Mixture Risk Assessment of Complex Real-Life Mixtures-The PANORAMIX Project.

Humans are involuntarily exposed to hundreds of chemicals that either contaminate our environment and food or are added intentionally to our daily products. These complex mixtures of chemicals may pose a risk to human health. One of the goals of the European Union's Green Deal and zero-pollution ambition for a toxic-free environment is to tackle the existent gaps in chemical mixture risk assessment by providing scientific grounds that support the implementation of adequate regulatory measures within the EU. We suggest dealing with this challenge by: (1) characterising 'real-life' chemical mixtures and determining to what extent they are transferred from the environment to humans via food and water, and from the mother to the foetus; (2) establishing a high-throughput whole-mixture-based in vitro strategy for screening of real-life complex mixtures of organic chemicals extracted from humans using integrated chemical profiling (suspect screening) together with effect-directed analysis; (3) evaluating which human blood levels of chemical mixtures might be of concern for children's development; and (4) developing a web-based, ready-to-use interface that integrates hazard and exposure data to enable component-based mixture risk estimation. These concepts form the basis of the Green Deal project PANORAMIX, whose ultimate goal is to progress mixture risk assessment of chemicals.

Chemical interactions and mixtures in public health risk assessment: An analysis of ATSDR's interaction profile database.

The Agency for Toxic Substances and Disease Registry (ATSDR) develops interaction profiles using binary weight of evidence (BINWOE) methodology to determine interaction directions of common environmental mixtures. We collected direction of interactions, BINWOE score determination, and BINWOE score confidence rating from 13 interaction profiles along with toxicodynamic and toxicokinetic influences on interaction direction. By doing so, we quantified the 1) direction of interaction and indeterminate evaluations; 2) characterized confidence in the BINWOE determinations; and 3) quantified toxicokinetic/toxicodynamic, and other influences on projected BINWOE interaction directions. Thirty-nine percent (130/336) of the attempts to make a BINWOE were indeterminate due to no interaction data or inadequate or conflicting evidence. Out of remaining BINWOEs, 25% were additive, 9% were greater-than-additive, and 27% were less-than-additive interactions. Fifty-five percent of BINWOEs were explained by toxicokinetic interactions, 12% and 5% were explained by toxicodynamic and other explanations, respectively. High quality mixture toxicology in vivo studies along with mixture in vitro and in silico studies will lead to greater confidence in interaction directions and influences. Limitations for interpretation of the data were also included.

Chemical Mixture Calculator - A novel tool for mixture risk assessment.

Humans are continuously exposed to complex chemical mixtures from foods and the environment. Experimental models in vivo and in vitro have increased our knowledge on how we can predict mixture effects. To accommodate a need for tools for efficient mixture risk assessment across different chemical classes and exposure sources, we have developed fit-for-purpose criteria for grouping of chemicals and a web-based tool for mixture risk assessment. The Chemical Mixture Calculator (available at www.chemicalmixturecalculator.dk) can be used for mixture risk assessment or identification of main drivers of risk. The underlying database includes hazard and exposure estimates for more than 200 chemicals in foods and environment. We present a range of cumulative assessment groups for effects on haematological system, kidney, liver, nervous system, developmental and reproductive system, and thyroid. These cumulative assessment groups are useful for grouping of chemicals at several levels of refinement depending on the question addressed. We present a mixture risk assessment case for phthalates, evaluated with and without contributions from other chemicals with similar effects. This case study shows the usefulness of the tool as a starting point for mixture risk assessment by the risk assessor, and emphasizes that solid scientific insight regarding underlying assumptions and uncertainties is crucial for result interpretation.

Identification of component-based approach for prediction of joint chemical mixture toxicity risk assessment with respect to human health: A critical review.

Toxicity risk assessment of chemical mixture possesses huge challenges due to limited evidence on toxicity of compounds, the infinite number of chemical combinations makes the problem even more difficult. Normally, prediction of joint mixture toxicity depends on toxicological data of constituent compounds, although lack of information on dose-response of chemical mixture raises serious concerns on human health. Component-based approaches mainly use dose-addition or response-addition method to assess mixture toxicity risk exposure. Several models based on theoretical concepts of concentration/dose addition and independent/response action were also developed but these models do not address chemical interactions in mixture, and were mostly used to assess ecological risk exposure with limited or no information on human health risk assessment. This paper reviews available models to predict joint toxicity of chemical mixtures, and most applicable one to address human health risk exposure was identified. United States Environmental Protection Agency (US EPA) weight-of-evidence hazard index (HI) based approach seems to be most appropriate to predict joint toxicity of chemical mixtures, and applicability of model is explained using emerging contaminants as an example. The review also identified challenges in implementing the interaction-based EPA approach and highlighted the need for necessary future research actions.

The Cumulative Risk Assessment of Hepatotoxic Chemicals: A Hepatic Histopathology Perspective.

The increased concern on the consequence of exposure to multiple chemical combinations has led national regulatory authorities to develop different concepts to conduct risk assessments on chemical mixtures. Pesticide residues were identified as "problem formulation" in the respective European regulations and in this context, the European Food and Safety Authority has suggested to group pesticidal active ingredients (AIs) into cumulative assessment groups (CAGs) based on the toxicological properties of each AI. One proposed CAG, on the liver, currently consists of 15 subgroups, each representing a specific hepatotoxic effect observed in toxicity studies. Dietary cumulative risk assessments would then have to be conducted assuming dose additivity of all members of each CAG subgroup. The purpose of this publication is to group AIs based upon the knowledge of the pathogenesis of liver effects to discriminate between primary end points (direct consequence of chemical interaction with a biological target) and secondary end points (which are a consequence of, or that arise out of, a previous pathological change). Focusing on the relevant primary end points strengthens and simplifies the selection of compounds for cumulative risk assessment regarding the liver and better rationalizes the basis for chemical grouping. Relevant dose additivity is to be expected at the level of the primary/leading pathological end points and not at the level of the secondary end points. We recognize, however, that special consideration is needed for substances provoking neoplasia, and this category is included in the group of primary end points for which chemicals inducing them are grouped for risk assessment. Using the pathological basis for defining the respective CAGs, 6 liver subgroups and 2 gallbladder/bile duct groups are proposed. This approach simplifies the cumulative assessment calculation without obviously affecting consumer safety.

Hazard assessment of air pollutants: The transforming ability of complex pollutant mixtures in the Bhas 42 cell model.

The use of in vitro alternative methods is a promising approach to characterize the hazardous properties of environmental chemical mixtures, including urban airborne particulate matter (PM). The aim of this study was to examine seasonal differences in the toxic and transforming potential of PM samples, by using the in vitro cell transformation assay in Bhas 42 cells for the prediction of potential carcinogenic effects. Bhas 42 cells are already initiated, and the v-Ha-ras transfection, together with genetic modification following the immortalization process, makes them a valuable model to study the late steps of cellular transformation leading to the acquisition of the malignant phenotype. Exposure to organic extracts of PM1 and PM2.5 induced dose-related effects. The transforming and cytotoxic properties are related to the amount of PM collected during the sampling campaign and associated with the concentrations of polycyclic aromatic hydrocarbons (PAHs) in the samples. All the samples induced cell transformation following prolonged exposure of 2 weeks. Our results support the utility of the in vitro top-down approach to characterise the toxicity of real mixtures, thereby supporting regulators in the decision-making process. The results also identify the need for appropriate assay selection within the in vitro testing strategy to address the complexity of the final adverse outcomes.

A Novel Approach to Chemical Mixture Risk Assessment-Linking Data from Population-Based Epidemiology and Experimental Animal Tests.

Humans are continuously exposed to chemicals with suspected or proven endocrine disrupting chemicals (EDCs). Risk management of EDCs presents a major unmet challenge because the available data for adverse health effects are generated by examining one compound at a time, whereas real-life exposures are to mixtures of chemicals. In this work, we integrate epidemiological and experimental evidence toward a whole mixture strategy for risk assessment. To illustrate, we conduct the following four steps in a case study: (1) identification of single EDCs ("bad actors")-measured in prenatal blood/urine in the SELMA study-that are associated with a shorter anogenital distance (AGD) in baby boys; (2) definition and construction of a "typical" mixture consisting of the "bad actors" identified in Step 1; (3) experimentally testing this mixture in an in vivo animal model to estimate a dose-response relationship and determine a point of departure (i.e., reference dose [RfD]) associated with an adverse health outcome; and (4) use a statistical measure of "sufficient similarity" to compare the experimental RfD (from Step 3) to the exposure measured in the human population and generate a "similar mixture risk indicator" (SMRI). The objective of this exercise is to generate a proof of concept for the systematic integration of epidemiological and experimental evidence with mixture risk assessment strategies. Using a whole mixture approach, we could find a higher rate of pregnant women under risk (13%) when comparing with the data from more traditional models of additivity (3%), or a compound-by-compound strategy (1.6%).

Assessment of test method variables for in vitro skin irritation testing of medical device extracts.

Skin irritation is an important component of the biological safety evaluation of medical devices. This testing has typically been performed using in vivo models. However, in an effort to reduce the need for in vivo testing, alternative methods for assessing skin irritation potential in vitro have been developed using a Reconstructed Human Epidermis (RhE) model. During the development of the protocol for the round robin validation of in vitro irritation testing for medical device extracts, it became clear that there were three points in the procedure where different options may be validated within each laboratory for routine testing: sample exposure time (18 vs 24h), SDS positive control concentration, and cytokine (IL-1α) release testing. The goal of our study was to evaluate the effect of these variables. EpiDerm™ tissues were exposed to extracts of three plain polymer samples, and four polymers embedded with known irritant chemicals. Exposures were performed for 18 and 24h. Resulting tissue viability was assessed by MTT reduction and IL-1α release was assessed by ELISA. Testing was also performed using various concentrations of SDS ranging from 0.5 to 1% (w/v). Overall, results were similar for samples tested and 18 and 24h, but the 18h exposure time has the potential to have an impact on the results of some sample types. IL-1α testing was shown to be useful to clarify conflicting tissue viability results. Use of a lower concentration of SDS as a positive control can help prevent issues that arise from excessive tissue damage often caused by 1% SDS.

Method to assess component contribution to toxicity of complex mixtures: Assessment of puberty acquisition in rats exposed to disinfection byproducts.

A method based on regression modeling was developed to discern the contribution of component chemicals to the toxicity of highly complex, environmentally realistic mixtures of disinfection byproducts (DBPs). Chemical disinfection of drinking water forms DBP mixtures. Because of concerns about possible reproductive and developmental toxicity, a whole mixture (WM) of DBPs produced by chlorination of a water concentrate was administered as drinking water to Sprague-Dawley (S-D) rats in a multigenerational study. Age of puberty acquisition, i.e., preputial separation (PPS) and vaginal opening (VO), was examined in male and female offspring, respectively. When compared to controls, a slight, but statistically significant delay in puberty acquisition was observed in females but not in males. WM-induced differences in the age at puberty acquisition were compared to those reported in S-D rats administered either a defined mixture (DM) of nine regulated DBPs or individual DBPs. Regression models were developed using individual animal data on age at PPS or VO from the DM study. Puberty acquisition data reported in the WM and individual DBP studies were then compared with the DM models. The delay in puberty acquisition observed in the WM-treated female rats could not be distinguished from delays predicted by the DM regression model, suggesting that the nine regulated DBPs in the DM might account for much of the delay observed in the WM. This method is applicable to mixtures of other types of chemicals and other endpoints.

Human exposure to chemical mixtures: Challenges for the integration of toxicology with epidemiology data in risk assessment.

Little is known about the potential adverse effects from longterm exposure to complex mixtures at low doses, close to health-based reference values. Traditional chemical-specific risk assessment based on animal testing may be insufficient and the lack of toxicological studies on chemical mixtures remains a major regulatory challenge. Hence, new methodologies on cumulative risk assessment are being developed but still present major limitations. Evaluation of chemical mixture effects requires an integrated and systematic approach and close collaboration across different scientific fields, particularly toxicology, epidemiology, exposure science, risk assessment and statistics for a proper integration of data from all these disciplines. Well designed and conducted epidemiological studies can take advantage of this new paradigm and can provide insight to support the correlation between humans low-dose exposures and diseases, thus avoiding the uncertainty associated with extrapolation across species. In this regard, human epidemiology studies may play a significant role in the new vision of toxicity testing. However, this type of information has not been fully considered in risk assessment, mainly due to the inherent limitations of epidemiologic studies. An integrated approach of in vivo, in vitro and in silico data, together with systematic reviews or meta-analysis of high quality epidemiological studies will improve the robustness of risk assessment of chemical mixtures and will provide a stronger basis for regulatory decisions. The ultimate goal is that experimental and mechanistic data can lend support and biological plausibility to the human epidemiological observations.

Should the scope of human mixture risk assessment span legislative/regulatory silos for chemicals?

Current chemicals regulation operates almost exclusively on a chemical-by-chemical basis, however there is concern that this approach may not be sufficiently protective if two or more chemicals have the same toxic effect. Humans are indisputably exposed to more than one chemical at a time, for example to the multiple chemicals found in food, air and drinking water, and in household and consumer products, and in cosmetics. Assessment of cumulative risk to human health and/or the environment from multiple chemicals and routes can be done in a mixture risk assessment (MRA). Whilst there is a broad consensus on the basic science of mixture toxicology, the path to regulatory implementation of MRA within chemical risk assessment is less clear. In this discussion piece we pose an open question: should the scope of human MRA cross legislative remits or 'silos'? We define silos as, for instance, legislation that defines risk assessment practice for a subset of chemicals, usually on the basis of substance/product, media or process orientation. Currently any form of legal mandate for human MRA in the EU is limited to only a few pieces of legislation. We describe two lines of evidence, illustrated with selected examples, that are particularly pertinent to this question: 1) evidence that mixture effects have been shown for chemicals regulated in different silos and 2) evidence that humans are co-exposed to chemicals from different silos. We substantiate the position that, because there is no reason why chemicals allocated to specific regulatory silos would have non-overlapping risk profiles, then there is also no reason to expect that MRA limited only to chemicals within one silo can fully capture the risk that may be present to human consumers. Finally, we discuss possible options for implementation of MRA and we hope to prompt wider discussion of this issue.

[Hygienic assessment of toxic dust factor at the aluminium smelter in Eastern Siberia].

There is presented the assessment of priority toxic matters in the air of working zone for basic occupations of aluminum smelting by electrolysis. There are presented results of different production technologies. There are presented the results of the physical-chemical analysis of the morphology and composition of produced toxic-dust complexes.

Incorporating bioavailability into toxicity assessment of Cu-Ni, Cu-Cd, and Ni-Cd mixtures with the extended biotic ligand model and the WHAM-F(tox) approach.

There are only a limited number of studies that have developed appropriate models which incorporate bioavailability to estimate mixture toxicity. Here, we explored the applicability of the extended biotic ligand model (BLM) and the WHAM-F(tox) approach for predicting and interpreting mixture toxicity, with the assumption that interactions between metal ions obey the BLM theory. Seedlings of lettuce Lactuca sativa were exposed to metal mixtures (Cu-Ni, Cu-Cd, and Ni-Cd) contained in hydroponic solutions for 4 days. Inhibition to root elongation was the endpoint used to quantify the toxic response. Assuming that metal ions compete with each other for binding at a single biotic ligand, the extended BLM succeeded in predicting toxicity of three mixtures to lettuce, with more than 82% of toxicity variation explained. There were no significant differences in the values of f(mix50) (i.e., the overall amounts of metal ions bound to the biotic ligand inducing 50% effect) for the three mixture combinations, showing the possibility of extrapolating these values to other binary metal combinations. The WHAM-F(tox) approach showed a similar level of precision in estimating mixture toxicity while requiring fewer parameters than the BLM-f(mix) model. External validation of the WHAM-F(tox) approach using literature data showed its applicability for other species and other mixtures. The WHAM-F(tox) model is suitable for delineating mixture effects where the extended BLM also applies. Therefore, in case of lower data availability, we recommend the lower parameterized WHAM-F(tox) as an effective approach to incorporate bioavailability in quantifying mixture toxicity.

Challenging conventional risk assessment with respect to human exposure to multiple food contaminants in food: A case study using maize.

Mycotoxins and heavy metals are ubiquitous in the environment and contaminate many foods. The widespread use of pesticides in crop production to control disease contributes further to the chemical contamination of foods. Thus multiple chemical contaminants threaten the safety of many food commodities; hence the present study used maize as a model crop to identify the severity in terms of human exposure when multiple contaminants are present. High Content Analysis (HCA) measuring multiple endpoints was used to determine cytotoxicity of complex mixtures of mycotoxins, heavy metals and pesticides. Endpoints included nuclear intensity (NI), nuclear area (NA), plasma membrane permeability (PMP), mitochondrial membrane potential (MMP) and mitochondrial mass (MM). At concentrations representing legal limits of each individual contaminant in maize (3ng/ml ochratoxin A (OTA), 1µg/ml fumonisin B1 (FB1), 2ng/ml aflatoxin B1 (AFB1), 100ng/ml cadmium (Cd), 150ng/ml arsenic (As), 50ng/ml chlorpyrifos (CP) and 5µg/ml pirimiphos methyl (PM), the mixtures (tertiary mycotoxins plus Cd/As) and (tertiary mycotoxins plus Cd/As/CP/PM) were cytotoxic for NA and MM endpoints with a difference of up to 13.6% (p≤0.0001) and 12% (p≤0.0001) respectively from control values. The most cytotoxic mixture was (tertiary mycotoxins plus Cd/As/CP/PM) across all 4 endpoints (NA, NI, MM and MMP) with increases up to 61.3%, 23.0%, 61.4% and 36.3% (p≤0.0001) respectively. Synergy was evident for two endpoints (NI and MM) at concentrations contaminating maize above legal limits, with differences between expected and measured values of (6.2-12.4% (p≤0.05-p≤0.001) and 4.5-12.3% (p≤0.05-p≤0.001) for NI and MM, respectively. The study introduces for the first time, a holistic approach to identify the impact in terms of toxicity to humans when multiple chemical contaminants are present in foodstuffs. Governmental regulatory bodies must begin to contemplate how to safeguard the population when such mixtures of contaminants are found in foods and this study starts to address this critical issue.

Effect-based assessment of persistent organic pollutant and pesticide dumpsite using mammalian CALUX reporter cell lines.

A combined chemical and biological analysis of samples from a major obsolete pesticide and persistent organic pollutant (POP) dumpsite in Northern Tajikistan was carried out. The chemical analytical screening focused on a range of prioritized compounds and compounds known to be present locally. Since chemical analytics does not allow measurements of hazards in complex mixtures, we tested the use of a novel effect-based approach using a panel of quantitative high-throughput CALUX reporter assays measuring distinct biological effects relevant in hazard assessment. Assays were included for assessing effects related to estrogen, androgen, and progestin signaling, aryl hydrocarbon receptor-mediated signaling, AP1 signaling, genotoxicity, oxidative stress, chemical hypoxia, and ER stress. With this panel of assays, we first quantified the biological activities of the individual chemicals measured in chemical analytics. Next, we calculated the expected sum activity by these chemicals in the samples of the pesticide dump site and compared the results with the measured CALUX bioactivity of the total extracts of these samples. The results showed that particularly endocrine disruption-related effects were common among the samples. This was consistent with the toxicological profiles of the individual chemicals that dominated these samples. However, large discrepancies between chemical and biological analysis were found in a sample from a burn place present in this site, with biological activities that could not be explained by chemical analysis. This is likely to be caused by toxic combustion products or by spills of compounds that were not targeted in the chemical analysis.

A novel safety assessment strategy applied to non-selective extracts.

A main challenge in food safety research is to demonstrate that processing of foodstuffs does not lead to the formation of substances for which the safety upon consumption might be questioned. This is especially so since food is a complex matrix in which the analytical detection of substances, and consequent risk assessment thereof, is difficult to determine. Here, a pragmatic novel safety assessment strategy is applied to the production of non-selective extracts (NSEs), used for different purposes in food such as for colouring purposes, which are complex food mixtures prepared from reference juices. The Complex Mixture Safety Assessment Strategy (CoMSAS) is an exposure driven approach enabling to efficiently assess the safety of the NSE by focussing on newly formed substances or substances that may increase in exposure during the processing of the NSE. CoMSAS enables to distinguish toxicologically relevant from toxicologically less relevant substances, when related to their respective levels of exposure. This will reduce the amount of work needed for identification, characterisation and safety assessment of unknown substances detected at low concentration, without the need for toxicity testing using animal studies. In this paper, the CoMSAS approach has been applied for elderberry and pumpkin NSEs used for food colouring purposes.

State of the art in the application of QSAR techniques for predicting mixture toxicity in environmental risk assessment.

The focus of regulatory chemical risk assessment has been mainly placed on single chemicals rather than mixtures. However, living organisms and the environment might be exposed to mixtures of chemicals. Many scientific studies have revealed that mixture toxicity can arise from the combined effects of components present at levels below their individual no-effect concentrations. Predictive approaches will be essential for estimating mixture toxicity, as the number of possible mixtures is extremely large. Although predictive models are virtually indispensable for estimating mixture toxicity for both scientific and regulatory purposes, risk assessors encounter substantial difficulties in using conventional models, mainly due to the lack of information on the modes of toxic action of the mixture constituents. Alternative models that use different information instead of the modes of action thus need to be developed. The objective of this study is to investigate the state of the art in predictive models based on quantitative structure-activity relationship techniques for estimating the toxicity of mixture components, and to identify future challenges hindering more reliable mixture risk assessment for environmental risk assessment. Alternative models need to be developed not only to overcome the limitations of conventional models, but also to improve their performance.

Interactions between polycyclic aromatic hydrocarbons in complex mixtures and implications for cancer risk assessment.

In this review we discuss the effects of exposure to complex PAH mixtures in vitro and in vivo on mechanisms related to carcinogenesis. Of particular concern regarding exposure to complex PAH mixtures is how interactions between different constituents can affect the carcinogenic response and how these might be included in risk assessment. Overall the findings suggest that the responses resulting from exposure to complex PAH mixtures is varied and complicated. More- and less-than additive effects on bioactivation and DNA damage formation have been observed depending on the various mixtures studied, and equally dependent on the different test systems that are used. Furthermore, the findings show that the commonly used biological end-point of DNA damage formation is insufficient for studying mixture effects. At present the assessment of the risk of exposure to complex PAH mixtures involves comparison to individual compounds using either a surrogate or a component-based potency approach. We discuss how future risk assessment strategies for complex PAH mixtures should be based around whole mixture assessment in order to account for interaction effects. Inherent to this is the need to incorporate different experimental approaches using robust and sensitive biological endpoints. Furthermore, the emphasis on future research should be placed on studying real life mixtures that better represent the complex PAH mixtures that humans are exposed to.

A novel safety assessment strategy for non-intentionally added substances (NIAS) in carton food contact materials.

One of the main challenges in food contact materials research is to prove that the presence of non-intentionally added substances (NIAS) is not a safety issue. Migration extracts may contain many unknown substances present at low concentrations. It is difficult and time-consuming to identify all these potential NIAS and concurrently to assess their health risk upon exposure, whereas the health relevance at low exposure levels might not even be an issue. This paper describes a scientifically based, but pragmatic safety assessment approach for unknown substances present at low exposure levels in food contact matrices. This complex mixture safety assessment strategy (CoMSAS) enables one to distinguish toxicologically relevant from toxicologically less relevant substances, when related to their respective levels of exposure, and allows one to focus on the substances of potential health concern. In particular, substances for which exposure will be below certain thresholds may be considered not of health relevance in case specific classes of substances are excluded. This can reduce the amount of work needed for identification, characterisation and evaluation of unknown substances at low concentration. The CoMSAS approach is presented in this paper using a safety assessment of unknown NIAS that may migrate from three carton samples.

Genotoxic mixtures and dissimilar action: concepts for prediction and assessment.

Combinations of genotoxic agents have frequently been assessed without clear assumptions regarding their expected (additive) mixture effects, often leading to claims of synergisms that might in fact be compatible with additivity. We have shown earlier that the combined effects of chemicals, which induce micronuclei (MN) in the cytokinesis-block micronucleus assay in Chinese hamster ovary-K1 cells by a similar mechanism, were additive according to the concept of concentration addition (CA). Here, we extended these studies and investigated for the first time whether valid additivity expectations can be formulated for MN-inducing chemicals that operate through a variety of mechanisms, including aneugens and clastogens (DNA cross-linkers, topoisomerase II inhibitors, minor groove binders). We expected that their effects should follow the additivity principles of independent action (IA). With two mixtures, one composed of various aneugens (colchicine, flubendazole, vinblastine sulphate, griseofulvin, paclitaxel), and another composed of aneugens and clastogens (flubendazole, doxorubicin, etoposide, melphalan and mitomycin C), we observed mixture effects that fell between the additivity predictions derived from CA and IA. We achieved better agreement between observation and prediction by grouping the chemicals into common assessment groups and using hybrid CA/IA prediction models. The combined effects of four dissimilarly acting compounds (flubendazole, paclitaxel, doxorubicin and melphalan) also fell within CA and IA. Two binary mixtures (flubendazole/paclitaxel and flubendazole/doxorubicin) showed effects in reasonable agreement with IA additivity. Our studies provide a systematic basis for the investigation of mixtures that affect endpoints of relevance to genotoxicity and show that their effects are largely additive.