, Consumer Products and the Environment (2014) does not give references so we cannot resolve the discrepancy between their LOAEL value for the rat and our NOAEL value. Using the proposed approach in this paper the rat chronic NOAEL of 0.2 mg/ kg/day would be adjusted by 10 to 0.02 mg/kg which would be further adjusted in a final risk assessment by inter and intra species UFs. None of the other chemicals that they cite with large differences between rat and rabbit LOAEL values are within our dataset. The only other chemical with a large difference, with the rabbit being more sensitive, was valsartan. Valsartan shows a large difference in toxicity between rats and rabbits. Published descriptions of the toxicology studies on this drug are poor. The best descriptions of the studies that we could locate are provided by Novartis (2014). Developmental effects are seen in the presence of maternal toxicity in both species, but in the rabbit these effects occur at doses about two orders of magnitude below the effect levels in the rat. The rat repeat dose NOAEL was 20 mg/kg/day from a 12 month gavage study. In a rat gavage teratology study there was evidence of maternal and fetotoxicity at 600 mg/kg with an NOAEL of 200 mg/kg. A similar NOAEL was reported from a rat two generation study. In a rabbit gavage teratology study maternal and fetal toxicity were seen at 5 mg/kg with an NOAEL of 2 mg/kg. No teratogenicity was reported for either species. Valsartan is associated with structures with precedent in the DART tree so in the absence of DART toxicity data we would apply a 10 factor to the rat NOAEL of 20 mg/kg/day. Thus, the resulting value would be protective even in the absence of rabbit test data. Net, we do not believe that the omission of rabbit NOAELs from the analysis performed in the present work will result in an approach that lacks sufficient conservatism. This conclusion is consistent with the conclusions drawn by others on the value of a second species in DART testing discussed earlier in this paper (e.g., Theunissen et al. 2014). For organic chemicals outside of the domain of the DART decision tree, because they have structures that do not overlap with structures assessed in the construction of the tree, we propose a database UF of 10 could be applied as a conservative starting point to account for missing DART toxicity data. We believe this approach is appropriate due to the possibility that chemicals outside of the chemical domain of the DART decision tree could be as potent as the chemicals associated with DART structure precedence within the domain of the tree. Because we found very few chemicals that were outside of the domain of the DART decision tree, we included metals and OPs in our analysis of ‘out of domain’


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chemicals in this analysis even though they were specifically excluded during development of the tree. However, most metals and OPs have available test data that can be applied and the OPs may be more robustly assessed using an analog/chemical class based approach. In addition, we did not conduct a comprehensive evaluation of the relationship between DART and repeat dose toxicity NOAELs for metals or for OPs. Therefore, we believe that metals and OPs should be evaluated on a case by case basis and in general do not recommend using this database UF approach for these materials. Application of these database UFs to cover DART data gaps to less than chronic repeat dose NOAELs that have not been adjusted for duration or have been adjusted using different duration adjustment factors than those included in this analysis should be evaluated on a case by case basis. There are a variety of approaches for using less than chronic data in risk assessments. Given that the initial analysis of the database UF for DART endpoints was conducted by the US EPA, we chose to apply their conservative default factors for duration adjustment in this analysis (with the exception of the use of subacute data, not addressed by the US EPA (2002a–c)). However, it should be noted that we are recommending these database UFs to fill a DART data gap as a starting point for risk assessment and that it may be possible to adjust these UFs or use partial factors depending on the totality of the data available for the risk assessment. In conclusion, in a given chemical safety assessment DART toxicity potential must be evaluated and both reproductive and developmental effects must be considered. If either type of study or surrogate information is missing from the data set, it may be appropriate to apply a database UF to cover the DART data gap. We propose that the use of the DART decision tree to inform the magnitude of the appropriate database UF when reproductive and/or developmental toxicity data are lacking for a chemical (but when repeat dose data are available) provides a conservative path forward for addressing these data gaps in a weight of the evidence risk assessment. This analysis both supports and extends previous work demonstrating a relationship between the repeat dose and DART NOAELs and provides further support for historical approaches that apply a database UF to fill DART data gaps. As with all weight of the evidence risk assessments, there may be aspects of a dataset on a particular chemical that would suggest a different approach. Therefore this database UF approach to cover DART data gaps should be applied on a case by case basis.

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The Transparency document associated with this article can be found in the online version.

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Metals and female reproductive toxicity.

Reproductive toxicity in rats with crystal nephropathy following high doses of oral melamine or cyanuric acid.

Reproductive and developmental toxicity of styrene.

Reproductive toxicity in acrylamide-treated female mice.

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Indium acetate toxicity in male reproductive system in rats.

Reproductive toxicity of theobromine and cocoa extract in male rats.

The European Community classification of chemicals for reproductive toxicity.

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Reproductive toxicity of nanoscale graphene oxide in male mice.

Reproductive and developmental toxicity of amitraz in sprague-dawley rats.

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Reproductive and developmental toxicity of toluene: a review.

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Abnormal secretion of reproductive hormones and antioxidant status involved in quinestrol-induced reproductive toxicity in adult male rat.

developmental toxicity of 3'-hydroxypterostilbene in experimental animals.