© 2002 by CRC Press LLC Section III Applications of SSDs This section presents various applications of species sensitivity distributions (SSDs) to illustrate the ways in which SSDs are currently used in practice. It has two subsections, A on derivation of environmental quality criteria and B on ecological risk assessment of contaminated ecosystems. The first subsection starts with a description of the true start of adopting SSD-based methods in an international regulatory context. Further, the subsection presents four examples of implementation of SSDs in the derivation of environmental quality criteria, two from North America, and two from Europe. The second subsection presents six examples of applications of SSDs in ecological risk assessment that illustrate the range of environmental problems that can be tackled by SSD-based methods, alone or combined with other methods. The chapters show how SSDs can function in a range of applications, from formal tiered risk assessment schemes to life cycle assessments of manufactured products. The chapters presented here were meant to present the range of applications of SSDs, without attempting complete coverage of all SSD applications. © 2002 by CRC Press LLC A. Derivation of Environmental Quality Criteria © 2002 by CRC Press LLC Effects Assessment of Fabric Softeners: The DHTDMAC Case Cornelis J. van Leeuwen and Joanna S. Jaworska CONTENTS 10.1 Introduction 10.2 DHTDMAC Behavior in Water 10.3 Effects Assessment of DHTDMAC 10.4 Risk Management 10.5 Discussions about the Selection of Species and Testing for Ecotoxicity 10.6 Discussions about the Extrapolation Methodology 10.7 Communication and Validation: The Development of a Common Risk Assessment Language 10.8 Current Activities Abstract — DHTDMAC was a test case for the ecotoxicological risk assessment of chemicals. High political and economic stakes were involved. There is no doubt that the (inter)national discussions on DHTDMAC accelerated the mutual acceptance of the new extrapolation methodologies to assess environmental effects of chemicals based on Species Sensitivity Distributions. These discussions went through a three-step process of (1) confrontation, (2) communication, and (3) cooperation. From a general perspec- tive, the cooperation evolved to European Union (EU)-approved risk assessment meth- odologies. In a more limited sense, the DHTDMAC case resulted in the development and marketing of a new generation of fabric softeners that are readily biodegradable. 10.1 INTRODUCTION DHTDMAC, dihydrogenated-tallow dimethyl ammonium chloride (Figure 10.1), a quaternary ammonium surfactant, has been used as a fabric softener, to the exclusion of almost all other substances, in the household laundry rinsing process. Consequently, the chemical has been widely dispersed and may have contaminated the aquatic and terrestrial environment even after sewage treatment. The technical-grade product 10 © 2002 by CRC Press LLC contains impurities such as mono- and trialkyl ammonium compounds with varying carbon chain lengths from C 14 to C 18 . The C 18 variety is the most abundant. In the Netherlands about 2000 tonnes/year (as active ingredient) were used in the early 1990s. For the whole of Europe the amount used was approximately 50,000 tonnes/year. In 1990, the use of fabric softeners became a political issue as a result of a discussion in the Dutch Parliament. This discussion was the result of disagreements between the detergent industry and representatives of the Dutch Ministry of the Environment (VROM) regarding the conclusions of a report prepared by the Dutch Consultative Expert Group Detergents–Environment (DCEGDE, 1988). An alterna- tive risk assessment on DHTDMAC, including the comments of the detergent indus- try and a reaction by the representatives of VROM, was published in a Dutch journal (Van Leeuwen, 1989). This article catalyzed policy discussions and attracted public attention in the media. In the end, fabric softeners containing DHTDMAC were classified as dangerous for the environment. In the discussions and publications in the 1990s the acronym DTDMAC was most often used, which actually refers to DHTDMAC but with some unsaturated bonds in the alkyl chains. As a result of risk management discussions between the Netherlands Association of Detergent Industries and VROM (VROM/NVZ, 1992; De Nijs and de Greef, 1992; Roghair et al., 1992; Van Leeuwen et al., 1992a) and to reduce the uncertainties in risk assessment for this type of compound, additional research on DHTDMAC was conducted at the National Institute of Public Health and the Environment (RIVM) in the Netherlands. The studies comprised (1) exposure modeling of DHT- DMAC in the Netherlands, (2) chemical analyses of the substance in effluents, sewage sludge, and surface waters, and (3) assessment of ecotoxicological effects. The DHTDMAC case was the first case in which extrapolation methodologies based on Species Sensitivity Distributions (SSDs) were applied in risk assessment of industrial chemicals in the European Union (EU). But the DHTDMAC case was more. It was a classical clash between (1) science (ecotoxicological extrapolation methodology and SSDs), (2) environmental policy (the application of the precau- tionary approach; i.e., how to deal with uncertainties in risk assessment), and (3) the economy (the high market value of the fabric softeners for the chemical industry in the Netherlands and Europe). After this debate, a constructive cooperation followed between industry, VROM and RIVM. This chapter describes these risk evaluations of DHTDMAC and the cooperative actions. Note that the prediction of environmental concentrations is also subject to recent modeling development (e.g., Feijtel et al., 1997; Boeije et al., 2000), but the description of that subject in detail is beyond the scope of this chapter. FIGURE 10.1 Chemical structure of DHTDMAC. N + H 3 C H 3 C Cl (CH 2 ) 17 CH 3 (CH 2 ) 17 CH 3 – © 2002 by CRC Press LLC 10.2 DHTDMAC BEHAVIOR IN WATER DHTDMAC is a difficult substance to assess because of (1) its extremely low water solubility (<0.52 pg/l), (2) its high adsorptivity (with strong ionic and hydrophobic interactions), (3) its tendency to form complexes with anionic substances and min- erals, and (4) the formation of precipitates. As is evident from the high variability in the available data sets, all these properties have implications for the estimation of physicochemical parameters, bioavailability, ecotoxicity, and monitoring. For example, reported sorption coefficients to suspended solids vary between 3,833 and 85,000 l/kg (Van Leeuwen, 1989; ECETOC, 1993a). The rate of decomposition of DHTDMAC greatly depends on the presence of sediment, microbial adaptation, and the type of dosing. Degradation is likely to be slow in surface water, where the concentrations are generally lower than those used in laboratory biodegradation tests. Studies with similar cationic surfactants have led the Dutch Consultative Expert Group Detergents–Environment (DCEGDE, 1988) to the conclusion that degradation will probably fail in surface water that has not been adapted; however, after adaptation the substance becomes inherently, completely biodegradable (ECETOC, 1993a). In 1990, no data were available on the anaerobic degradation in aquatic sediments. The laboratory results on aquatic toxicity of DHTDMAC are highly dependent on test conditions, sample preparation, and the presence of impurities. Compared with other surfactants, the chemical appears to be relatively toxic to algae when tested in reconstituted water. In natural waters, effects may be observed at concen- trations two to three orders of magnitude higher. In reconstituted water, the lowest no-observed effect concentration (NOEC) was observed with Selenastrum capricor- nutum (0.006 mg/l). In treated sewage effluents diluted in river water the NOEC for Selenastrum was 20.3 mg/l (Versteeg et al., 1992). Because of the extremely low solubility of DHTDMAC in the reconstituted water experiments, isopropanol was used as a carrier solvent. At this moment there is limited understanding of the physical form of DHTDMAC in this toxicity test. However, opinions have been expressed that this may have a strong impact on the results. In addition, MTTMAC (the derivative mono-tallow trimethyl ammonium chloride) is present in the recon- stituted water studies with commercial-grade DHTDMAC and its contribution to toxicity should be taken into account because it is more toxic than DHTDMAC, but readily biodegradable. 10.3 EFFECTS ASSESSMENT OF DHTDMAC What follows here is a summary of the work done by the Ministry of VROM and RIVM as published in 1992 (Van Leeuwen et al., 1992a). There were two major discussions at that time: (1) a discussion about the validity of the input data (the results of the toxicity tests) and (2) a discussion about the effects assessment (extrap- olation) methods. This is why different sets of toxicity data were used (Table 10.1) and why different effect assessment methods were applied on these data (Table 10.2). The results of the ecotoxicity studies from Roghair et al. (1992), the Dutch Consultative Expert Group Detergents–Environment (DCEGDE, 1988) and Lewis and Wee (1983) are summarized in Table 10.1. The NOECs are nominal concentrations © 2002 by CRC Press LLC that have been corrected for the DHTDMAC content of the technical-grade product that was tested. The results show that the algae Microcystis aeruginosa, Selenastrum capricornutum , and Navicula seminulum are the most sensitive and the bacteria the least sensitive. The differences in toxicity to the fish species Gasterosteus aculeatus and Pimephales promelas , the midge larva Chironomus riparius , the crustacean Daphnia magna , and the water snail Lymnea stagnalis are very small. All the tests done with surface water (Table 10.1, Set A) produced higher NOEC values than the tests done with standard water without suspended material (set B). This can be easily explained by the adsorption of cationic surfactants to suspended matter which results in a reduced biological availability. The same has been observed TABLE 10.1 NOEC Values (mg/l) Used to Calculate MPC and NC for DHTDMAC According to Various Risk Assessment Methods a Species Set A Set B Gasterosteus aculeatus 0.58* — Pimephales promelas b 0.23 0.053 Chironomus riparius 1.03* — Daphnia magna b 0.38 — Lymnaea stagnalis 0.25* — Scenedesmus pannonicus 0.58* — Selenastrum capricornutum 0.71 c 0.020 d Microcystis aeruginosa 0.21 c 0.017 d Navicula seminulum — 0.023 d Photobacterium phosphoreum 4.27* — Nitrifying bacteria 2.31* — Note: Set A are tests carried out in surface water, whereas the data presented in Set B are results of toxicity tests carried out in standard water without suspended matter. The data derived from Roghair et al. (1992) are nominal concentrations expressed as the active ingredient as indicated by an asterisk (*). The remaining data are taken from the Dutch Consultative Expert Group Deter- gents–Environment (DCEGDE, 1988) and Lewis and Wee (1983). a Set A was used for the MPC and NC calculations using methods 1, 3, 4, and 5. Set B was used for the risk assessment according to method 2 (Van der Kooy et al., 1991). b NOECs are based on measured concentrations of DHTDMAC in water. The test with D . magna was carried out with DSDMAC (distearyl dimethyl ammonium chloride). c This is an algistatic concentration. The actual NOEC value is therefore lower. d NOEC values for algae were obtained from the EC 50 values divided by a factor of three. © 2002 by CRC Press LLC in a study by Lewis and Wee (1983), who demonstrated a variation in toxicity to algae of 200 to 2600 µg/l due to varying amounts of suspended matter in the water. Similar observations have been made by Pittinger et al. (1989). Therefore, by car- rying out studies with surface water containing suspended matter (1 to 4 mg/l), the reduced biological availability and therefore reduced toxicity was taken into account. It is important to note that the OECD guidelines (OECD, 1984) for mimicking river water suggested much higher values of suspended solids (10 to 20 mg/l) as well as 2 to 5 mg/l of dissolved organic carbon. The data presented in Table 10.1 were used to calculate the maximum permis- sible concentrations (MPC) and the negligible concentrations (NC, see Chapter 12 for explanation) for DHTDMAC according to five different effects assessment meth- ods. The results of these calculations are shown in Table 10.2. Method 1: The method entails to applying a safety factor of ten to the lowest NOEC. It is used in the United States to calculate concern levels (U.S. EPA, 1984b) and by the EU for the risk assessment of new and existing chemicals (CEC, 1996). Method 2: The Dutch Ministry of Transport and Public Works used this method. It is applied to the lowest NOEC (expressed as dissolved concentration) obtained from experiments carried out with at least the following group of species: fish, crustacean, mollusks, and algae. If nominal concentrations rather than measured concentrations are given, the NOEC should be corrected for this. The combined toxicity of similar substances should also be taken into account. The “dissolved” concentrations in water TABLE 10.2 MPCs and NCs for DHTDMAC Calculated Using the Data in Table 10.1 Method MPC NC 1. Hansen (1989); U.S. EPA (1984b) 21 0.21 2. Van der Kooy et al. (1991) a 16 0.16 3. Van Straalen and Denneman (1989) 63 0.63 4. Van de Meent et al. (1990b) b 27–100 0.27–1.0 5. Van de Meent et al. (1990b) b 18–90 0.18–0.9 Note: NC is 1% of MPC (VROM, 1989b). Values are given in µ g/l and represent “total” concentrations of DHTDMAC in sur- face water. a A suspended matter content of 30 mg/l, a solids–water parti- tion coefficient ( K sw ) of 8.5 × 10 4 l/kg, and a correction factor of 0.8 for combined toxicity were used. As dissolved concentra- tions were not determined in the tests with algae, the lowest NOEC from the study was divided by 3 for the calculations. b The interval represents the confidence interval of the calculated 95% protection level of the species. The upper limit is the median value. The lowest value represents the lower limit of the 95% confidence interval. © 2002 by CRC Press LLC are then converted to “total” concentrations (dissolved + adsorbed), assuming a sus- pended matter concentration in surface water of 30 mg/l and an experimental or estimated sediment–water partition coefficient (VROM, 1989b). Method 3: This is the Van Straalen and Denneman (1989) method, reviewed by the Health Council of the Netherlands (1989) and proposed in Premises for Risk Management (VROM, 1989b). According to this method, the 95% protection level for species is calculated under the assumption that the SSD can be described by a log-logistic function. Method 4: This is Van Straalen and Denneman’s method as modified by Van de Meent et al. (1990b). In this method the 95% protection level of the species is calculated using Bayesian statistics. This method also provides a median value and an estimate of the confidence limits of the 95% protection level. Method 5: This method is described in detail by Van de Meent et al. (1990b). It differs from method 4 only in the selection of data: 1. If more than one toxicity study is done with the same species and different toxicological criteria, the lowest NOEC is used. 2. If several toxicity studies are done with the same species and the same toxicological criterion, the geometric average of these values is used. 3. The lowest NOEC for each taxonomic group (fish, insects, crustaceans, mollusks, green algae, blue-green algae, bacteria, etc.) is used. More specifically, in the case of DHTDMAC, the tests with Photobacterium phosphoreum and G. aculeatus were excluded (Figure 10.2). At that time is was concluded that the results of the various risk calculations for cationic surfactants were remarkably close, and were equivalent to the variation in the reproducibility of toxicological experiments. It was also not possible to make a FIGURE 10.2 Cumulative distribution of DHTDMAC toxicity data fitted to logistic model of log-transformed data. NOEC (mg/l) 0.01 0.1 1 10 100 1000 Cumulative Probability 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 nitrifying bacteria Chironomus riparius Scenedesmus pannonicus Daphnia magna Lymnaea stagnalis Pimephales promelas Microcystis aeruginosa species logistic cdf © 2002 by CRC Press LLC definitive choice about the preferred extrapolation method. Further international discussions were needed on these methods. From a risk management point of view, the risk assessment problem was solved in a practical manner. To arrive at an MPC it was proposed to use the average of the results of the different extrapolation methodologies and the MPC was set at 50 µ g/l (Van Leeuwen et al., 1992a). A year later, the Van Straalen and Denneman method was refined by Aldenberg and Slob (1993) who introduced confidence limits to the HC 5 . The method of Aldenberg and Slob (1993) was officially adopted by the Dutch authorities and is still in use today. 10.4 RISK MANAGEMENT On the basis of single-species laboratory toxicity data and various extrapolation methods, an MPC of 50 µ g/l and an NC of 0.5 µ g/l (Van Leeuwen et al., 1992a) were derived. In the same assessment, exposure calculations, assuming no degrada- tion, indicated a median concentration of 3 µ g/l and a 90th percentile of 45 µ g/l. In 1990, concentrations of 6 to 25 µ g/l were measured in the Rhine, Meuse, and Scheldt Rivers (Van Leeuwen et al., 1992a). Model predictions indicated that in approxi- mately 30 to 40% of the surface waters considerably higher DHTDMAC concen- trations were expected to occur (Van Leeuwen et al., 1992a). At the same time, industry initiated its own risk assessment, including generation of additional data, and reached different conclusions due to differences in accounting for degradation, solubility, and, most importantly, bioavailability. Using a similar modeling approach as van Leeuwen et al. (1992a) but with in-stream removal, Versteeg et al. (1992) concluded that the median environmental concentration of DHTDMAC was 7 µ g/l and the 90th percentile was 21 µ g/l. Furthermore, Versteeg et al. (1992) used a novel approach to calculate a chronic “practical” NOEC that addressed the difference between bioavailability in laboratory studies and in the real environment. In these experiments continuous activated sludge units were fed with sewage dosed with DHTDMAC and the chronic toxicity tests were performed with the effluent. The lowest NOEC of 4.53 mg/l, found for Ceriodaphnia dubia , demonstrated a marked attenuation of toxicity in the presence of suspensed solids and in the absence of MTTMAC. VROM concluded that this approach transferred the problems from the water phase into suspendend solids and sediments phases and that this could not be the objective of sound environmental policy. On the basis of these results (and dis- agreements), which were discussed in the Dutch Parliament in spring 1990, the Neth- erlands Association of Detergent Industries agreed to replace DHTDMAC by chemi- cals of lower environmental concern within a period of 2 years. By the end of 1990 (Giolando et al., 1995), almost all DHTDMAC had already been replaced by a readily biodegradable substitute: DEEDMAC (diethyl ester dimethyl ammonium chloride). 10.5 DISCUSSIONS ABOUT THE SELECTION OF SPECIES AND TESTING FOR ECOTOXICITY The use of extrapolation techniques is based on the recognition that not all species are equally sensitive. Furthermore, it is assumed that by protecting the structure of © 2002 by CRC Press LLC ecosystems (i.e., the qualitative and quantitative distribution of species) their func- tional characteristics will also be safeguarded. Differences in sensitivity are the results of true interspecies variability (e.g., uptake-elimination kinetics, biotransfor- mation, differences in the receptors, repair mechanisms), as well as variability in the experimental design (experimental errors and the composition of test media, e.g., pH, salinity, suspended matter, duration of the test, etc.). Van Straalen and Van Leeuwen (Chapter 3) discuss these aspects in more detail. In the case of DHTDMAC, discussions took place regarding all these aspects, i.e., the exclusion of the Microtox test and the exclusion of very susceptible species. It was clear to everybody that the exclusion of very susceptible and very tolerant species had a great impact on the value of the MPC. This extrapolation methodology demonstrated the great influence of aspects that have nothing to do with the statistical extrapolation technique, but everything to do with ecotoxicological test design and practical aspects of testing, e.g., the low solubility of DHTDMAC, the presence of suspended matter in the test media, and the density of algae (bioavailability of DHTDMAC), the presence of toxic impurities (MTTMAC), the minimal number of single-species toxicity tests necessary to predict effects at the ecosystem level, and the selection of these species (ecosystem sampling). The essence was a discussion about the limitations of single- species toxicity testing for predicting effects at the ecosystem level from a theoretical as well as a practical point of view. 10.6 DISCUSSIONS ABOUT THE EXTRAPOLATION METHODOLOGY Adopting the percentage of “unprotected” species or the implementation of the 95% protection level as the MPC was probably one of the biggest mistakes in commu- nicating extrapolation methodologies to the scientific and regulatory community. Many people interpreted this as if 5% of the species were sacrificed with each chemical that came on the market. This also resulted in discussion in the Dutch Parliament within the framework of the National Environmental Policy Plan (VROM, 1991). In retrospect, it would have been better to promote that the policy objective is to prevent ecosystems against the adverse effects of chemicals and that a “statistical cut-off value” of 5% is needed to obtain the MPC. At the time of the DHTDMAC debate, the extrapolation methodologies were not yet validated in terms of MPCs derived from field studies. The development of validation activities was certainly stimulated by the DHTDMAC discussion (Emans et al., 1993; Versteeg et al., 1999). Lively discussions were generated on all other aspects, such as the minimal number of entry points (the sample sizes), their repre- sentativeness, the shape of the SSDs (e.g., the logistic, normal, and triangular distribution), the statistical verification of the assumed distribution (see Figure 10.2), the ecological relevance of this approach, and the fact that the whole idea was new. However, the main impact was not that this new methodology was scientifically discussed, but that it was applied and could have enormous economic consequences for the detergent industry. It was new and paradigm-breaking. [...]... Examples 12 .3. 1.1 Refined Effect Assessment 12 .3. 1.2 Preliminary Effect Assessment 12 .3. 1 .3 Added Risk Approach 12 .3. 1.4 Secondary Poisoning 12 .3. 1.5 Equilibrium Partitioning Method 12 .3. 1.6 Probabilistic Modeling 12 .3. 1.7 Harmonization 12 .3. 2 Current ERLs and EQSs 12 .3. 3 Concluding Remarks Appendix: Human Toxicological Risk Limits and Integration with ERLs Abstract — In the Netherlands, environmental risk... extrapolated single -species toxicity data are given in Table 10 .3 Recently, Versteeg et al (1999) worked further on validation of the extrapolation approach They summarized the chronic single -species and experimental ecosystem data on a variety of substances (n = 11) including heavy metals, pesticides, surfactants, and general organic and inorganic compounds Single -species data were summarized as genus-specific... (H = 10%, L = 25), in mg/kg R(exp) = reference value for soil or sediment used in the experiment (H = y%, L = z%), in mg/kg © 2002 by CRC Press LLC TABLE 12 .3 Empirical Reference Lines for Calculating the Background Concentration for Different Dutch Soils and Sediments Metal or Metalloid Reference Line for Soil or Sediment Cb 3. 0 15 + 0.4 (L + H) 30 + 5L 0 .3 + 0. 033 L 0.4 + 0.007(L + 3H) 50 + 2L 2 + 0.28L... minimum required number of MAVs is low, it will increase the probability that low © 2002 by CRC Press LLC percentiles will be calculated by extrapolation, which results in benchmarks that have greater uncertainty than benchmarks obtained by interpolation However, increasing the minimum required number of MAVs will tend to increase the cost of satisfying the MDRs b If amphibians, fishes, and aquatic invertebrates... carried out in © 2002 by CRC Press LLC TABLE 10 .3 Final MPC and NC Expressed as Dissolved Concentrations in ␮g/l for LAS, AE, AES, and Soap Surfactant MPC Based on Single -Species Data Range of Field NOECs Final MPC NC LAS AE AES Soap 32 0 110 400 27 250–500 42 38 0 190 37 00 — 250 110 400 27 2.5 1.1 5 0.27 Source: Van de Plassche, E J et al., Environmental Toxicology and Chemistry, 18, 26 53, 1999 With... methodologies on deriving ERLs are described in Section 12.2 In Section 12 .3 some examples are provided and reference is made to the current set of ERLs and EQSs in the Netherlands; the section finishes with some concluding remarks 12.1.2 POLICY BACKGROUND As described in the Third National Environmental Policy Plan (VROM, 1998), environmental policy in the Netherlands has taken two tracks: the source-oriented... were available at that time A comparison was made between the MPCs from field and extrapolated single -species studies for 23 data pairs (including the less reliable studies) The MPC based on field studies was generally higher than the MPC based on single -species tests, but the geometric mean of extrapolated single -species MPCs did not differ significantly from the geometric mean of the MPCs based on field... Limits in the Netherlands Dick T H M Sijm, Annemarie P van Wezel, and Trudie Crommentuijn CONTENTS 12.1 Introduction 12.1.1 Focus, Aim, and Outline 12.1.2 Policy Background 12.1 .3 ERLs and EQSs in the Netherlands 12.1 .3. 1 Ecotoxicological Serious Risk Concentration 12.1 .3. 2 Maximum Permissible Concentration 12.1 .3. 3 Negligible Concentration 12.1.4 EQSs in the Dutch Environmental Policy 12.1.4.1 Intervention... 12.2 .3. 4 Sorption Coefficients 12.2.4 Calculating Environmental Risk Limits (Step 3) 12.2.4.1 Refined Effect Assessment 12.2.4.2 Preliminary Effect Assessment 12.2.4 .3 The Added Risk Approach 12.2.4.4 Secondary Poisoning © 2002 by CRC Press LLC 12.2.4.5 Equilibrium Partitioning Method 12.2.4.6 Probabilistic Modeling 12.2.5 Harmonization (Step 4) 12 .3 Examples and Current ERLs and EQSs 12 .3. 1 Examples 12 .3. 1.1... this procedure for calculating sensitivity factors applied normal distribution theory to the data that were available concerning the sensitivities of species to a variety of pollutants These same factors were used in the second version of the guidelines (U.S EPA, 1979), where they were called species sensitivity factors.” 11 .3 THE 1980 GUIDELINES The third version of the guidelines was published as part . results in bench- marks that have greater uncertainty than benchmarks obtained by inter- polation. However, increasing the minimum required number of MAVs will tend to increase the cost of satisfying. n = 11) including heavy metals, pesticides, surfac- tants, and general organic and inorganic compounds. Single -species data were sum- marized as genus-specific geometric means using the NOEC. distribution of species) their func- tional characteristics will also be safeguarded. Differences in sensitivity are the results of true interspecies variability (e.g., uptake-elimination kinetics,