Page 2 of 18

II. BACKGROUND

In 2005, a revised HED human health risk assessment for formetanate HCl was issued. The 

dose and endpoint for acute dietary (general population) exposure scenarios were based on 

female pup ChE inhibition observed in a comparative ChE study in rats (MRID 46618901). 

However, a re-evaluation of the ChE assay methodologies and ChE data in November 2008

concluded that the study was Unacceptable/Non-Guideline for risk assessment purposes 

(D356185; TXR 0055042). The re-evaluation noted a significant number of assay errors in the 

measurement of ChE activity which likely resulted in the underestimation of the true ChE 

inhibition. Furthermore, the difficulty in consistently and accurately measuring ChE activity 

likely resulted in the poor dose-response in both sexes of both pups and adults that was reported 

in the original DER of this study (D320464, TXR 0053305). 

In 2009, post-natal day 17 (PND17) rat pup ChE data became available from the EPA Office of 

Research Development (MRID 47692902). This study examined both brain and red blood cell 

(RBC) ChE in male PND17 rat (Long Evans) pups (female pups not examined) 40 minutes after 

a single dose of 0, 0.1, 0.3, 0.75, or 1.5 mg/kg/day. An analysis of these data was performed 

with an exponential benchmark dose (BMD) modeling program written in R language, and the 

acute dietary point of departure (PoD) for formetanate was re-evaluated on the basis of the 2009 

BMD results (D364562, TXR00555179). A 10x FQPA safety factor, however, was retained 

based on the lack of acceptable PND11 ChE data for the acute dietary risk assessment. This 

FQPA factor was consistent with other N-methyl carbamates without acceptable PND11 ChE 

data.

In 2010, Gown submitted to the Agency a new formetanate CCA study (MRID 48298401) that 

was conducted at Charles River Laboratories, the same laboratory which performed the 2005

formetanate CCA study. The new CCA study was reviewed by HED and the male PND11 ChE 

data (both RBC and brain) were considered unacceptable for use in risk assessment (D383678, 

TXR0055523). As in the 2005 CCA study, there were numerous assay errors that likely resulted 

in the underestimation of the true brain and RBC ChE activity in the PND11 male pups. The 

ChE data from the PND11 female pups and male and female adults, however, are considered 

acceptable since the same level of assay errors were not present in these groups. Since both ChE 

compartments are now available for formetanate in PND11 female pups, a new PoD was

determined along with an appropriate FQPA safety factor to be consistent with the other Nmethyl carbamates. The discussion below provides details regarding the weight-of-evidence 

(WOE) development of both the PoD as well as the FQPA safety factor for formetanate based on 

the results of the acceptable PND11 and PND17 ChE data.

III. RESULTS/DISCUSSION

Benchmark Dose Analysis

Detailed results of the new BMD analysis (outputs) based on the 2010 formetanate CCA study 

(MRID 48298401) are included in Appendix 1. A summary of the BMD estimates for all ChE 

data with formetanate is presented in Table 1 below.
Page 3 of 18

Table 1. BMD1 Results for PND11 and PND17 Rats to Formetanate

AGE SEX Compartment BMD10

mg/kg

BMDL10

mg/kg

Timepoint 

(min) MRID

PND11 Male Brain & RBC NA2 NA NA 48298401

PND11 Female

(BMDS) 2 Brain 0.041 0.032 30 48298401

PND11 Female

(BMDS) 2 RBC 0.067 0.034 30 48298401

PND17 Male

(BMDS) 2 Brain 0.059 0.051 40 47692902

PND17 Male 

(BMDS) 2 RBC 0.047 0.037 40 47692902

1 2010 Benchmark dose analysis using the current BMDS exponential model. D381401, TXR0055532

2

 NA: Data not available/ not acceptable

PND11 ChE Results

The RBC and brain ChE data from the male PND11 pups from the new CCA study are

unacceptable due to numerous assay errors that resulted in the underestimation of the true 

inhibition of the enzyme. The female PND11 ChE data, however, were considered acceptable 

for use in risk assessment (D383678, TXR0055523, final pending). The ChE compartments in 

the PND11 females are 1.6x different with the brain BMD10 of 0.041 mg/kg and RBC BMD10 of 

0.067 mg/kg. The difference in brain and RBC BMDL10 estimates are 1.1x with the brain 

BMDL10 of 0.032 mg/kg and RBC BMDL10 of 0.034 mg/kg. 

A comparison of the PND11 ChE data with the PND17 ChE data required the reanalysis of the 

PND17 data. The previous BMD analysis of the PND17 data (2009) was performed with an 

exponential BMD modeling program written in R language, which was the only available model 

at the time (D381408, TXR0055532). To compare the PND17 with the new PND11 ChE data

(2010) which were analyzed with the BMDS software, the PND17 ChE data were also analyzed

with the BMDS software. The BMDS exponential model includes a family of nested models that 

provides improved model fitting for all kinds of datasets. Because of the flexibility and 

advantages of the EPA BMDS exponential models, the formetanate data were reanalyzed with 

this software. The BMDS exponential model resulted in significantly higher BMD10 and 

BMDL10 estimates for both PND17 RBC and brain ChE. The 2010 BMDS analysis suggests that 

PND17 brain and RBC are similar in ChE sensitivity with only a 1.2 fold difference between the 

BMD10 estimates. Furthermore, the BMD10 estimates displayed in Table 1 suggest that the 

PND11 brain ChE data (BMD10 0.041 mg/kg) are 1.4x more sensitive than the PND17 brain ChE

(BMD10 0.059 mg/kg). For RBC ChE, the PND11 BMDL10 (0.034 mg/kg) estimate is similar to 

the PND17 BMDL10 (0.037 mg/kg) estimate. 
Page 4 of 18

IV. Endpoint and Point of Departure (PoD) Weight of Evidence (WOE)

A weight of evidence determination was performed for all of the ChE data available for 

formetanate. The BMD10 estimates for RBC and brain ChE from PND11 females from the recent 

CCA study (MRID 48298401) suggest no significant differences in compartment sensitivity but 

brain slightly more sensitive (i.e., lower). The BMDL10 estimates are also similar but with brain 

ChE again slightly more sensitive. Therefore, the brain BMDL10 of 0.032 mg/kg from the 

PND11 female pups is the most appropriate for use as the PoD in the acute dietary risk 

assessment. This PoD is protective and consistent with PoDs established for other NMCs. Since 

the slightly more sensitive compartment (i.e., brain ChE) from the most sensitive subpopulation 

(PND11) is the basis of the PoD, an FQPA factor should not be retained. Furthermore, there are 

no sex differences in the adult formetanate data or for the other NMCs to suggest the PND11 

females would be less sensitive than PND11 males to formetanate. Therefore, the acute dietary 

aPAD of 0.00032 mg/kg is based on a PoD of 0.032 mg/kg (PND11 female brain BMDL10), per 

a 1x FQPA safety factor, 10x intraspecies factor, and 10x interspecies factor.

Table 2. Acute Dietary Endpoints for Formetanate Human Health Risk Assessment

Exposure/Scenario Point of Departure Uncertainty/FQPA 

Factor

RfD, PAD, Level of 

Concern for risk 

assessment

Study and 

Toxicological 

Effects

Acute Dietary 

(general population, 

including infants and 

children)

BMDL10 = 0.032 

mg/kg

UFA= 10x

UFH= 10x

FQPA = 1x

aRfD = 0.00032 

mg/kg/day

aPAD= 0.00032 

mg/kg/day

Comparative 

Cholinesterase Study 

(MRID 48298401)

Acceptable RBC and 

brain ChE data in 

PND11 female pups

Brain BMD10: 

0.041mg/kg

Brain BMDL10: 

0.032 mg/kg

V. CONCLUSIONS 

The single chemical assessments for the recently updated NMCs have consistently evaluated 

compartment sensitivity, especially in PND11 pups. Formetanate was therefore evaluated in a 

consistent fashion to the other NMCs. Reliable RBC and brain ChE data are available in PND11 

females for formetanate. The PoD of 0.032 mg/kg for the acute dietary assessment is based on 

the brain ChE BMDL10 in PND11 female pups. Since the PoD is based upon the most sensitive 

subpopulation and the most sensitive ChE compartment, retention of the FQPA factor is not 

warranted. The aPAD of 0.00032 mg/kg is based on the PoD of 0.032 mg/kg, with a 1x FQPA, 

10x intraspecies factor, and 10x interspecies factor. 
Page 5 of 18

APPENDIX 1

RBC PND11-female
Page 6 of 18

formetanate

new 

CCA ACUTE NONGUIDELINE PND11 RBC F 30 min

High dose dropped

Exponential

Model var

10 bmr

==================================================================== 

 Exponential Model. (Version: 1.7; Date: 12/10/2009) 

 Input Data File: C:/Usepa/BMDS212/Data/exp_Testrunscontinuous_Setting.(d) 

 Gnuplot Plotting File: 

Tue Nov 16 09:01:34 2010

==================================================================== 

BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

 The form of the response function by Model: 

 Model 2: Y[dose] = a * exp{sign * b * dose}

 Model 3: Y[dose] = a * exp{sign * (b * dose)^d}

 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}]

 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}]

 Note: Y[dose] is the median response for exposure = dose;

 sign = +1 for increasing trend in data;

 sign = -1 for decreasing trend.

 Model 2 is nested within Models 3 and 4.

 Model 3 is nested within Model 5.

 Model 4 is nested within Model 5.

 Dependent variable = Mean

 Independent variable = Dose

 Data are assumed to be distributed: normally

 Variance Model: exp(lnalpha +rho *ln(Y[dose]))

 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho)

 Total number of dose groups = 4

 Total number of records with missing values = 0

 Maximum number of iterations = 250

 Relative Function Convergence has been set to: 1e-008

 Parameter Convergence has been set to: 1e-008

 MLE solution provided: Exact

 Initial Parameter Values

 Variable Model 2 Model 3 Model 4 Model 5

 -------- ------- ------- ------- -------

 lnalpha -4.20227 -4.20227 -4.20227 -4.20227

 rho 3.0041 3.0041 3.0041 3.0041

 a 0.996322 1.1328 2.2449 2.2449

 b 2.90384 1.82258 2.99935 2.99935
Page 7 of 18

 c -- -- 0.000334982 

0.000334982

 d -- 3 -- 1

 Parameter Estimates by Model

 Variable Model 2 Model 3 Model 4 Model 5

 -------- ------- ------- ------- -------

 lnalpha -4.26902 -4.34669 -4.26902 -4.34669

 rho 3.04507 3.06327 3.04507 3.06327

 a 2.22012 2.06288 2.22012 2.06288

 b 2.97577 2.79384 2.97577 2.79384

 c -- -- 0 2.19711e-024

 d -- 1.34119 -- 1.34119

 Table of Stats From Input Data

 Dose N Obs Mean Obs Std Dev

 ----- --- ---------- -------------

 0 5 2.138 0.386

 0.04 8 1.874 0.345

 0.12 8 1.67 0.235

 0.36 7 0.752 0.081

 Estimated Values of Interest

 Model Dose Est Mean Est Std Scaled Residual

 ------- ------ ---------- --------- ----------------

 2 0 2.22 0.3984 -0.4609

 0.04 1.971 0.3324 -0.8252

0.12 1.553 0.2313 1.425

0.36 0.7605 0.07798 -0.2901

 3 0 2.063 0.345 0.4869

 0.04 1.957 0.3181 -0.7341

0.12 1.638 0.2422 0.3792

0.36 0.753 0.0737 -0.03665

 4 0 2.22 0.3984 -0.4609

 0.04 1.971 0.3324 -0.8252

0.12 1.553 0.2313 1.425

0.36 0.7605 0.07798 -0.2901

 5 0 2.063 0.345 0.4869

 0.04 1.957 0.3181 -0.7341

 0.12 1.638 0.2422 0.3792

 0.36 0.753 0.0737 -0.03665

 Other models for which likelihoods are calculated:

 Model A1: Yij = Mu(i) + e(ij)

 Var{e(ij)} = Sigma^2

 Model A2: Yij = Mu(i) + e(ij)

 Var{e(ij)} = Sigma(i)^2

 Model A3: Yij = Mu(i) + e(ij)

 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho)

 Model R: Yij = Mu + e(i)
Page 8 of 18

 Var{e(ij)} = Sigma^2

 Likelihoods of Interest

 Model Log(likelihood) DF AIC

 ------- ----------------- ---- ------------

 A1 23.99972 5 -37.99945

 A2 30.61741 8 -45.23483

A3 30.45202 6 -48.90404

 R 1.940927 2 0.118145

2 28.98214 4 -49.96429

 3 30.08243 5 -50.16485

4 28.98214 4 -49.96429

5 30.08243 6 -48.16485

 Additive constant for all log-likelihoods = -25.73. This constant added to the

 above values gives the log-likelihood including the term that does not

 depend on the model parameters.

 Explanation of Tests

 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R)

 Test 2: Are Variances Homogeneous? (A2 vs. A1)

 Test 3: Are variances adequately modeled? (A2 vs. A3)

 Test 4: Does Model 2 fit the data? (A3 vs. 2)

 Test 5a: Does Model 3 fit the data? (A3 vs 3)

 Test 5b: Is Model 3 better than Model 2? (3 vs. 2)

 Test 6a: Does Model 4 fit the data? (A3 vs 4)

 Test 6b: Is Model 4 better than Model 2? (4 vs. 2)

 Test 7a: Does Model 5 fit the data? (A3 vs 5)

 Test 7b: Is Model 5 better than Model 3? (5 vs. 3)

 Test 7c: Is Model 5 better than Model 4? (5 vs. 4)

 Tests of Interest

 Test -2*log(Likelihood Ratio) D. F. p-value

 -------- ------------------------ ------ --------------

 Test 1 57.35 6 < 0.0001

 Test 2 13.24 3 0.004154

 Test 3 0.3308 2 0.8476

 Test 4 2.94 2 0.23

 Test 5a 0.7392 1 0.3899

 Test 5b 2.201 1 0.138

 Test 6a 2.94 2 0.23

 Test 6b 0 0 N/A

 Test 7a 0.7392 0 N/A

 Test 7b -7.105e-015 1 N/A

 Test 7c 2.201 2 0.3328

 The p-value for Test 1 is less than .05. There appears to be a

 difference between response and/or variances among the dose

 levels, it seems appropriate to model the data.

 The p-value for Test 2 is less than .1. A non-homogeneous

 variance model appears to be appropriate.
Page 9 of 18

 The p-value for Test 3 is greater than .1. The modeled

 variance appears to be appropriate here.

 The p-value for Test 4 is greater than .1. Model 2 seems

 to adequately describe the data.

 The p-value for Test 5a is greater than .1. Model 3 seems

 to adequately describe the data.

 The p-value for Test 5b is greater than .05. Model 3 does

 not seem to fit the data better than Model 2.

 The p-value for Test 6a is greater than .1. Model 4 seems

 to adequately describe the data.

 Degrees of freedom for Test 6b are less than or equal to 0.

 The Chi-Square test for fit is not valid.

 Degrees of freedom for Test 7a are less than or equal to 0.

 The Chi-Square test for fit is not valid.

 The p-value for Test 7b is less than .05. Model 5 appears

 to fit the data better than Model 3.

 The p-value for Test 7c is greater than .05. Model 5 does

 not seem to fit the data better than Model 4.

 Benchmark Dose Computations:

 Specified Effect = 0.100000

 Risk Type = Relative deviation

 Confidence Level = 0.950000

 BMD and BMDL by Model

 Model BMD BMDL

 ------- ------------ ----------

 2 0.0354061 0.0322295

 3 0.0668501 0.0339757

 4 0.0354061 0.029042

 5 0.0668501 0.0339757
Page 10 of 18

 0.5

 1

 1.5

 2

 2.5

 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

Mean Response

dose

Exponential Model 2 with 0.95 Confidence Level

09:01 11/16 2010

BMDL BMD

 

Exponential

 0.5

 1

 1.5

 2

 2.5

 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

Mean Response

dose

Exponential Model 3 with 0.95 Confidence Level

09:01 11/16 2010

BMDL BMD

 

Exponential
Page 11 of 18

 0.5

 1

 1.5

 2

 2.5

 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

Mean Response

dose

Exponential Model 4 with 0.95 Confidence Level

09:01 11/16 2010

BMDL BMD

 

Exponential

 0.5

 1

 1.5

 2

 2.5

 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

Mean Response

dose

Exponential Model 5 with 0.95 Confidence Level

09:01 11/16 2010

BMDL BMD

 

Exponential
Page 12 of 18

APPENDIX 2

brain PND11-female
Page 13 of 18

formetanate

new 

CCA ACUTE NONGUIDELINE PND11 BRAIN F 30 min

Exponential 

Constant var

10 bmr 

==================================================================== 

 Exponential Model. (Version: 1.7; Date: 12/10/2009) 

 Input Data File: C:/Usepa/BMDS212/Data/exp_Testrunscontinuous_Setting.(d) 

 Gnuplot Plotting File: 

Tue Nov 16 09:12:53 2010

==================================================================== 

BMDS Model Run 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

 The form of the response function by Model: 

 Model 2: Y[dose] = a * exp{sign * b * dose}

 Model 3: Y[dose] = a * exp{sign * (b * dose)^d}

 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}]

 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}]

 Note: Y[dose] is the median response for exposure = dose;

 sign = +1 for increasing trend in data;

 sign = -1 for decreasing trend.

 Model 2 is nested within Models 3 and 4.

 Model 3 is nested within Model 5.

 Model 4 is nested within Model 5.

 Dependent variable = Mean

 Independent variable = Dose

 Data are assumed to be distributed: normally

 Variance Model: exp(lnalpha +rho *ln(Y[dose]))

 rho is set to 0.

 A constant variance model is fit.

 Total number of dose groups = 5

 Total number of records with missing values = 0

 Maximum number of iterations = 250

 Relative Function Convergence has been set to: 1e-008

 Parameter Convergence has been set to: 1e-008

 MLE solution provided: Exact

 Initial Parameter Values

 Variable Model 2 Model 3 Model 4 Model 5

 -------- ------- ------- ------- -------

 lnalpha -1.21046 -1.21046 -1.21046 -1.21046
Page 14 of 18

 rho(S) 0 0 0 0

 a 2.40207 2.40207 5.58705 5.58705

 b 1.25126 1.25126 4.03036 4.03036

 c -- -- 0.256887 

0.256887

 d -- 1 -- 1

 (S) = Specified

 Parameter Estimates by Model

 Variable Model 2 Model 3 Model 4 Model 5

 -------- ------- ------- ------- -------

 lnalpha -0.949194 -0.949193 -1.20882 -1.20921

 rho 0 0 0 0

 a 5.10881 5.10881 5.34674 5.33365

 b 1.67587 1.67587 3.5434 3.58703

 c -- -- 0.260103 0.265245

 d -- 1 -- 1.02562

 Table of Stats From Input Data

 Dose N Obs Mean Obs Std Dev

 ----- --- ---------- -------------

 0 7 5.321 0.48

 0.04 8 4.862 0.529

 0.12 8 3.961 0.765

 0.36 8 2.494 0.672

 1 6 1.507 0.293

 Estimated Values of Interest

 Model Dose Est Mean Est Std Scaled Residual

 ------- ------ ---------- --------- ----------------

 2 0 5.109 0.6221 0.9024

 0.04 4.778 0.6221 0.3838

0.12 4.178 0.6221 -0.9871

0.36 2.795 0.6221 -1.366

 1 0.9561 0.6221 2.169

 3 0 5.109 0.6221 0.9024

 0.04 4.778 0.6221 0.3838

0.12 4.178 0.6221 -0.9871

0.36 2.795 0.6221 -1.366

 1 0.9561 0.6221 2.169

 4 0 5.347 0.5464 -0.1246

 0.04 4.824 0.5464 0.197

0.12 3.977 0.5464 -0.08025

 0.36 2.495 0.5464 -0.007527

 1 1.505 0.5464 0.008554

 5 0 5.334 0.5463 -0.06125

 0.04 4.834 0.5463 0.1473

0.12 3.986 0.5463 -0.1317

0.36 2.483 0.5463 0.05721

 1 1.511 0.5463 -0.01793

 Other models for which likelihoods are calculated:
Page 15 of 18

 Model A1: Yij = Mu(i) + e(ij)

 Var{e(ij)} = Sigma^2

 Model A2: Yij = Mu(i) + e(ij)

 Var{e(ij)} = Sigma(i)^2

 Model A3: Yij = Mu(i) + e(ij)

 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho)

 Model R: Yij = Mu + e(i)

 Var{e(ij)} = Sigma^2

 Likelihoods of Interest

 Model Log(likelihood) DF AIC

 ------- ----------------- ---- ------------

 A1 3.893561 6 4.212879

A2 7.109295 10 5.78141

A3 3.893561 6 4.212879

 R -33.05449 2 70.10897

2 -0.939906 3 7.879812

3 -0.939906 3 7.879812

4 3.863087 4 0.2738264

5 3.870359 5 2.259282

 Additive constant for all log-likelihoods = -34. This constant added to the

 above values gives the log-likelihood including the term that does not

 depend on the model parameters.

 Explanation of Tests

 Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R)

 Test 2: Are Variances Homogeneous? (A2 vs. A1)

 Test 3: Are variances adequately modeled? (A2 vs. A3)

 Test 4: Does Model 2 fit the data? (A3 vs. 2)

 Test 5a: Does Model 3 fit the data? (A3 vs 3)

 Test 5b: Is Model 3 better than Model 2? (3 vs. 2)

 Test 6a: Does Model 4 fit the data? (A3 vs 4)

 Test 6b: Is Model 4 better than Model 2? (4 vs. 2)

 Test 7a: Does Model 5 fit the data? (A3 vs 5)

 Test 7b: Is Model 5 better than Model 3? (5 vs. 3)

 Test 7c: Is Model 5 better than Model 4? (5 vs. 4)

 Tests of Interest

 Test -2*log(Likelihood Ratio) D. F. p-value

 -------- ------------------------ ------ --------------

 Test 1 80.33 8 < 0.0001

 Test 2 6.431 4 0.1692

 Test 3 6.431 4 0.1692

 Test 4 9.667 3 0.02162

 Test 5a 9.667 3 0.02162

 Test 5b -3.058e-011 0 N/A

 Test 6a 0.06095 2 0.97

 Test 6b 9.606 1 0.001939

 Test 7a 0.0464 1 0.8294
Page 16 of 18

 Test 7b 9.621 2 0.008146

 Test 7c 0.01454 1 0.904

 The p-value for Test 1 is less than .05. There appears to be a

 difference between response and/or variances among the dose

 levels, it seems appropriate to model the data.

 The p-value for Test 2 is greater than .1. A homogeneous

 variance model appears to be appropriate here.

 The p-value for Test 3 is greater than .1. The modeled

 variance appears to be appropriate here.

 The p-value for Test 4 is less than .1. Model 2 may not adequately

 describe the data; you may want to consider another model.

 The p-value for Test 5a is less than .1. Model 3 may not adequately

 describe the data; you may want to consider another model.

 Degrees of freedom for Test 5b are less than or equal to 0.

 The Chi-Square test for fit is not valid.

 The p-value for Test 6a is greater than .1. Model 4 seems

 to adequately describe the data.

 The p-value for Test 6b is less than .05. Model 4 appears

 to fit the data better than Model 2.

 The p-value for Test 7a is greater than .1. Model 5 seems

 to adequately describe the data.

 The p-value for Test 7b is less than .05. Model 5 appears

 to fit the data better than Model 3.

 The p-value for Test 7c is greater than .05. Model 5 does

 not seem to fit the data better than Model 4.

 Benchmark Dose Computations:

 Specified Effect = 0.100000

 Risk Type = Relative deviation

 Confidence Level = 0.950000

 BMD and BMDL by Model

 Model BMD BMDL

 ------- ------------ ----------

 2 0.0628692 0.0512403

 3 0.0628692 0.0512403

 4 0.0409787 0.0317504

 5 0.0427913 0.0317731
Page 17 of 18

 1

 2

 3

 4

 5

 6

 0 0.2 0.4 0.6 0.8 1 Mean Response

dose

Exponential Model 2 with 0.95 Confidence Level

09:12 11/16 2010

BMDL BMD

 

Exponential

 1

 2

 3

 4

 5

 6

 0 0.2 0.4 0.6 0.8 1 Mean Response

dose

Exponential Model 3 with 0.95 Confidence Level

09:12 11/16 2010

BMDL BMD

 

Exponential
Page 18 of 18

 1

 2

 3

 4

 5

 6

 0 0.2 0.4 0.6 0.8 1 Mean Response

dose

Exponential Model 4 with 0.95 Confidence Level

09:12 11/16 2010

BMDL BMD

 

Exponential

 1

 2

 3

 4

 5

 6

 0 0.2 0.4 0.6 0.8 1 Mean Response

dose

Exponential Model 5 with 0.95 Confidence Level

09:12 11/16 2010

BMDL BMD

 

Exponential