Environmental Health Perspectives Vol. 42, pp. 9-13, 1981 Dose-Response Analysis in Animal Studies: Prediction of Human Responses by Yves Alarie* An animal bioassay has been used to evaluate a series of airborne chemicals for their sensory irritating properties to the upper respiratory tract. The results obtained can be used to rank their potency. An attempt has been made to predict "safe" levels of exposure for humans on the basis of this short-term assay. A good correlation was obtained between the predicted "safe" levels of exposure and current Threshold Limit Values established for industrial exposures. Introduction Epidemiologists and toxicologists have shared a concern about the effects of chemicals on human health. Both are involved in devising protocols to study the effects of chemicals in order to arrive at "safe" level of exposure. Both face the same difficulties in studying low levels of exposure and low risk situations. While toxicologists must face the dangerous business of extrapolation from ani- mals studies to man, the epidemiologist is never certain about exposure levels and the many vari- ables which may have been overlooked. Despite such difficulties a variety of models for data analysis have been proposed and used in toxicolog- ical as well as epidemiological studies (1,2). Assuming for a moment that such models permit us to extrapolate from toxicological data obtained in long-term chronic studies (2) within reason-and it looks that way-the long-term chronic study remains to be done. The question is whether there is any possibility to use short-term tests reliably to predict and evaluate chemicals prior to undertak- ing such studies. During the past 10 years, there has been a great emphasis on such short-term tests but it seems that the emphasis has been more on qualitative than on quantitative predic- tions, and none of them are applicable to inhalation *Department of Industrial Health Sciences, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Penn- sylvania 15261. December 1981 exposure. I would like to present a somewhat different approach which, although empirical, is nonetheless no more so than the extrapolation models so popular now (1). Thirty years ago, the British pharmacologist Frazer (3) had the same concern about chemicals as we have today, primarily with respect to food additives, the main concerns of that time period. The same questions were raised then about long- term toxic effects of chemicals. Reflecting on his experiences, he proposed that some extrapolations could be made from acute studies if one obtained a dose-response relationship for a major biological effect of the chemical in question. Then extrapola- tion could be made from the 50% effect level by taking various ratio of the dose producing this level of effect. Using this scheme, we can propose the relationship given in Table 1. Note that there are not only two variables to consider-dose and response-usually discussed on toxic effects, but a third variable, duration of administration, has been entered. This general approach has been used by many toxicologists in selecting dose level for long-term chronic studies in animals. However, the real question is whether such an approach can be used whereby the same ratio would be used to predict, from the acute studies in animals, what would be a "safe" level for humans. Obviously an "appropriate" animal model must be available whereby the biological effect observed can be qualitatively correlated with a particular effect in man. It is not necessary, however, that 9 Table 1. A proposed approach combining quantity, quality of the effect and duration of administration required of an airborne contaminant. Duration of exposure Quantity Types of effects required or permitted 10 Lethal Minutes 1 Toxic: tissue damage Hours 0.1 Effective: pharmacological reaction Hours-days 0.01 Ineffective: within physiological limits Weeks-years 0.001 Completely safe Years, continuously the effect observed in animal be the same as that in humans, it is only required that one predicts the other. A dose-response curve must be obtained. Since the midpoint will be used for extrapolation it is not necessary to carry on a large number of experi- ments nor are sophisticated statistical approaches required. A least-squares linear regression analy- sis method is all that is needed. A literature search must be conducted for the effect of the chemicals in humans. Obviously epi- demiological studies of human exposed at very low levels must be avoided at first. One must try to find exposure levels within the range tested in the acute animal model and then proceed to the other ranges and longer duration of exposure. Too often we get carried away with prediction of "safe" levels for long-term exposures, and we forget that we have many episodes of short-term exposures which have yielded more reliable data in terms of exposure conditions as well as measurement of the effects. Attempt to Verify the Above Approach For a series of airborne chemicals having sen- sory irritating properties, we attempted to verify how appropriate the approach presented in Table 1 would be. I do not want you to think that a systematic approach can be followed from the beginning. Indeed there were many "best guesses" involved and it took many years to arrive at some useful results. In particular, much discussion was conducted with Dr. Henry F. Smyth, Jr. and his first-hand knowledge and experience in establish- ing Threshold Limit Values (TLVs) for industrial exposure to airborne chemicals was invaluable. Type of Chemicals Selected One basis for establishing a TLV is quite simply to prevent complaints of eye, nose and throat irri- tation in workers, commonly referred to as "sen- 10 sory irritation." Indeed, an evaluation done by H. F. Smyth, Jr. (personal communication) showed that this was the primary basis for the TLV for about 40% of the industrial chemicals for which we have a TLV. His evaluation also showed that at levels three to four times the TLV, 66% of the chemicals listed would elicit sensory irritation. Ob- viously, they can elicit a wide variety of other toxic effects, but it seems that if the exposure level is low enough to prevent sensory irritation these other toxic effects are unlikely to occur. There- fore, a series of these chemicals was tested in an animal model to determine their potency as sen- sory irritant and prediction of human responses developed following the approach given in Table 1. Animal Model and Qualitative Correlation The animal model was devised in 1966 (4). Briefly, its basis is as follows. When airborne chemicals impinge on the nasal mucosa, the trigeminal nerve endings are stimulated, and inhibition of respira- tion occurs. This inhibition occurs in a characteris- tic fashion with the net results being a decrease in respiratory rate. First it was verified that a per- fect correlation existed between this response in animals and the response in humans, i.e., com- plaints of eye, nose and throat irritation (5, 6). Potency of These Chemicals It was found that the decrease in respiratory rate was dependent on the exposure concentration of each chemical. By plotting the percentage de- crease in respiratory rate versus the logarithm of the exposure concentration, a linear relationship was obtained (4-6). Such relationships are summa- rized in Figure 1 for 25 chemicals. From these relationships the exposure concentration necessary to evoke a 50% decrease in respiratory rate was obtained and termed RD50. These values are given in Table 2. Thus the potency of these chemicals can be compared on the basis of their RD50 and Environmental Health Perspectives 70 ETHANOL O TOLUENE S 4 060 DI1SOCYANATE SO? U ~~~~~~~~~~~~~~~~~~NH3 CONCENTRATION - PPM ~ ~ ~ ~ ~ ACEON IA ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ C~ FIGURE 1. Concentration-response relationships obtained for 25 airborne chemicals. Data points are omitted for clarity but can be obtained from Kane (6, 8) with the exception of styrene and amyl acetate. The concentration is given in ppm for all chemicals although in some cases an aerosol form was used. Table 2. RD50 values, 95% confidence intervals, and regression equation for 25 airborne sensory irritants. 95% confidence Regression equation Compound RD50, ppm intervals, ppm y = a + b log x Acetaldehyde 4,946 4,579 - 5,381 -198.34 + 67.22 Acetone 77,517 59,004 - 115,366 -163.46 + 43.66 Acrolein 1.68 1.26 - 2.24 41.16 + 39.44 Ammonia 303 159 - 664 -94.27 + 58.13 Amyl acetate 1,531 1,295 - 1,902 -214.56 + 83.06 n-Butanol 4,784 3,797 - 7,727 -204.81 + 69.25 2-Butoxyethanol 2,824 1,695 - 7,278 -38.88 + 25.76 Chlorine 9.34 6.64 - 14.1 8.00 + 43.30 Chloroacetophenone 0.96 0.766 - 1.26 50.64 + 40.36 Chlorobenzylidene malononitrile 0.52 0.429 - 0.677 70.70 + 73.81 Chloropicrin 7.98 6.22 - 10.6 9.54 + 44.87 Epichlorohydrin 687 633 - 748 -108.58 + 55.90 Ethanol 27,314 24,154-32,605 -401.71 + 101.82 Ethyl acetate 614 562 - 684 -268.99 + 114.41 Formaldehyde 3.13 2.54 - 3.97 28.21 + 43.91 Hydrogen chloride 309 281 - 410 -59.40 + 43.95 Isopentanol 41,514 32,939- 58,633 -207.16 + 55.68 Isopropanol 4,452 2,885 - 12,459 -109.95 + 43.84 Methanol 4,039 3,113 - 6,033 -99.20 + 41.37 n-Pentanol 17,693 15,509-20,511 -201.30 + 59.16 n-Propanol 12,704 11,558- 14,152 -219.67 + 65.71 Propionaldehyde 2,751 2,294 - 4,009 -228.16 + 80.87 Styrene 980 826 - 1,297 -219.88 + 90.22 Sulfur dioxide 117 107 - 128 -47.06 + 46.95 Toluene diisocyanate 0.39 0.345 - 0.446 73.82 + 58.01 11 December 1981 predictions made from this value. This is true if the curves are parallel or various corrections can be used. Inspection of Figure 1 (and the regression equations yielding the value for the slopes) reveals that the main exceptions are ethyl acetate, 2-but- oxyethanol and ethanol. However, no correction will be made here; we will simply accept the RD50 values and proceed from there. Prediction of Level of Response in Humans Following the approach in Table 1, levels and types of effects expected to occur in humans at various RD50 ratios are presented in Table 3. To verify how close these predictions were, an exten- sive literature search was conducted for the first eleven chemicals tested (6, 7); in general, a good correlation was found. Also for 19 of the 23 chemi- cals listed in Table 1 for which TLVs have been established, correct predictions were made for the range 0.01 to 0.1 RD50 as being where the value for the TLV should be (6, 8). For one of the chemi- cals tested, sulfur dioxide, the highest level per- mitted for an Air Quality Standard was 0.1 ppm according to the model. The current Air Quality Standard is 0.03 ppm on the basis of annual aver- age and 0.14 ppm for a 24-hr period. Perhaps a better way of looking at the data is to take a particular fraction of RD50, a single value, instead of predicting an acceptable range. To do this, a convenient value would be 0.03 RD50, the midpoint on a logarithmic scale, between the range 0.01 and 0.1 RD50. These values are also listed. Taking the logarithm of both values and performing a regression analysis yields the results in Figure 2. If we believe the model to be correct, the TLV for formaldehyde and ethyl acetate should be reduced. However, what is rather remarkable is that the model seems to be working over five orders of magnitude of potency for the wide variety of chemi- cals tested. Table 3. Predictions of level and type of responses in humans at various multiples of RD5, value found in mice. Multiples of RD50 Response 10 Severe injury, possibly lethal 1 Intolerable to humans 0.1 Some sensory irritation 0.01 No sensory irritation 0.001 No effect of any kind on respiratory system Table 4. RD50, Current TLV-TWA and Predicted Acceptable TLV-TWA on the Basis of 0.03 RD5, RD50, 1978 0.03 RD50, log 1978 log 0.03 Chemical ppm TLV-TWA, ppm ppm TLV-TWA, ppm RD50, ppm Toluene diisocyanate 0.2 0.02 0.006 -1.70 -2.22 Chlorobenzylidene malononitrile 0.52 0.05 0.016 -1.30 -1.80 Chloroacetophenone 0.96 0.05 0.03 -1.30 -1.52 Acrolein 1.68 0.1 0.05 -1.00 -1.30 Formaldehyde 3.13 2.0 0.10 0.30 -1.0 Chloropicrin 7.98 0.1 0.25 -1.0 -0.602 Chlorine 9.34 1 0.30 0 -0.523 Sulfur dioxide 117 5 3.8 0.69 0.58 Ammonia 303 25 30 1.4 1.48 Hydrogen chloride 309 5 9.6 0.69 Ethyl acetate 614 400 19.0 2.6 1.28 Epichlorohydrin 687 5 22 0.69 1.34 Styrene 980 100 31 2.0 1.49 Amyl acetate 1,531 100 48 2.0 1.68 Propionaldehyde 2,751 - 88 - - 2-Butoxyethanol 2,825 50 89 1.7 1.95 n-Pentanol 4,039 - 129 - - Isopentanol 4,452 100 142 2.0 2.15 n-Butanol 4,784 50 152 1.7 2.18 Acetaldehyde 4,946 100 151 2.0 2.2 n-Propanol 12,704 200 402 2.3 2.6 Isopropanol 17,693 400 559 2.6 2.75 Ethanol 27,314 1000 864 3.0 2.94 Methanol 41,514 200 1,312 2.3 3.12 Acetone 77,516 1000 2,451 3.0 3.39 Environmental Health Perspectives 12 4 Acetone E - Ethanol- a03 Methanol 0 - Isoproponol- < _ Ethyl Acetate-0n9 31. ~~~~~~~~n-Propanol 2- Isopenta nol ~ cetaldehyde co2 - Styrene ) r-~ ~ ~ ~ ~~trn ~'n-Butanol 0) ~~~~Amyl Acetate 2-Butoxyethanol - Sulfur Dioxide Ammonia E Formaldehyde \\- Epichlorohydrin * 0 - Chlorine -O Hydrogen Chloride 0 -Acrolein Chlorocetophenone -Ik-c 0- Chloropicrin h lorobenzylidene Malononitrile Toluene Diisocyanate -2F ... - . ... , .... I I I ,, I I . I a.. I I,,, I I ... -3 -2 -I 0 1 2 3 4 Logarithm of Proposed TWAs from Animal Model (ppm) FIGURE 2. Regression analysis for 23 airborne chemicals ob- tained by plotting 0.03 RD50 as the proposed TLV-TWA versus the TLV-TWA for each chemical from the data given in Table 4. Regression equation, y(x) = 0.24 + 83x, r = 0.95. Conclusions In the case of these airborne contaminants it appears that the "appropriate" model has been selected and that "reasonable" predictions can be made for effects in humans over a wide range of concentrations and duration of exposure. Thus, this short-term test can be used to rapidly evaluate new as well as old chemicals never tested before to obtain their potency and make comparisons with the chemicals already tested. From these results, we can get a reasonable estimate of the level of control likely to be needed for industrial produc- tion and the cost for such controls. It is, at least, a starting point. The results can also be used for planning repeated exposures (9) to verify the ap- propriateness of the predictions and make neces- sary corrections prior to long term chronic studies. The main problem in toxicology does not seem to me to be related to dose-response analysis but rather to be related to the appropriateness of the models we use. Perhaps the new generation of toxicologists will concern themselves more with resolving this issue. Written under support from Grant OH-00367 from the Na- tional Institute of Occupational Safety and Health. REFERENCES 1. Hunter, W. G., and Crowley, J. J. Hazardous substances, the environment and public health: a statistical overview. Environ. Health Perspect. 32: 241-254 (1979). 2. Gehring, P. J., Watanabe, P. G., and Park, C. N. Risk of angiosarcoma in workers exposed to vinyl chloride as predicted from studies in rats. Toxicol. Appl. Pharmacol. 49: 15-21 (1979). 3. Frazer, A. Pharmacological aspects of chemicals in food. Endeavour 12: 43-47 (1953). 4. Alarie, Y. Irritating properties of airborne materials to the upper respiratory tract. Arch. Environ. Health 13: 433-449 (1966). 5. Alarie, Y. Sensory irritation by airborne chemicals. CRC Crit. Rev. Toxicol. 2: 299-363 (1973). 6. Kane, L. E., Barrow, C. S., and Alarie, Y. A short-term test to predict acceptable levels of exposure to airborne sensory irritants. Amer. Ind. Hyg. Assoc. J. 40: 207-229 (1979). 7. Alarie, Y., Kane, L., and Barrow, C. S. Sensory irritation: a basis to establish acceptable exposure to airborne chemical irritants. In: Principles and Practice of Industrial Toxicolo- gy, A. Reeves and H. N. MacFarland, Eds., Wiley, New York, in press. 8. Kane, L. E., Dombroske, R., and Alarie, Y. Evaluation of sensory irritation from some common industrial solvents. Amer. Ind. Hyg. Assoc. J. 41: 451-455 (1980). 9. Sangha, G. K., and Alarie, Y. Sensory irritation by toluene diisocyanate in single and repeated exposures. Toxicol. Appl. Pharmacol. 50: 533-547 (1979). December 1981 13