UNITED STATES ENVIRONMENTAL PROTECTION AGENCY

 WASHINGTON D.C. 20460 

 

OFFICE OF THE ADMINISTRATOR 

 SCIENCE ADVISORY BOARD 

December 19, 2008 

EPA-SAB-09-009 

The Honorable Stephen L. Johnson 

Administrator 

U.S. Environmental Protection Agency 

1200 Pennsylvania Avenue, N.W. 

Washington, DC 20460 

Subject: Review of EPA’s draft entitled “Toxicological Review of Acrylamide” 

Dear Administrator Johnson: 

In response to a request from EPA’s Office of Research and Development (ORD), the 

Science Advisory Board (SAB) convened an expert panel to conduct a peer review of EPA's 

draft Integrated Risk Information System (IRIS) assessment entitled, “Toxicologic Review of 

Acrylamide” (December 2007). This draft document updates EPA’s current evaluation of the 

potential health effects of acrylamide. 

 

 The SAB was asked to comment on the hazard characterization and dose-response 

assessment of acrylamide, including the Agency’s selection of the most sensitive non-cancer 

health endpoint, the use of a physiologically-based toxicokinetic (PBTK) model, the derivation 

of a proposed oral reference dose (RfD), an inhalation reference concentration (RfC) for noncancer endpoints, as well as the cancer descriptor, oral slope factor, and inhalation unit risk for 

acrylamide. The SAB Panel’s report contains a number of recommendations that are aimed at 

making the assessment more transparent and improving the scientific bases for the conclusions 

presented. While a more detailed description of the technical recommendations is contained in 

the body of the report, the key points and recommendations are highlighted below: 

• The Panel agreed with the EPA’s conclusion that based on the existing toxicity data base for 

acrylamide, neurotoxicity appears to be the most sensitive non-cancer endpoint, and 

therefore, the most appropriate for developing the RfD and RfC for non-cancer health effects. 

The Panel was concerned, however, that the RfD/RfC was derived from studies which were 

primarily designed as cancer bioassays and therefore did not include the most sensitive 

measures of neurotoxicity. 

• The Panel believed that the use of the benchmark dose methodology in this assessment was 

scientifically supportable, given the nature and robustness of the data sets available on the 

endpoint of concern. 
• The Panel supported the Agency’s conclusions that exposure to acrylamide in animals leads 

to heritable gene mutations and that these results indicate that it may also pose a hazard to 

humans. The Panel further supported the Agency’s conclusions that the available data on 

heritable gene mutations are not adequate to conduct a robust assessment of this endpoint at 

this time. The Panel urges further research on acrylamide-induced heritable germ cell 

mutations, given the serious nature of such effects. 

• The Panel concluded that the rationale and justification for acrylamide being a “likely human 

carcinogen” via a mutagenic mechanism was well described and the conclusion was 

scientifically supportable, although it should be further elaborated. While the Panel did 

consider available information regarding non-mutagenic MOAs (e.g., hormonal) as presented 

by public commenters, they did not find it to be compelling. 

• The Panel encouraged the Agency to use the two main chronic bioassays in rats for deriving 

the oral cancer slope factor and include an in depth discussion of the strengths and limitations 

of both studies. 

• The Panel commends EPA for using the PBTK model for developing the RfD, RfC and 

cancer slope factor for acrylamide. The Panel did however provide some recommendations 

to the Agency for improving the model as they revise their draft document. The Panel notes 

that the use of internal dose metrics combined with a fairly robust understanding of the 

mechanism of action may replace the use of the default interspecies factor for toxicokinetic 

differences. Internal dose may be derived using the PBTK model or through application of 

other pharmacokinetic approaches indicated in the Panel report. 

• The Panel agreed with the use of PBTK modeling to conduct dose-route extrapolation and 

commended the EPA for using the PBTK model to fill the gap created due to the absence of 

robust animal toxicology studies that would support the development of an RfC. In 

estimating the cancer slope factor and unit risk, human-rodent differences in toxicokinetics 

were taken into account with the PBTK model, whereas toxicodynamic differences were not, 

but should be, through the application of a standard factor. 

• Finally, the Panel agreed that the use of the age-dependent adjustment factors to adjust the 

unit risk for early life exposure is well justified and transparently and objectively described. 

 The SAB appreciates the opportunity to provide EPA with advice on this important 

subject. Although cognizant of additional acrylamide studies currently underway, the SAB urges 

EPA to move expeditiously to finalize the IRIS document on acrylamide as the Agency considers 

relevant data which has been published since the release of the draft assessment. We look 

forward to receiving the Agency’s response. 

Sincerely, 

/Signed/ /Signed/ 

Dr. Deborah L. Swackhamer, Chair Dr. Deborah Cory-Slechta, Chair 

EPA Science Advisory Board SAB Acrylamide Review Panel 
NOTICE 

This report has been written as part of the activities of the EPA Science Advisory Board, 

a public advisory committee providing extramural scientific information and advice to the 

Administrator and other officials of the Environmental Protection Agency. The Board is 

structured to provide balanced, expert assessment of scientific matters related to problems facing 

the Agency. This report has not been reviewed for approval by the Agency and, hence, the 

contents of this report do not necessarily represent the views and policies of the Environmental 

Protection Agency, nor of other agencies in the Executive Branch of the Federal government, nor 

does mention of trade names or commercial products constitute a recommendation for use. 

Reports of the EPA Science Advisory Board are posted on the EPA Web site at: 

http://www.epa.gov/sab. 
U.S. Environmental Protection Agency 

Science Advisory Board 

Acrylamide Review Panel 

CHAIR 

Dr. Deborah Cory-Slechta, Professor, Department of Environmental Medicine, School of 

Medicine and Dentistry, University of Rochester, Rochester, NY 

PANEL MEMBERS 

Dr. Alfred Branen, Associate Vice President, University of Idaho, Coeur d'Alene, ID 

Dr. Daniel R. Doerge, Research Chemist, National Center for Toxicological Research, Food and 

Drug Administration, Jefferson, AR 

Dr. James S. Felton, Senior Biomedical Scientist, University of California, Lawrence 

Livermore National Laboratory, Livermore, CA 

Dr Timothy Fennell, Senior Research Chemist, Drug Metabolism and Pharmacokinetics, RTI 

International, Research Triangle Park, NC 

Dr. Penelope Fenner-Crisp, Independent Consultant, North Garden, VA 

Dr. Jeffrey Fisher, Professor, Department Environmental Health Science, University of 

Georgia, Athens, GA 

Mr. Sean Hays, President, Summit Toxicology, Allenspark, CO 

Dr. Steven Heeringa, Director, Division of Surveys and Technologies, Institute for Social 

Research, University of Michigan, Ann Arbor, MI 

Dr. Richard M. LoPachin, Professor of Anesthesiology, Department of Anesthesiology, 

Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY 

Dr. Lorelei Mucci, Assistant Professor, Harvard Medical School, Channing Laboratory, Boston, 

MA 

Dr. Jerry M. Rice, Distinguished Professor, Department of Oncology, Lombardi Cancer Center, 

Box 571465, Georgetown University Medical Center, Washington, DC 

Dr. Dale Sickles, Professor and Vice-Chair, Department of Cellular Biology and Anatomy, 

Medical College of Georgia, Augusta, GA 

4
Dr. Gina Solomon, Senior Scientist, Health and Environment Program, Natural Resources 

Defense Council, San Francisco, CA 

Dr. Anne Sweeney, Professor of Epidemiology, Commonwealth Medical Education, The 

Commonwealth Medical College, Scranton, PA 

Dr. Lauren Zeise, Chief, Reproductive and Cancer Hazard Assessment Branch, Office of 

Environmental Health Hazard Assessment, California Environmental Protection Agency, 

Oakland, CA 

SCIENCE ADVISORY BOARD STAFF 

Dr. Suhair Shallal, Designated Federal Officer, EPA Science Advisory Board, Science 

Advisory Board Staff Office, Washington, DC 

5
U.S. Environmental Protection Agency 

Science Advisory Board 

CHAIR 

Dr. Deborah L. Swackhamer, Professor, Co-Director of the Water Resources Center,

University of Minnesota School of Public, St. Paul, MN

SAB MEMBERS 

Dr. Gregory Biddinger, Coordinator, Natural Land Management Programs, Toxicology 

and Environmental Sciences, ExxonMobil Biomedical Sciences, Inc., Houston, TX 

Dr. Thomas Burke, Professor, Department of Health Policy and Management, Johns 

Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 

Dr. James Bus, Director of External Technology, Toxicology and Environmental 

Research and Consulting, The Dow Chemical Company, Midland, MI 

Dr. Deborah Cory-Slechta, Professor, Department of Environmental Medicine, School of 

Medicine and Dentistry, University of Rochester, Rochester, NY 

Dr. Maureen L. Cropper, Professor, Department of Economics, University of Maryland, 

College Park, MD 

Dr. Virginia Dale, Corporate Fellow, Environmental Sciences Division, Oak Ridge 

National Laboratory, Oak Ridge, TN 

Dr. Kenneth Dickson, Regents Professor, Department of Biological Sciences, University 

of North Texas, Aubrey, TX 

Dr. David A. Dzombak, Walter J. Blenko Sr. Professor of Environmental Engineering, 

Department of Civil and Environmental Engineering, College of Engineering, Carnegie 

Mellon University, Pittsburgh, PA 

Dr. Baruch Fischhoff, Howard Heinz University Professor, Department of Social and 

Decision Sciences, Department of Engineering and Public Policy, Carnegie Mellon 

University, Pittsburgh, PA 

Dr. James Galloway, Professor, Department of Environmental Sciences, University of 

Virginia, Charlottesville, VA 

Dr. James K. Hammitt, Professor, Center for Risk Analysis, Harvard University, Boston, 

MA 

6
Dr. Rogene Henderson, Senior Scientist Emeritus, Lovelace Respiratory Research 

Institute, Albuquerque, NM 

Dr. James H. Johnson, Professor and Dean, College of Engineering, Architecture & 

Computer Sciences, Howard University, Washington, DC 

Dr. Bernd Kahn, Professor Emeritus and Director, Environmental Radiation Center, 

Nuclear and Radiological Engineering Program, Georgia Institute of Technology, Atlanta, 

GA 

Dr. Agnes Kane, Professor and Chair, Department of Pathology and Laboratory Medicine, 

Brown University, Providence, RI 

Dr. Meryl Karol, Professor Emerita, Graduate School of Public Health, University of 

Pittsburgh, Pittsburgh, PA 

Dr. Catherine Kling, Professor, Department of Economics, Iowa State University, Ames, 

IA 

Dr. George Lambert, Associate Professor of Pediatrics, Director, Center for Childhood 

Neurotoxicology, Robert Wood Johnson Medical School-UMDNJ, Belle Mead, NJ 

Dr. Jill Lipoti, Director, Division of Environmental Safety and Health, New Jersey 

Department of Environmental Protection, Trenton, NJ 

Dr. Michael J. McFarland, Associate Professor, Department of Civil and Environmental 

Engineering, Utah State University, Logan, UT 

Dr. Judith L. Meyer, Distinguished Research Professor Emeritus, University of Georgia, 

Lopez Island, WA 

Dr. Jana Milford, Associate Professor, Department of Mechanical Engineering, 

University of Colorado, Boulder, CO 

Dr. M. Granger Morgan, Lord Chair Professor in Engineering, Department of 

Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA 

Dr. Rebecca Parkin, Professor and Associate Dean, Environmental and Occupational 

Health, School of Public Health and Health Services, The George Washington University 

Medical Center, Washington, DC 

Mr. David Rejeski, Director, Foresight and Governance Project, Woodrow Wilson 

International Center for Scholars, Washington, DC 

Dr. Stephen M. Roberts, Professor, Department of Physiological Sciences, Director, 

Center for Environmental and Human Toxicology, University of Florida, Gainesville, FL 

7
Dr. Joan B. Rose, Professor and Homer Nowlin Chair for Water Research, Department of 

Fisheries and Wildlife, Michigan State University, East Lansing, MI 

Dr. James Sanders, Director and Professor, Skidaway Institute of Oceanography, 

Savannah, GA 

Dr. Jerald Schnoor, Allen S. Henry Chair Professor, Department of Civil and 

Environmental Engineering, Co-Director, Center for Global and Regional Environmental 

Research, University of Iowa, Iowa City, IA 

Dr. Kathleen Segerson, Professor, Department of Economics, University of Connecticut, 

Storrs, CT 

Dr. Kristin Shrader-Frechette, O'Neil Professor of Philosophy, Department of Biological 

Sciences and Philosophy Department, University of Notre Dame, Notre Dame, IN 

Dr. V. Kerry Smith, W.P. Carey Professor of Economics, Department of Economics, 

W.P Carey School of Business, Arizona State University, Tempe, AZ 

Dr. Thomas L. Theis, Director, Institute for Environmental Science and Policy, 

University of Illinois at Chicago, Chicago, IL 

Dr. Valerie Thomas, Anderson Interface Associate Professor, School of Industrial and 

Systems Engineering, Georgia Institute of Technology, Atlanta, GA 

Dr. Barton H. (Buzz) Thompson, Jr., Robert E. Paradise Professor of Natural Resources 

Law at the Stanford Law School and Director, Woods Institute for the Environment 

Director, Stanford University, Stanford, CA 

Dr. Robert Twiss, Professor Emeritus, University of California-Berkeley, Ross, CA 

Dr. Lauren Zeise, Chief, Reproductive and Cancer Hazard Assessment Branch, Office of 

Environmental Health Hazard Assessment, California Environmental Protection Agency, 

Oakland, CA 

LIAISON MEMBERS 

Dr. Steven Heeringa, (FIFRA SAP), Research Scientist and Director, Statistical Design Group, 

Institute for Social Research (ISR), University of Michigan, Ann Arbor, MI 

Dr. Melanie Marty, (CHPAC Chair), Chief, Air Toxicology and Epidemiology Branch, Office of 

Environmental Health Hazard Assessment, California EPA, Oakland, CA 

SCIENCE ADVISORY BOARD STAFF 

Mr. Thomas Miller, Designated Federal Officer, EPA SAB, Washington, DC 

8
TABLE OF CONTENTS 

EXECUTIVE SUMMARY........................................................................................................... 10

INTRODUCTION........................................................................................................................ 16

RESPONSES TO THE CHARGE QUESTIONS....................................................................... 17

Question 1. 17

Question 2. 19

Question 3. 21

Question 4. 22

Question 5. 24

Question 6. 25

Question 7. 27

Question 8 28

Question 9. 34

Question 10. 34

Question 11. 35

Question 12. 36

Question 13. 36

Question 14. 38

Question 15. 39

Question 16. 40

Question 17. 41

Question 18. 42

Question 19. 44

Question 20. 46

Question 21. 47

Question 22. 50

Question 23. 50

Question 24. 51

Question 25. 52

Question 26. 53

ABREVIATIONS ........................................................................................................................ 54

REFERENCES ............................................................................................................................ 55

Appendix A Memorandum and Charge Questions ................................................................ 68

Appendix B Proposed Modes of Action (MOAs) for Acrylamide Neurotoxicity...................... 76

9
EXECUTIVE SUMMARY 

 This report was prepared by the Science Advisory Board (SAB) Acrylamide Review 

Panel (the “Panel”) in response to a request by EPA’s Office of Research and Development 

(ORD) to review the Draft IRIS Toxicological Review of Acrylamide (hereafter referred to as 

the draft document). The Panel deliberated on the charge questions (see Appendix A) during a 

March 10-11, 2008 face-to-face meeting and discussed its draft report in a subsequent conference 

call on July 16, 2008. The final draft of the panel’s report was reviewed and approved during a 

meeting of the chartered SAB on October 28, 2008. There were 26 charge questions that focused 

on the selection of the most sensitive non-cancer health endpoint, the use of a PBTK model for 

the derivation of a proposed oral reference dose (RfD), an inhalation reference concentration 

(RfC) for non-cancer endpoints, as well as the cancer descriptor, oral slope factor, and inhalation 

unit risk for acrylamide. The Panel encourages the Agency to review relevant data which has 

been published since their draft assessment was completed as they revise and finalize the IRIS 

document. 

 This Executive Summary highlights the Panel’s major findings and recommendations as 

a result of their deliberations. The responses that follow represent the views of the Panel. 

Selection of Endpoint 

 In the draft document, EPA identified neurotoxicity as the most sensitive non-cancer 

effect from exposure to acrylamide. This endpoint was based on an extensive database of animal 

and human studies. Other endpoints were also considered, such as reproductive toxicity and 

heritable germ cell effects. The Panel agreed that based on the existing toxicity data base for 

acrylamide, neurotoxicity does appear to be the most sensitive non-cancer endpoint, and 

therefore, the most appropriate for developing the RfD and RfC for non-cancer effects from 

exposure to acrylamide. 

Mechanism of Action 

 The Panel discussed two hypotheses regarding the mechanism of acrylamide 

neurotoxicity. The Panel did not attempt to resolve the debate over a definitive or single MOA 

for neurotoxicity; however, there was agreement that the discussion of MOA is important for 

10
inclusion in the draft document. The Panel found the separation of the discussion of MOA(s) for 

neurotoxicity in two different sections of the document confusing and recommended their 

incorporation into a single section. A more complete presentation by the Panel of these MOAs 

has been appended (see Appendix B) to this report for EPA’s consideration as they revise their 

draft document. 

Derivation of RfD 

 EPA’s proposed RfD (0.003 mg/kg-day) for acrylamide is based on a benchmark dose 

analysis of the dose-response relationship for neurotoxicity in two chronic drinking water 

exposure bioassays using Fischer 344 rats. Uncertainty factors and a PBTK model were used to 

extrapolate the animal dose-response to a human equivalent dose-response in the derivation of 

the RfD. The Panel afforded considerable discussion to the question of whether the Friedman et 

al. (1995) and Johnson et al. (1986) studies were the best choices for derivation of the 

quantitative RfD (and RfC). The main concerns with these studies are that they were primarily 

designed as cancer bioassays and therefore did not include the most sensitive measures of 

neurotoxicity. Nevertheless, the Panel agreed that the selected studies did have some important 

strengths, including reasonable statistical power due to the relatively large number of animals, 

chronic dosing, and the fact that the NOAELs for the endpoint in the two studies were similar, 

implying some precision in the effect estimate measured. Several Panel members noted that the 

lack of sensitive functional/behavioral assessments is a significant data gap that should be 

considered in the context of setting a database uncertainty factor. Use of the benchmark dose 

methodology in this assessment was deemed scientifically supported, given the nature and 

robustness of the data sets available on the endpoint of interest. The calculations and choices 

made were described clearly and at an appropriate level of detail. The Panel suggested that EPA 

undergo the exercise of generating an RfD from the Calleman study for purposes of comparison 

with the RfD derived based on the animal data. This comparison can serve as a type of 

sensitivity analysis, to help determine whether the RfD based on the Johnson study appears to be 

adequately health-protective despite the insensitive endpoint used in that study. 

11
Heritable Germ Mutations 

 EPA’s draft document concluded that data exist that reveal acrylamide’s capacity to 

induce heritable germ cell effects at doses somewhat above those at which neurotoxicity has 

been observed, but that there are as yet no studies providing an in-depth examination of doseresponse or identification of credible no-effect levels. The Panel supports the Agency’s 

conclusions that exposure to acrylamide in animals leads to heritable gene mutations and that 

these results indicate that it may also pose a hazard to humans. In addition, the Panel supports 

the Agency’s conclusions that the available data are not adequate to conduct a robust assessment 

of this endpoint at this time. There is still uncertainty about the mode of action of acrylamide 

and its metabolite, glycidamide, in the induction of heritable genetic effects. The potential for 

DNA adducts of glycidamide to play a role is an attractive hypothesis for the mode of action. 

The Panel found the discussion in the document on heritable germ cell effects useful and 

presented in a clear, transparent manner reflective of the current science. However, the Panel 

suggested that, given the serious consequences of heritable germ cell effects, the considerable 

deficiencies of the database should be identified and the significance of this endpoint 

emphasized. 

Physiologically-Based Toxicokinetic (PBTK) modeling 

 A physiologically-based toxicokinetic (PBTK) model originally developed by Kirman et 

al. (2003), and recalibrated by EPA with more recent kinetic and hemoglobin binding data in 

rats, mice, and humans, was used in the derivation of the RfD. The PBTK model was used to 

extrapolate from the animal dose-response relationship to derive a human equivalent 

concentration. The Panel commends EPA for their efforts to adapt the PBTK model of Kirman 

et al. (2003) for acrylamide and glycidamide, recognizing that this was a complex and 

challenging task. The Panel believes, though, that the documentation is not adequate to 

determine whether the recalibrated Kirman model is appropriate for its intended use. While the 

Panel considered that the model structure was reasonable, the parameter estimates require greater 

justification. The Panel was concerned about the ability of the model to adequately simulate the 

kinetics of acrylamide and glycidamide. The Panel has proposed several modifications to the 

PBTK model for making the estimates of internal dose in rats needed for both the non-cancer and 

cancer assessments and for calculating the Human Equivalent Dose (HED). 

12
Uncertainty Factors 

 EPA has proposed to use the default 10X uncertainty factors (UF) to account for 

intraspecies (i.e., human) differences. The Panel concurred with this choice, noting that there 

were insufficient data on inter-individual differences, based upon lifestage, gender or genetic 

characteristics, to support departing from the default. Consensus was not achieved on the issue of 

the inclusion of an UF to account for deficiencies in the existing database. 

EPA has suggested that the acrylamide IRIS document include a Table that lists points of 

departure for various endpoints to facilitate a Margin of Exposure (MOE) evaluation by EPA’s 

Regional or Program offices, or by other end users of the assessment. The Panel recommends 

the inclusion of such a table, to the extent possible, in all IRIS documents, which provides 

information that may be used to conduct a variety of analyses. Uses may include, for example, 

MOE analyses for specific endpoints of interest and/or for other than lifetime durations of 

exposure and for windows of increased susceptibility early in the life cycle, in addition to the 

traditional lifetime focus. Agency risk assessments would benefit from the inclusion of 

transparently-developed, peer-reviewed consensus hazard values. 

Carcinogenicity 

 The Panel believes that the rationale and justification for acrylamide being a “likely 

human carcinogen” has been well described and the conclusion is scientifically supportable 

based on the fact that it produces tumors in rodents of both sexes, that there are multiple tumor 

sites, and tumors are induced via multiple routes of exposure. Acrylamide is also clearly and 

reproducibly carcinogenic in both rats and mice. Nonetheless, the draft document can be 

improved by expanding the discussion of biological plausibility and coherence beyond DNA 

adducts. The weight of evidence supports a mutagenic mode of action for carcinogenesis, and 

overall the rationale has been clearly and objectively presented. During the advisory process, 

information was presented by several members of the public for the Panel’s consideration. 

While the Panel did consider the information regarding alternative, non-mutagenic MOAs, they 

did not find it to be compelling. Significant biological support and data on any putative alternate 

MOAs are not sufficient for either explaining cancer findings or quantifying dose response 

13
relationships. More than one MOA may operate for a given carcinogenic chemical, and the 

likelihood that more than a single MOA is operative increases as levels of exposure increase. 

EPA used two chronic drinking water exposure bioassays in Fischer 344 rats (Friedman 

et al., 1995; Johnson et al., 1986) to derive the oral cancer slope factor, and to identify the 

tumors of interest for the MOA discussion. The Panel agrees that the two chronic bioassays in 

F344 rats are the main studies to consider in dose response analysis, but the rationale for using 

only the Friedman et al. study for derivation of the oral cancer slope factor should be improved 

with the strengths and limitations of both studies discussed in greater depth The use of the 

Weibull-in-time multistage-in-dose analysis is a reasonable and scientifically justifiable way to 

take into account the early mortality in the high dose group in the male study. The decision not 

to employ this analysis, in the case of the female because mortality across treatment and control 

groups did not differ and the overall survival appears to be fairly good, is also reasonable. 

Derivation of the RfC and IUR 

The draft document used area under the curve (AUC) in the blood for the putative 

genotoxic metabolite, glycidamide, as the dose metric for the PBTK model analysis to derive the 

human equivalent concentration. The Panel agreed that the AUC for glycidamide is the best 

choice for estimating the human equivalent concentration to derive the oral slope factor. One 

consideration in using this as the dose metric, however, comes from some of the human studies 

in which variability is not accounted for adequately. Consideration of additional human data can 

provide an improved basis for adjustments for cross-species differences in pharmacokinetics, as 

well as human variability in glycidamide formation from acrylamide. 

As with the RfC, EPA concluded that there were insufficient inhalation data to derive an 

inhalation unit risk (IUR). The PBTK model was used in a route-to-route extrapolation of the 

dose-response relationship from the oral data, and to estimate the human equivalent 

concentration for inhalation exposure to acrylamide. The Panel commended the EPA for using 

the PBTK model to fill the gap resulting from the absence of robust animal toxicology studies 

investigating neurotoxicity via the inhalation route that would support the development of an 

RfC. The Panel agreed that the absence of evidence for route of entry specific effects would 

allow route-to-route extrapolation for deriving an RfC based on using the PBTK model to 

calculate the human equivalent concentration (HEC). 

14
Age-dependent adjustment factors 

 The Panel agreed that the recommendation to use the age-dependent adjustment factors is 

well justified and transparently and objectively described. Additionally the Panel believed that 

the discussion of uncertainties is adequate, but that human variability could be more completely 

addressed. There is no characterization of sensitive populations, and this should be explored and 

discussed to a much greater extent. 

PBTK model and uncertainty 

 The Panel commends EPA for using the PBTK model for developing the RfD, RfC and 

Cancer Slope Factors for acrylamide. The Panel notes that the use of internal dose metrics 

combined with a fairly robust understanding of the mechanism of action may replace the use of 

the default interspecies uncertainty factor for toxicokinetic differences (i.e., 101/2) , but not the 

default interspecies uncertainty factor for toxicodynamics. This uncertainty factor is still needed 

in deriving the RfC and RfD. Further the Panel strongly encourages the Agency to move 

forward with revising and finalizing their assessment.

Additional Comments 

The Panel is aware that studies of acrylamide toxicity are ongoing in the FDA. However, 

these studies will not be finalized or go through the peer-review process for some time. 

Therefore, the Panel believed that the draft risk assessment document should not be held-up 

awaiting those results, but that the Agency should consider relevant data which has been 

published since their draft assessment was released in December 2007 as they finalize the IRIS 

document on Acrylamide. 

15
INTRODUCTION 

 This report was prepared by the Science Advisory Board (SAB) Acrylamide Review 

Panel (the “Panel”) in response to a request by EPA’s Office of Research and Development 

(ORD) to review the Draft Toxicological Review of Acrylamide (hereafter referred to as the 

“draft document”). The IRIS Toxicological Review of Acrylamide, released in December 2007, 

is a compilation and summary of the available information on the potential for cancer and noncancer hazardous effects in humans from exposure to acrylamide. 

 The SAB was asked to comment on (1) whether the document is logical, clear and 

concise, (2) if the discussion is objectively and transparently represented, and (3) if it presents an 

accurate synthesis of the scientific evidence for non-cancer and cancer hazard. The SAB was 

also asked to identify any additional relevant studies that should be included in the evaluation of 

the non-cancer or cancer health effects of acrylamide, or in the derivation of toxicity values. In 

addition, the SAB was asked to provide advice on 26 specific charge questions related to the 

derivation of a proposed oral reference dose (RfD) and an inhalation reference concentration 

(RfC) for non-cancer endpoints, as well as the cancer descriptor, oral slope factor, and inhalation 

unit risk for acrylamide. 

 The Panel deliberated on the charge questions during a March 10-11, 2008, face-to-face 

meeting and discussed their draft report in a subsequent conference call on July 16, 2008. The 

final draft of the panel’s report was reviewed and approved during a meeting of the chartered 

SAB on October 28, 2008. 

The responses that follow represent the views of the Panel. The charge to the SAB is 

available in Appendix A. 

16
RESPONSES TO THE CHARGE QUESTIONS 

Charge Question 1. Please comment on the selection of neurotoxicity as the most appropriate 

choice for the most sensitive endpoint (in contrast to reproductive toxicity, heritable germ cell 

effects, or other endpoint) based upon the available animal and human data. 

 Based on the existing toxicity data base for acrylamide, neurotoxicity does appear to be 

the most sensitive endpoint, and therefore, the most appropriate for developing the (non-cancer) 

RfD and RfC. Animal studies report microscopically-detected degeneration in peripheral nerve 

cells at doses of 1-2 mg/kg day, as compared to levels of 3-13 mg/kg day to detect impaired male 

reproductive performance. Animal studies provide a clear mechanistic understanding whereby 

low-dose, subchronic exposure leads to toxicity with concomitant nerve damage. Acrylamide 

has a direct or indirect effect on the motor protein kinesin or nerve terminals, producing damage 

in the peripheral and central nervous systems, which leads to sensory and motor disease. 

Correspondingly, reports of central-peripheral neuropathy, ataxia and muscle weakness in 

exposed human cohorts have been documented since the early 1950’s. Acute occupational 

exposure to acrylamide can lead to an immediate neurologic response, e.g., sweating, nausea, 

myalgia, numbness, paresthesia, and weakened legs and hands. Following termination of short 

term exposure, these acute effects disappear. 

There were issues of concern that should be noted: 

1) As detailed in the response to Question 4, the determination of accurate benchmark doses 

(e.g., LOAELs, NOAELs, RfDs) from the Friedman et al. (1995) and Johnson et al. (1986) 

studies may be compromised by their lack of functional testing of neurotoxicity and the use 

of a relatively insensitive measure, peripheral axonopathy, as the primary index 

neurotoxicity. 

2) There was concern that axonal degeneration observed under light microscopy was the 

endpoint chosen from the Friedman et al. (1995) and Johnson et al. (1986) studies for 

derivation of the RfD and RfC. Animal studies indicate that nerve terminal degeneration can 

17
occur prior to axonal degeneration at some doses. This would suggest that all of the cited 

studies, including the subchronic Burek study and the 2 year bioassay studies of sciatic nerve 

(Friedman et al., 1995) and tibial nerve (Johnson et al., 1986) axons, in looking at axonal 

degeneration, may have missed a preceding terminal degeneration at a lower dose, 

particularly as no specific mention of terminal degeneration is provided and 

functional/behavioral measures of neurotoxicity were not included. 

3) It should be noted that future studies may demonstrate effects of acrylamide exposure on 

male reproductive function, as currently evidenced in animal studies by increased pre- and 

post-implantation losses and decreased litter sizes, at even lower doses than those currently 

associated with neurotoxicity after acrylamide dosing in animal studies. The draft document 

states that “associations between human exposure to acrylamide and reproductive effects 

have not been reported” (p. 187 and p. 224); rather, these associations have not been 

adequately studied. The lack of human data is a major limitation in this regard. As noted in 

the draft document, data also exists that reveal acrylamide’s capacity to induce heritable 

germ cell effects at doses somewhat above those at which neurotoxicity has been observed, 

but there are as yet no studies providing an in-depth examination of dose response or 

identification of credible no-effect levels. The heritable germ cell effects are very worrisome 

and deserve even more consideration, including perhaps the use of this endpoint to generate 

an independent RfD. 

4) Although still controversial and recognizing that cigarette smoke is a complex mixture made 

up of hundreds of compounds, there is growing evidence that supports an association 

between cigarette smoking, a known source of acrylamide exposure, and altered semen 

parameters, including concentration, morphology, motility, and DNA fragmentation 

(Richthoff et al., 2008; Sepaniak et al., 2006; Marinelli et al., 2004). The lack of data 

regarding potential interactions between acrylamide and other exposures, including cigarette 

smoke, alcohol use, and cosmetics (another source of acrylamide exposure) has been cited as 

a major limitation in studies of human acrylamide exposure and adverse health effects (Rice 

2005; draft document p.194; p. 224). The investigation of altered semen parameters among 

18
occupationally exposed males, controlling for smoking and alcohol consumption, should be a 

high priority. 

New References

 Richthoff J, Elzanaty S, Rylander L, Hagmar L, Giwercman A. Association between 

tobacco exposure and reproductive parameters in adolescent males. Int J Androl 2008; 31:31-9. 

 Sepaniak S, Forges T, Foliguet B, Bene MC, Monnier-Barbarino P. The influence of 

cigarette smoking on human sperm quality and DNA fragmentation. Toxicol 2006; 223:54-60. 

 Marinelli D, Gaspari L, Pedotti P, Taioli E. Mini-review of studies on the effect of 

smoking and drinking habits on semen parameters. Toxicol 2004; 207:185-92. 

Charge Question 2. Please comment on the discussion of mode of action for acrylamideinduced neurotoxicity. 

 The Panel found the separation of the discussion of MOA(s) for neurotoxicity in two 

different sections of the document (Section 4.6.1, pages 123-124; and Section 4.7.3, pages 134-

136) confusing and recommends their incorporation into a single section. 

 Acrylamide is a member of the type-2 alkene chemical class, which includes acrolein, 

methylvinyl ketone and methyl acrylate. A weight of evidence evaluation of the current body of 

data now suggests that the type-2 alkenes produce toxicity via a common molecular mechanism: 

i.e., formation of adducts with essential sulfhydryl thiolate groups on proteins that play 

regulatory roles in cellular processes (LoPachin et al., 2007a,b, 2008a; reviewed in LoPachin and 

Barber, 2006b; LoPachin et al., 2008b). 

 Currently, there are two hypotheses regarding the mechanism of acrylamide 

neurotoxicity: 1) Acrylamide/glycidamide inhibits fast axonal transport by forming adducts with 

kinesin, the transport motor (reviewed in Sickles et al., 2002). 2) Acrylamide disrupts nerve 

nitric oxide (NO) signaling at the nerve terminal (reviewed in LoPachin et al., 2006a). The 

Panel did not attempt to resolve the debate over the MOA of neurotoxicity. It is also possible 

that both MOAs may be pertinent, and studies directly comparing the time course of the two 

proposed MOAs in a single model have not been carried out. However, the Panel agreed that the 

further delineation of MOAs will improve acrylamide risk assessment. Both of the proposed 

19
MOAs suggest that visible axonal degeneration seen with light microscopy is not likely to be the 

low-dose effect in the causal pathway. Regardless, it should also be evident that substantial, 

detailed molecular information is available regarding mechanisms of acrylamide neurotoxicity 

and that these data should be included. 

Thus, the following deficiencies in the draft document were identified by the Panel: 

1) As drafted, the document’s coverage of research findings is incomplete and does not 

adequately reflect the current molecular understanding of the mechanisms of acrylamide 

neurotoxicity. Moreover, information in the document regarding the hypothesized MOAs is 

not presented in a sufficiently transparent manner consistent with the Agency’s guidance on 

identification of the key events leading to the effect of concern, i.e., use of the modified 

Bradford Hill criteria with respect to dose-response concordance, temporal relationship(s), 

strength, consistency, specificity of association and biological plausibility and coherence, as 

is done for carcinogenicity. 

2) There was insufficient discussion of acrylamide adduct chemistry and corresponding 

neuronal targets pertinent to understanding the MOAs. 

3) There was lack of a discussion of residual questions surrounding the respective roles of the 

parent toxicant, acrylamide, and its epoxide metabolite, glycidamide, in the production of 

neurotoxicity. 

 The Panel recommends that the Agency expand its discussion of the two MOAs. Panel 

members provided more specific text that describes the two proposed MOAs, and the Panel 

offers this text to EPA for consideration in revising the acrylamide assessment. The text is given 

in Appendix B of this report. 

20
Charge Question 3. Please comment on the qualitative discussion of acrylamide’s heritable 

germ cell effects and whether the discussion is clear, transparently and objectively described, 

and reflective of the current science. 

 Discussion in the document of heritable germ cell effects, consisting of five (5) heritable 

translocation studies, the two (2) specific locus studies, two (2) studies on acrylamide 

transformation to glycidamide and the importance of this metabolism to toxicity, is relevant and 

useful, and is presented in a clear, transparent manner reflective of the current science. However, 

the discussion is a linear description of germ cell toxicity with little synthesis, analysis and 

scrutiny. While some SAB members considered the presentation objective, some expressed 

concerns over the lack of inclusion of all potential MOAs. Given the serious consequences of 

heritable germ cell effects, the considerable deficiencies of the database should be identified and 

the significance of this endpoint emphasized. 

 The entire section is prefaced and summarized with the perspective that DNA adduct 

formation and mutagenicity is the only operative mechanism for heritable germ cell effects of 

acrylamide. While adducts can certainly lead to these observations, there are alternative 

mechanisms for discussion. Clastogenic mechanisms, as well as, mitotic spindle defects are 

viable candidates for dominant lethal effects. There is a wealth of acrylamide studies reporting 

these alternative mechanisms that should be included in this discussion as well. They were 

briefly outlined in the carcinogenicity section, but should also be identified here. In regards to 

spindle defects, the effects of acrylamide on kinesin motors involved in cell division should be 

added to the document (Sickles et al., 2007). 

 Adequate response data are lacking in the existing heritable germ cell studies such that 

the shape of the dose response relationship cannot be ascertained. However, in Tyl et al. (2000) 

dose responses are identified - a NOAEL of 2 mg/kg/d and a LOAEL of 5 mg/kg/d for a 13 week 

exposure. All of the dominant lethal studies were conducted at a dose of 50 mg/kg or higher and 

most with multiple exposures. The specific locus studies were conducted at 50 mg/kg/d for 5 

days (Russel et al., 1991) or with a single 100-125 mg/kg exposure (Ehling and NeuhauserKlaus, 1992). The discrepancy between the negative results of Russel et al. (1991) and the 

positive results of Ehling and Neuhauser-Klaus (1992) may be dose-related or due to other 

factors. The fact that heritable translocations appeared at high frequency at the lowest doses 

21
tested implies that even lower doses may produce such effects. 

 However, in the absence of these data, the uncertainty should be identified. As a 

consequence of these limitations in the database, there is some uncertainty related to the RfD. 

The Panel unanimously agreed that this is an extremely serious data gap that should be a top 

priority for further study. Additional studies to address the aforementioned database deficiencies 

in mechanisms and dose-responses would be desirable. 

 The document requires correction in that the NTP/CERHR report was published in 

February 2005, not 2004. Also, there appears to be a discrepancy in the text (Pg 117 indicates the 

historical controls were 6%, yet on pg 116 in the discussion of the Adler et al. (1994) study, the 

historical controls are listed as 5/9890 which is 0.05%). 

Charge Question 4.  Please comment on whether the selection of the Friedman et al, 1995 and 

Johnson et al, 1986 studies as co-principal studies has been scientifically justified. Although 

EPA considers Friedman et al and Johnson et al to be co-principal studies, the final 

quantitative RfD value is derived only from the Johnson study. Please comment on this aspect 

of the EPA’s approach. Please comment on whether this choice is transparently and 

objectively described in the document. Please identify and provide the rationale for any other 

studies that should be selected as the principal studies. 

 The Panel afforded considerable discussion to the question of whether the Friedman et al. 

(1995) and Johnson et al. (1986) studies were the best choices for derivation of the quantitative 

RfD (and RfC). The main concerns with these studies included the fact that they were primarily 

designed as cancer bioassays rather than for evaluation of neurotoxicity. Specifically, the Panel 

contended that the endpoint of axonal degeneration visible under light microscopy is an 

insensitive measure of neurotoxicity. Alterations visible under electron microscopy or 

functional/behavioral alterations would have provided more sensitive endpoints. 

 Nevertheless, the Panel agreed that the selected studies did have some important 

strengths, including reasonable statistical power due to the relatively large number of animals, 

chronic dosing, and the fact that the NOAELs for the endpoint in the two studies were similar, 

implying some precision in the effect estimate measured. The Panel also noted that there are no 

studies yet available which include the sensitive functional/behavioral assessments that would be 

22
most desirable. Several Panel members noted that this issue is a significant data gap that should 

be considered in the context of setting a database uncertainty factor. 

 With respect to the Burek et al. (1980) study, the Panel notes that while the endpoint in 

this study (axolemmal invaginations under electron microscopy) is a highly sensitive one for use 

in risk assessment, the study was subchronic. One Panel member proposed that EPA consider 

generating an RfD based on the data in Burek et al. (1980), but not use a subchronic-to-chronic 

uncertainty factor given the existence of the two chronic studies, to compare the resulting RfD to 

that based on the less sensitive endpoint of axonal degeneration. Such a comparison might begin 

to quantify the degree of potential under-estimate of risk due to the less satisfactory choice of 

endpoint in the Johnson and Friedman studies. 

 There was a brief discussion of the report of foot splay at 0.5 mg/kg in F0 males in the 

Tyl et al. (2000a) two-generation reproductive toxicity/dominant lethal mutation study. The use 

of this gross functional endpoint could also serve as a point of departure, although it was 

considered questionable because: it was only observed in the F0 generation, was found in control 

animals to some degree (raising questions about the methodology used in the lab), and did not 

follow a clear dose-response relationship. Overall, the Panel decided that the Tyl study was not a 

good choice for derivation of the RfD. 

 The Panel also considered the option of deriving an RfD based on human data. Both the 

Calleman et al. (1994) and the Hagmar et al. (2001) studies contain sufficient data to allow the 

Agency to calculate an RfC or potentially an RfD. In this regard, the Panel made the following 

observations: (1) in general, it is preferable to use human data when available; (2) the Calleman 

study included a measure of internal dose (adduct levels) and a fairly sensitive measure of effect, 

thereby making it appealing for risk assessment; (3) PBTK modeling could allow dose 

extrapolation based on adduct levels, such that an ingested or inhaled dose could be estimated for 

purposes of setting either an RfC or an RfD from the data. 

 However, the Panel also cautioned that there are a number of drawbacks to using the 

human studies, including the following: (1) the sample sizes are small; (2) the samples mostly 

include young adult males; (3) the healthy worker effect would tend to bias these studies 

(especially the Calleman study) toward the null, since workers with significant neurological 

symptoms would leave the workplace, thus selecting for individuals with lower genetic 

susceptibilities; (4) the workers in each study were exposed to other confounding neurotoxicants 

23
(acrylonitrile and N-methylolacrylamide (NMA)), but this would tend to generate a more 

conservative risk estimate because these other exposures would tend to result in an over-estimate 

of the effect; and (5) the exposure duration was relatively short and variable (1 month to 11.5 

years in the Calleman study with an average of 3 years, and 55 days in the Hagmar study). In the 

end, the Panel suggested that EPA undergo the exercise of generating an RfD from the Calleman 

study for purposes of comparison with the RfD derived based on the animal data. The Panel 

stopped short of recommending that the human RfD be used in place of the one in the draft 

document, but instead saw this as a type of sensitivity analysis, to help determine whether the 

RfD based on the Johnson study appears to be adequately health-protective despite the 

insensitive endpoint used in that study. 

Charge Question 5. Please comment on the benchmark dose methods and the choice of 

response level used in the derivation of the RfD, and whether this approach is accurately and 

clearly presented. Do these choices represent the most scientifically justifiable approach for 

modeling the slope of the dose-response for neurotoxicity? Are there other response levels or 

methodologies that EPA should consider? Please provide a rationale for alternative 

approaches that should be considered or preferred to the approach presented in the document. 

 Use of the benchmark dose methodology has become the preferred approach and an 

acknowledged improvement over the historically traditional NOAEL ÷ UF procedure for the 

derivation of RfDs. Its application in this instance is scientifically supported, given the nature 

and robustness of the data sets available for the endpoint of interest. The calculations and 

choices made were described clearly at an appropriate level of detail. 

 EPA’s Benchmark Dose guidance provides default criteria to be used for selecting the 

benchmark response (BMR). For quantal data, an excess risk of 10% is the default BMR, since 

the 10% response is at or near the limit of sensitivity in most studies. In this case, even though 

the BMR at 10% extra risk also was within the range of observation, the BMR5 was selected for 

the point of departure. The choice of a BMR5 makes sense and is well-justified: (1) the 95% 

lower bound of the benchmark dose (BMD), BMDL5

, remained near the range of observation; 

(2) the 5% extra risk level is supportable given the relatively large number of animals used in the 

critical studies; and (3) the use of BMDL5 

is consistent with the Agency’s technical guidance for 

24
BMD analysis which allows flexibility in making such a choice. One of the strengths of the 

Johnson study is that it is sufficiently large (i.e., numbers of animals/group) to allow the lower 

5% bound to be identified with sufficient stability that it is usable for risk assessment purposes. 

Therefore, it is reasonable to use that strength in the underlying data set and choose this number. 

Such a choice is appropriately conservative (i.e., public health protective). 

 While alternative approaches such as averaging the BMDLs from each of the four data 

sets (Friedman and Johnson, male and female) rather than using just the one for males in the 

Johnson study were discussed, the Panel concluded that the steps described by the Agency in the 

draft document represented the preferred approach. 

Charge Question 6. Please comment on the selection of the uncertainty factors (other than the 

interspecies uncertainty factor) applied to the point of departure (POD) for the derivation of 

the RfD. For instance, are they scientifically justified and transparently and objectively 

described in the document? [Note: This question does not apply to the interspecies uncertainty 

factor which is addressed in the questions on the use of the PBTK model (see PBTK model 

questions below)] 

 

 The Agency has proposed to use a composite uncertainty factor (UF) of 30: 10X to 

represent human variability (10H) and 3X to reflect the toxicodynamic component of the default 

interspecies uncertainty factor (10A). The other half of the 10x interspecies UF, i.e., the 3X that 

would otherwise account for interspecies differences in toxicokinetics, is subsumed in the PBTK 

modeling. 

 Two points were raised about the use of 3X as a default to account for interspecies 

toxicodynamic differences. First, it was noted that the rodents are less sensitive to the neurotoxic 

effects of acrylamide than humans. The Panel concluded that the application of a UF for 

interspecies toxicodynamics was directionally correct. Second, there is insufficient information 

available to define a chemical-specific factor and the default factor of 3X UF for interspecies in 

toxicodynamics is therefore appropriate. It was noted that recent International Programme for 

Chemical Safety guidelines divide the default 10A into 2.5X for toxicodynamic differences and 

4.0X for toxicokinetics differences, based primarily upon a review of the literature published in 

1993 -(WHO IPCS 2005. Guidance Document for the Use of Data in Development of Chemical25
specific Adjustment Factors (CSAFs) for Interspecies Differences and Human Variability in 

Dose/Concentration-Response Assessment). The use of the factor of 3 (or √10) is consistent 

with current EPA practice: according to the recent EPA (2004) Staff Paper “a default UF of 10 

for interspecies variability that can now be reduced to 3 when animal data are dosimetrically 

adjusted to account for toxicokinetics.” The Staff paper cites the EPA (2002) RfD/RfC 

methodology document. That document divides UFs “into toxicokinetic and toxicodynamic 

components that have assigned default values of 3.16 (101/2) each.” 

 EPA has proposed to use the default 10X UF to account for intraspecies (i.e., human) 

differences. The Panel concurred with this choice, noting that there were insufficient data on 

interindividual differences, based upon lifestage, gender or genetic characteristics, to support 

departing from the default. 

 Consensus was not achieved on the issue of the inclusion on an UF to account for 

deficiencies in the existing database that would confound the derivation of the most 

scientifically-defensible RfD. EPA concluded that an UFD > 1 was not necessary, arguing that 

the existing database is sufficiently robust, even though they acknowledge there are some 

unresolved issues that warrant further research: describing the MOA(s) for neurotoxicity, the 

potential for behavioral or functional adverse effects not detected in the assays to date, and the 

uncertainty that heritable germ cell effects may occur at lower than previously reported doses. 

Some Panel members agreed with EPA’s position. One Panel member noted that additional UFs 

were implicitly, if not explicitly, incorporated into the RfD derivation. Using the output of the 

log-logistic model applied to the data set for the male rats in the Johnson study resulted in the 

lowest set of BMDs/BMDLs. According to one Panel member, it was perhaps conferring an 

extra UF of ~2X. In addition, using the BMDL5 as the POD, rather than the default BMDL10, 

also could be seen as conferring an extra UF of ~2X. 

 Other Panel members, however, disagreed with the Agency’s position regarding the 

database UF, arguing that the remaining uncertainties have major implications that could result 

in effects at significantly lower doses and thus a lower RfD. Database deficiencies include the 

following: 

1) EPA had to rely on the observation of axonal degeneration visible by light microscopy, 

an endpoint which is not likely to be the most sensitive. EPA is using studies that were 

26
not designed to evaluate neurotoxicity robustly, e.g., histopathology coupled with 

systematic evaluation of functional or behavioral parameters at multiple time points with 

robust numbers of animals/treatment and robust number of treatment groups; these 

studies should be done in adult animals and in a developmental neurotoxicity study in 

order to determine whether or not critical lifestage differences exist; 

2) Both existing chronic studies were done in the rat, creating some remaining uncertainty 

about interspecies differences that is not addressed by the interspecies UF. Based upon 

the comparison of results from the Tyl et al. (2000) 2-generation study in rats and the 

Chapin et al. (1995) 2-generation study in mice, the NOAEL for (adult) neurotoxicity is 

essentially the same (0.5 mg/kg/day in rats vs. 0.8 mg/kg/day in mice), but the difference 

could potentially be driven by the dose spacing regimen rather than a true difference in 

response. The outcomes of long-term exposure in mice hold the possibility of yielding 

lower NOAELs/LOAELs/BMDs than observed/calculated from the rat data. If this were 

to occur, the RfD/RfC would be lower. 

3) The germ cell effects have not been fully explored and have major intergenerational 

implications if they do occur at dose levels lower than those for neurotoxicity. There is a 

lack of adequate data to define the dose response for heritable germ cell effects. While 

the existing data describe adverse effects at doses somewhat higher than those at which 

neurotoxicity was observed, BMD modeling of robust dose-response data may yield 

results competitive with/lower than the neurotoxicity BMDs/BMDLs. 

Charge Question 7. Please provide any other comments on the derivation of the RfD and on 

the discussion of uncertainties in the RfD. 

Acrylamide and Cumulative Risk Assessment 

 While there were no additional comments on the derivation of the RfD per se, the Panel 

did want to address the potential for cumulative effects from exposure to acrylamide and other 

type-2 alkenes. The Food Quality Protection Act (FQPA) of 1996 mandates EPA to consider the 

“cumulative effects” of pesticides and other substances that have a “common mechanism of 

toxicity” when setting, modifying or revoking tolerances for food-use pesticides. Were 

27
acrylamide registered as a food use pesticide, its activity as a type-2 alkene would support a 

cumulative risk assessment of it and other chemicals in the class. From a scientific standpoint 

and particularly from a public health perspective, this class of chemicals should be subjected to a 

cumulative risk assessment (e.g., see Wilkinson et al., 2000). Evaluating the cumulative effects 

of the type-2 alkenes is particularly germane since human exposure is pervasive; i.e. chemicals in 

this class are used extensively in the agricultural, chemical and manufacturing industries. 

Furthermore, they are well-recognized environmental pollutants (e.g., acrolein, acrylonitrile), 

food contaminants (e.g., acrylamide, methyl acrylate) and endogenous mediators of cellular 

damage (e.g., acrolein, 4-hydroxy-2-nonenal) (see LoPachin et al., 2008b). Thus, the application 

of standard approaches may result in RfDs and RfCs which could be associated with risks in the 

population. At a minimum, a caveat in this regard should be included in the acrylamide 

assessment document. 

Charge Question 8 

Use of the PBTK Model 

A physiologically-based toxicokinetic (PBTK) model originally developed by Kirman et 

al. (2003), and recalibrated by EPA with more recent kinetic and hemoglobin binding data in 

rats, mice, and humans (Boettcher et al., 2005; Doerge et al., 2005a,b; Fennell et al., 2005) 

was used in the derivation of the RfD to extrapolate from the animal dose-response 

relationship (observed in the co-principal oral exposure studies for neurotoxicity) to derive a 

human equivalent concentration (HEC). The HEC is the external acrylamide exposure level 

that would produce the same internal level of parent acrylamide (in this case the area under 

the curve [AUC] of acrylamide in the blood) that was estimated to occur in the rat following 

an external exposure to acrylamide at the level of the proposed point of departure, and related 

to a response level of 5% (i.e., the BMDL5). The model results were used in lieu of the default 

interspecies uncertainty factor for toxicokinetics differences of 101/2, which left a factor of 

101/2 (which is rounded to 3) for interspecies differences in toxicodynamics. 

 With respect to the RfC, there are presently insufficient human or animal data to 

directly derive an RfC for acrylamide. The PBTK model was thus used to conduct a route-toroute extrapolation (oral-to-inhalation) to derive an RfC based on the dose-response 

relationship observed in the co-principal oral exposure studies for neurotoxicity. In this case, 

28
the HEC was based on a continuous inhalation exposure to acrylamide in the air that would 

yield the same AUC for the parent acrylamide in the blood as that estimated for the rat 

following an external oral exposure to acrylamide at the level of the proposed point of 

departure (i.e., the BMDL5). 

Please comment on whether the documentation for the recalibrated Kirman et al. (2003) 

PBTK model development, evaluation, and use in the assessment is sufficient to determine if 

the model was adequately developed and adequate for its intended use in the assessment. 

Please comment on the use of the PBTK model in the assessment, e.g., are the model structure 

and parameter estimates scientifically supportable? Is the dose metric of area-under-thecurve (AUC) for acrylamide in the blood the best choice based upon what is known about the 

mode of action for neurotoxicity and the available kinetic data? Please provide a rationale for 

alternative approaches that should be considered or preferred to the approach presented in the 

document. 

 The Panel commends EPA for their efforts to adapt the PBTK model of Kirman et al.

(2003) for acrylamide and glycidamide, recognizing that this was a complex and challenging 

task. The modified Kirman et al. model was produced by changing the model initially described 

for the rat, and adapting it to fit updated data published since the original publication in 2003, 

and to describe toxicokinetics in humans. Three major modifications were described - the 

partition coefficients for glycidamide, the metabolic rate constants for oxidation and conjugation, 

and the partition coefficients for acrylamide. The simulations of the modified Kirman model 

were presented as tables containing comparisons of AUC data, and the extent of metabolism of 

acrylamide to glycidamide, and the extent of conjugation of each with glutathione. 

 However, the Panel had a number of concerns about the description of the model and its 

parameterization. The Panel believed that the documentation is not adequate to determine 

whether the recalibrated Kirman model is appropriate for its intended use. Among the items that 

the Panel would like to see to justify the performance of the model are: the model code; 

graphical presentation of the data for time course simulations; and graphical presentation of dose 

response simulated by the model. Side by side comparisons of the model parameters for the rat 

and human could be accomplished by combining Tables E-4 and E-6. 

29
 The Panel noted that the model with some changes has been described in a manuscript 

published in 2007 by Walker et al. If life stage considerations are planned for subsequent work, 

PBTK modeling is the recommended tool for dosimetry estimates across life stages. The Panel 

would like to see the model used to simulate or show the degree of consistency with data 

published since 2005. 

 The Panel also noted that there have been additional studies of acrylamide, its metabolites 

and adducts, with varying data quality, and varying understanding of exposures. For example, 

exposures in smokers are likely a composite of exposure from diet (oral) and smoke (inhalation). 

There are possible ambiguities in assignment of acrylamide and glycidamide metabolites (the 

acrylamide mercapturic acid sulfoxide and the glycidamide mercapturic acids are isomeric, and 

need to be resolved chromatographically for appropriate quantitation). The Panel suggests that 

EPA review these reports for data quality and suitability, and if appropriate use them in 

evaluation/refinement of the model. 

 The Panel noted discrepancies between the PBTK predicted and measured critical dose 

metrics for the non-cancer (acrylamide AUC) or cancer (glycidamide AUC) PODs following 

drinking water exposures in rats (see table below). 

EPA PBTK Model 

Predictions 

Tareke/Doerge 

Measured Data 

(2005, 2006) 

EGV 

BMDL 

(mg/kg/day) 

Critical 

Dose Metric Internal dose (uM-hr) Internal dose (uM-hr) 

RfD 0.27 AA_AUC 18.1 4.2 

oral 

cancer 

0.3 GA_AUC 15.1 4.7 

 The draft document notes that the data of Doerge et al. (2005 a,b) were available (page E5), but it is not clear if the data were actually considered in updating the model. 

30
 While the Panel concluded that the model structure was reasonable, the parameter 

estimates require greater justification. The review notes (Page E-18 last paragraph) that: “In 

comparing different versions of the model, it was also noted that the model parameters were 

underdetermined, that is, there is just not enough basic toxicokinetic data to derive a unique set 

of optimal parameter values, given the number of “adjustable” parameters in the current model.” 

 The Panel was concerned about the ability of the model to adequately simulate the 

kinetics of acrylamide and glycidamide. There is little justification presented for the adjustment 

of parameters from the original Kirman model. The method of optimization was not well 

described. The comparisons provided between observed data and model simulations are largely 

for AUC in tables. Thus it is difficult to determine how the model would perform under the kind 

of tests usually applied to a model, including the ability to fit kinetic data. Table E-4 indicates 

that while AUC for acrylamide and glycidamide can be simulated reasonably well with the 

revised rat model, and AM-GSH is reasonably close, the extent of metabolism to GA-GSH is 

overestimated by 3 fold by the model. Approximately 40% of the urinary metabolites were 

reported as GA-GSH (Fennell et al., 2005), but the model simulates that 70% would be derived 

from GA-GSH. 

 Table E-9 indicates that almost 50% of acrylamide is converted to glycidamide in 

humans. The data reported in Fennell et al. (2005) indicate approximately 13.5 % of the 

urinary metabolites were derived from glycidamide. Some recent studies indicate a higher degree 

of glycidamide formation from acrylamide, and substantial variation among individuals in this 

formation (Vesper et al. 2008; Hartmann et al. 2008). The model simulations are based on the 

assumption that all of the acrylamide not accounted for by excretion in urine by 24 hours is 

converted to glycidamide. As noted above, there are data not modeled that could greatly 

improve the model parameter estimates, using human urine kinetic data for acrylamide, 

glycidamide and urinary metabolites (e.g., Fennell et al. 2006; Hartmann et al. 2008;Vesper et 

al. 2006, 2008). Table E-7 cites the Ratio of GA-GSH to AA-GSH metabolite excretion at low 

doses reported by Boettcher et al. (2005) as 0.206 as a data point used for calibration. Yet the 

model simulation reports a value of 0.733 (Table E-9). The half-life estimated for acrylamide in 

the model is approximately 5.8 hours and the half-life estimated for glycidamide is 

approximately 6.1 hours. The half life calculated from urinary excretion rate for acrylamide in 

humans by Fennell et al. (2006), who studied small groups of healthy infertile adult men, was 

31
approximately half this, ranging from 3.13-3.49 hours. The issue of adjusting the parameters for 

partition coefficients and the rates of glutathione conjugation and oxidation is a serious one. It is 

possible to simulate the same AUC in blood with different model parameters, but with wildly 

different extents of metabolism and dose to the tissues for acrylamide or glycidamide, by 

adjusting partition coefficients, and metabolic rate constants. In other words, there may not be 

unique solutions unless the full body of reported data can be used in model verification. It is 

exceedingly important to carefully consider the extent of metabolism as a key piece of 

information in making parameter selections. 

 The description of the parameters and calibration for the human Kirman model are 

generally presented clearly on pages E-17 and E-18. A possible exception is the very general 

description of the “iterative process” that was used to evaluate physiologically feasible options to 

best fit the Fennell et al. (2005b) and Boettcher (2005) human data on adult adduct levels and 

urinary metabolites. A rough comparison of the final rat and human values suggests increased 

values for a number of tissue binding and metabolic parameters in the human model. Many of 

these parameters that changed from rat to human increased roughly by a factor of 2 with the 

exception of the Cytochrome P-450 oxidation rate that decreased by a factor of almost 2.1. It is 

not clear from the description of the iterative process used to calibrate these values whether the 

process was designed to force these parameters to move as groups or exactly what logic was 

employed to adjust these multiple parameters. The general logic behind the iterative testing of 

permutations of values could be clarified here without going into extreme detail. 

 An alternative approach that should be considered is a re-evaluation of the revised PBTK 

model of Kirman et al. (2003). Determining how well it simulates the more recent data and 

adjusting the metabolic parameters as necessary is one approach. The Panel had an extensive 

discussion as to whether the dose metric of area-under-the-curve (AUC) for acrylamide in the 

blood was the best choice based upon what is known about the mode of action for neurotoxicity 

and the available kinetic data. A variety of opinions were expressed, ranging from the assertion 

that AUC for acrylamide in blood was a suitable dose metric, to the belief that it may not the best 

choice, but may be expedient. The best choice would be to have compartments for the tissues of 

interest, and to model the amount of acrylamide and/or glycidamide reaching the tissues. The 

Kirman model and the modified Kirman model are both limited by the tissue descriptions: liver, 

lung, blood and a single compartment for remaining tissues. 

32
 There was extensive discussion among the Panel members about whether the 

neurotoxicity of acrylamide could clearly be attributed to acrylamide alone, to glycidamide, or to 

a mixed mode of action. This question was raised in the review document (Page 136, last full 

paragraph). Therefore the choice of acrylamide in blood as the dose metric may need to be 

revisited as this question is clarified. 

 Several alternatives to the PBTK model exist for making the estimates of internal dose in 

rats needed for both the non-cancer and cancer assessments and for calculating the Human 

Equivalent Dose (HED). The data available in Doerge et al. (2005) and Tareke et al. (2006) 

provide measured serum acrylamide and glycidamide AUCs in rats exposed at drinking water 

concentrations and resulting doses near the PODs. Simple linear extrapolation could be used to 

calculate the critical internal dose metrics. The hemoglobin adduct and other data available in 

several recent publications (Fennell et al. 2005; Vesper et al. 2006, 2008; Hartmann et al. 2008) 

together provide a robust means of estimating HEDs. The Panel also discussed the alternative 

approach of using pharmacokinetic principles to interpret measurements of hemoglobin adducts 

of acrylamide and glycidamide and thereby model glycidamide formation. 

The Panel also raised concerns about the population variability in the metabolism and 

toxicokinetics of acrylamide, and how that could be incorporated in the model. It was 

recognized that there are some high quality human data sets that could be used for PBTK model 

development (e.g. Fennell et al., 2005, 2006). However, there are limitations with the small 

number of selected subjects compared with the general population, in describing the population 

variation. The Panel has identified some studies that suggest variation in the extent of 

metabolism of acrylamide to glycidamide (Vesper et al. 2006, 2008; Hartmann et al. 2008), and 

differences in extent of conversion of acrylamide to glycidamide in children (Heudorf et al., 

2008). There is a need for a better understanding of exposure route differences, inter-individual 

variation and life stage differences in the metabolism of acrylamide to glycidamide, and their 

clearance. The Panel encourages an evaluation of the available literature, and if possible, 

simulation of human variability within the PBTK model. 

33
Charge Question 9.  Is the Young et al model adequately discussed relative to structure, 

parameter values and data sets used in the model? 

The Young et al. paper does not provide citations or values for many of its physiological 

model parameters. This is an unusual situation for a PBTK modeling paper. For chemical 

specific model parameter values, the authors fitted the chemical specific model parameter values 

for each administered dose, creating a model that is calibrated for each dose. This results in an 

unwieldy model for use in risk assessment. The preferred approach is to use all the administered 

dose groups and create a model with one set of chemical specific model parameters that 

describes all the toxicokinetic data sets. The model was based on the use of linear terms to 

describe chemical specific reactions (e.g., binding, DNA adducts, and metabolism). This 

approach may not hold (and non-linear terms will be needed) when developing one set of 

chemical specific model parameters to describe the kinetics over a range of doses. 

Do you agree with the conclusion that the recalibrated Kirman et al. 2003 model is the best for 

deriving toxicity values? 

 In the opinion of the Panel, the recalibrated Kirman model was superior to the Young et 

al. PBTK model. However, the Panel noted that the recalibrated model requires updating to 

include new data sets in the rat and human. The concerns described in Charge Question 8 need 

to be addressed to use the recalibrated Kirman et al. 2003 model. The Panel also noted that an 

approach to calculating internal doses at the non-cancer and cancer PODs is available that relies 

on measured data (and minimal linear extrapolation in a dose range that has been shown to be 

linear) instead of the PBTK model. This approach also affords the ability to calculate the HED 

corresponding with the critical internal dose metrics associated with the PODs (see response to 

question 8). If life stages are considered, the PBTK modeling or another pharmacokinetic 

approach is the preferred approach for determining a HED or HEC. 

Charge Question 10.  According to US EPA’s RfC Methodology (1994), the use of PBTK 

models is assumed to account for uncertainty associated with the toxicokinetic component of 

the interspecies uncertainty factor across routes of administration. Does the use of the PBTK 

34
model for acrylamide objectively predict internal dose differences between the F344 rat and 

humans, is the use of the model scientifically justified, and does the use of the PBTK reduce 

the overall uncertainty in this estimate compared to the use of the default factor? Are there 

sufficient scientific data and support for use of this PBTK model to estimate interspecies 

toxicokinetic differences and to replace the default interspecies factor for toxicokinetic 

differences (i.e., 101/2)? Is the remaining uncertainty factor for toxicodynamic differences 

scientifically justified, appropriate and correctly used? 

 The Panel commends EPA for using the PBTK model for developing the RfD, RfC and 

Cancer Slope Factors for acrylamide. The kinetics of acrylamide are well characterized and thus 

the use of internal dose metrics that are thought to represent the critical dose metrics for noncancer (neurotoxicity) and cancer (various tumor types) is a preferred approach for extrapolating 

across species. The Panel agrees that the use of internal dose metrics (calculated using the 

PBTK model or other pharmacokinetic approaches alluded to above) combined with a fairly 

robust understanding of the mechanism of action and thus the critical dose metric replaces the 

use of the default interspecies factor for toxicokinetic differences (i.e., 101/2). 

 The Panel agreed with the use of the remaining UFs representing interspecies differences 

in toxicodynamics and intraspecies variability in both toxicokinetics and toxicodynamics. 

Charge Question 11.  Please comment on whether the PBTK model is adequate for use to 

conduct a route-to-route extrapolation for acrylamide to derive an RfC in the absence of 

adequate inhalation animal or human dose-response data to derive the RfC directly. Was the 

extrapolation correctly performed and sufficiently well documented? 

 The Panel discussed the lack of inhalation toxicology and PK studies. One Panel 

member who has conducted inhalation PK exposure studies noted the difficulty with conducting 

controlled rodent exposure studies and the difficulty in maintaining stable exposure 

concentrations because of the low volatility of acrylamide and its propensity to sublime. The 

Panel agreed with the use of PBTK modeling to conduct dose-route extrapolation. Additionally, 

the Panel commends the EPA for using the PBTK model to fill the gap resulting from the 

absence of robust animal toxicology studies investigating neurotoxicity via the inhalation route 

35
that would support the development of an RfC. The Panel agreed that the absence of evidence 

for route of entry specific effects would allow route-to-route extrapolation for deriving an RfC 

by using the PBTK model to calculate the human equivalent concentration (HEC). This would 

yield an equivalent internal dose (Acrylamide AUC) associated with those achieved at the POD 

from the oral sentinel (Johnson et al.) studies. The Panel noted that few inhalation PK studies 

exist to allow a robust parameterization of the inhalation component of the PBTK model for 

either rats or humans. Despite this, the Panel noted that acrylamide is very water soluble and 

non-volatile, and the compound has a relatively long half-life. Therefore, the absorption of 

acrylamide via inhalation should be nearly complete, and first pass effects are negligible, thereby 

making the pharmacokinetics of acrylamide via inhalation easy to extrapolate from the oral case, 

using simple principles of pharmacokinetics. The Panel agreed that the application of 

pharmacokinetic approaches (e.g,. the use of the PBTK model) reduces uncertainty associated 

with animal to human extrapolation and thus warrants replacing the default UF associated with 

interspecies extrapolation for pharmacokinetic differences as was done for deriving the RfD. 

 The Panel noted that the air concentration one would derive using the default approach 

(multiply the HED by body weight [70 kg] and dividing by daily inhalation rate [20 m3

/day] 

yielding 0.266 μg/m3

) is very similar to the HEC derived using the PBTK model (0.25 μg/m3). 

Therefore, if the EPA also decides to provide an extrapolation based on measured data (as 

described in the response to charge question 8), the default approach of extrapolating from an 

absorbed oral dose to an equivalent intake from the inhalation route (multiplying by 70 kg and 

dividing by 20 m3

/day) can be used with confidence to calculate the RfC. 

Charge Question 12. Please provide any other comments on the derivation of the RfC and on 

the discussion of uncertainties in the RfC. 

 The Panel has no further comments beyond those already discussed above. 

Charge Question 13. Would you suggest that EPA include a Table that lists points of 

departure (e.g., NOAELs, BMDs, etc.) for various endpoints that could be used, in 

conjunction with exposure assessments, to conduct a MOE analysis? 

36
 To the extent permitted by the available data, the Panel supports the concept of the 

inclusion of a table in the IRIS acrylamide document that provides information which could be 

used to conduct a variety of MOE analyses for specific endpoints of interest and/or for other than 

lifetime durations of exposure, in addition to the traditional lifetime focus. In doing so the 

magnitude of the MOE that represents a negligible risk should be reported for each point of 

departure tabulated. 

 Currently, for those environmental agents for which sufficient data exist, IRIS documents 

will present the derivation of a Reference Dose (RfD) and a Reference Concentration (RfC), as 

traditionally defined, to be used in the assessment of scenarios which assume that long-term or 

lifetime exposures are occurring to non-carcinogenic hazards. Additionally, in those cases where 

the agent of interest has been shown to have carcinogenic potential, an oral cancer slope factor 

(CSF) and/or an inhalation unit risk (IUR) may be derived, in order to estimate lifetime cancer 

risks. Whether or not this step is included is determined by a weight-of-evidence evaluation of 

the body of evidence supporting carcinogenic potential and an understanding, or lack thereof, of 

the mode(s) of action by which the carcinogenic responses are mediated. These four values (the 

RfD, RfC, CSF and IUR) are applicable in situations where the assessment is focused on the 

general population exposed over a lifetime, and may have more limited utility in the assessment 

of specific subpopulations and/or less-than-lifetime exposure durations. 

 EPA Program and Regional offices and other end-users of IRIS documents often must 

develop risk assessments for specific populations and/or less-than-lifetime exposure scenarios in 

order to carry out their respective legislative and regulatory mandates. These risk assessments 

would benefit from the inclusion of transparently-developed, peer-reviewed consensus hazard 

values. 

 A comprehensive table would, for example, include NOAELs, LOAELs, BMDs and 

BMDLs at the 1%, 5% and 10% risk levels (as the default) for those studies deemed the most 

appropriate for the assessment of specific endpoints and for acute, intermediate and long-term 

exposure scenarios, data permitting. It is recognized that it will typically not be possible to fill in 

every cell for every endpoint and all exposure durations of interest and that a different 

BMDR/BMDLR may better reflect the study’s results. Some EPA program offices have extensive 

experience in the selection of study types and durations that best lend themselves to the 

assessment of specific endpoints, exposure durations and subpopulations. 

37
 For this draft acrylamide assessment, such a table would display the relevant outcomes of 

a review of the reliable and well-performed studies which evaluated the potential for 

neurotoxicity in the adult and developing organism, reproductive toxicity including heritable 

germ effects, developmental toxicity, and general systemic toxicity following acute, intermediate 

and long-term exposure, as appropriate. 

Charge Question 14. Please comment on the discussion of methods to quantitate the doseresponse for heritable germ cell effects as to whether it is appropriate, clear and objective, and 

reflective of the current science. Has the uncertainty in the quantitative characterization of 

the heritable germ cell effects been accurately and objectively described? 

[It should be noted that the section under review is 5.5 rather than 5.4. In addition, page 215 

which includes figures 5-2 and 5-2a, was inadvertently omitted in the draft EPA report and thus 

not available for review by the Panel. Correction of this error, however, is not expected to 

impact the recommendations of the Panel on this question as outlined below.] 

Although reservations were expressed about the lack of data to quantify dose-response, it 

was the consensus of the Panel that the discussion of the methods should be retained in the 

report. The report adequately characterizes the current science, reflects historical attempts to 

estimate these risks and notes that the quantitation methods are based only on the Dearfield et al.

(1995) publication. Concerns about the validity of the data and methods are given throughout 

the section and it is appropriately noted on page 217, “ these uncertainties in the assumptions and 

data gaps warrant further research to improve the usefulness of the following quantitative 

estimates of risk of acrylamide-induced heritable effects.” 

 Some specific observations/recommendations/concerns are outlined below: 

• The parallelogram models were clearly described and the rationale for the decision to use 

the modified direct and doubling dose approach appears appropriate. 

• Clearly, there is considerable uncertainty regarding the validity of the underlying 

assumptions for these methods, and these methods may underestimate risk since they do not take 

into account all elements that may contribute to the risk. 

• The extrapolation of exposure is based on animal studies using high dosages (50 to 100 

mg/kg or even higher) 

38
• The risk extrapolation factors (REFs; pg. 217) should be explained in more detail and 

information included on how each number is derived (range, etc). 

• In agreement with the report, given the differences in glycidamide production in different 

species, an REF of 1 for the metabolic and dose rate variability is likely incorrect. There appear 

to be significant dose-rate and species-dependent variations in acrylamide metabolism to 

glycidamide (e.g., see Barber et al., 2001; Fennell and Friedman, 2005). 

• An REF for uncertainty in the mode of action was recommended since the doubling dose 

is dramatically higher when generated using specific locus studies which are clearly point 

mutations (53.1 mg/kg using Ehling and Neuhauser-Klaus, 1992) versus using heritable 

translocation data that could be based on clastogenic mechanisms (1.8, 3.3, 0.39 mg/kg for 

Shelby et al., 1987, Adler et al., 1994 and Adler, 1990). 

• The implementation of the modified direct approach was difficult to understand when, in 

the absence of the number of human loci capable of mutating to dominantly expressed disease 

alleles, it was assumed to be 1000. Clarification of how this number was derived would be 

helpful (i.e. how do we know the number of mutable genes?). 

• In the doubling dose approach it was not clear how the four data sets, each of which used 

high acrylamide dosing rates without significant dose ranges, could accurately predict the 

number of new diseases in the offspring at low doses. 

Lack of current research in this area is a major concern and little has been done to update the 

research and data collection based on the Dearfield et al. (1995) methods. The Panel is in 

agreement with the report that recommends further research and data to fill the critical data gaps 

and reduce uncertainties including gaps in interspecies extrapolation factors, the quantitative 

relationship between genetic alterations in germ cells and heritable disease, and the shape of the 

low-dose response relationship. Research might include multiple dose studies, including dose 

selection comparable to that employed in the repeated dose studies which identified 

neurotoxicity as a critical effect. It is also recommended that impacts on different cell types be 

determined and that biomonitoring data be utilized in any models developed. 

Charge Question 15. Please comment on the scientific support for the hypothesis that 

heritable germ cell effects are likely to occur at doses lower than those for neurotoxicity? 

What on-going or future research might help resolve this issue? 

39
 

 The Panel unanimously agreed that germ cell-induced effects should be taken very 

seriously, as their implications are highly significant from a public health perspective. There is 

an absence of data on these effects in lower dose ranges, making it very difficult to speculate 

about the relevance of this endpoint at or below the dose levels that cause neurotoxicity. 

Panelists did point out that heritable translocations appeared with very high frequency at the 

lowest doses tested (i.e., 5 x 40 mg/kg resulted in 24% translocation carriers, Shelby et al., 

1987). The high frequency of germ cell effects at these doses implies that these studies were far 

from identifying a LOAEL or NOAEL, and that there would likely be germ cell effects at much 

lower doses. However, the combination of lack of testing at lower doses, and the narrow dose 

range in which testing has been done, makes it very difficult to extrapolate down to a low dose 

range. The Panel agreed that it is a high priority to extend the heritable translocation studies 

down into lower dose ranges, and that this information would be very useful for risk assessment 

once it is completed. 

Charge Question 16. The risks of heritable germ cell effects (i.e., number of induced genetic 

diseases per million offspring) for some estimated exposure in workers and the population are 

presented in Table 5-11, and are based on the quantitative methods and parameter estimates 

discussed in Section 5.4 of the Toxicological Review. Please comment on whether or not the 

quantitation of heritable germ effects should be conducted, the level of uncertainty in the 

results, if Table 5-11 is useful for risk assessment purposes, and if the RfD should be included 

in the Table as one of the exposure levels. 

 The Panel supports the Agency’s conclusions that exposure to acrylamide in animals 

leads to heritable gene mutations and that these results indicate that it may also pose a hazard to 

humans. In addition, the Panel supports the Agency’s conclusions that the available data are not 

adequate to conduct a robust assessment of this endpoint at this time. 

 The Panel’s deliberations regarding quantifying heritable germ cell mutations centered on 

the importance of including data such as those presented in Table 5-14 (not Table 5-11, as noted 

in the final question), the potential significance of these endpoints to human risk assessment, and 

the paucity of new data developed since the Dearfield et al. (1995) review upon which this 

40
section relied heavily (including Table 5-14). A majority of Panel members were supportive of 

the inclusion of this table in the document and for including the RfD and RfC among the 

concentrations in the table as this would facilitate comparison with the neurological endpoints. 

Suggestions also included adding more information into the review regarding the role of CYP 

2E1 in the dominant lethal effects of acrylamide, which indicated a requirement for metabolism 

to glycidamide. While the caveats from the Dearfield et al. (1995) review were recapitulated in 

the document, the Panel discussed the need to further elaborate the limitations in the underlying 

data and to include reference to the new relevant studies that pertain to uncertainty and doseresponse. 

Charge Question 17.  Do you know of any additional data or analyses that would improve the 

quantitative characterization of the dose-response for acrylamide-induced heritable germ cell 

effects? Would these data also support the quantitative characterization of “total” malemediated reproduction risks to offspring (i.e., lethality + heritable defect)? If data are not 

available, do you have any recommendations for specific needed studies? 

 A concern raised by the Panel was that there is a lack of a suitable data set for dose 

response assessment for acrylamide-induced heritable germ cell effects. The majority of the 

studies reported have been conducted in mice, using relatively high doses. 

 Using wild type and Cyp 2E1 knockout mice, it has been demonstrated that oxidation of 

acrylamide to glycidamide is required for the dominant lethal effect (Ghanayem et al., 2005a) 

and for the induction of erythrocyte micronuclei and DNA strand breaks in lymphocytes, liver 

and lung using the Comet assay (Ghanayem et al., 2005b). The greater incidence of heritable 

translocation carriers in mice administered glycidamide (Generoso et al., 1996) compared with 

acrylamide (Adler et al., 1994) suggests that glycidamide plays a key role in the mode of action 

for heritable genetic effects. 

 The risk equivalent factors (REFs, page 217) need to be updated. There are profound 

differences between rats, mice and humans in the extent of metabolism of acrylamide to 

glycidamide, and the relative internal dose of acrylamide and glycidamide differs markedly 

between mice, rats and humans. The extension of the physiologically-based pharmacokinetic 

modeling approach to include the mouse should be a priority. The blood-testis barrier is thought 

41
to contribute to the reduction of internal dose in the testis compared with other tissues for 

ethylene oxide (Fennell et al., 2001). Testis should be included as a compartment in the model. 

Data permitting, including the testis as a compartment in the model could potentially improve the 

dose response characterization for this endpoint. 

 In reviewing data needs (page 220), it is noted that “The estimates do not take into 

account other potential genotoxic mechanisms such as effects in spermatogonia stem cells, 

effects in female germ cells, or induction of recessive mutations that would not appear in the first 

generation, but could lead to additional adverse effects in subsequent generations.” Studies to 

examine the dose response for heritable genetic effects, and the effect of long-term exposure to 

acrylamide are needed. 

 There is still uncertainty about the mode of action of acrylamide and glycidamide in the 

induction of heritable genetic effects. The potential for DNA adducts of glycidamide to play a 

role is an attractive hypothesis for the mode of action. With respect to the possible role for 

protamine modification in the generation of effects, there was extensive Panel discussion 

concerning the potential of glycidamide to form adducts with cysteine in proteins and peptides. 

Adducts to protamine from acrylamide have been identified in late stage spermatids and 

suggested to mediate the dominant lethal effects (Sega et al., 1989). Whether glycidamide will 

form similar protamine adducts has not been determined. Kinesin motor proteins associated with 

cell division are an additional site of potential action leading to heritable germ defects (Sickles et 

al., 2007) that requires future consideration. Both AA and GA inhibit two kinesin motors 

associated with spindle formation and maintenance as well as separation of chromosomes. Loss 

of fidelity of chromosomal separation is related to aneuploidy, micronuclei formation and 

instability of the genome. The motor protein inhibitions occur at concentrations well below the 

occurrence of all heritable germ cell effects. Furthermore, glycidamide is more potent than 

acrylamide. Surveying populations occupationally exposed to acrylamide in manufacturing 

plants was suggested as an approach for evaluation in humans. 

 

Charge Question 18. Have the rationale and justification for the cancer designation for 

acrylamide been clearly described? Is the conclusion that acrylamide is a likely human 

carcinogen scientifically supportable? 

42
 Yes, the rationale and justification have been clearly described, although it should be 

further expanded (see below), and the conclusion is scientifically supportable. Acrylamide is 

clearly and reproducibly carcinogenic in both rats and mice. As outlined in the draft document, it 

produced tumors at multiple sites in the rat in multiple chronic studies, and was a skin tumor 

initiator in mice by multiple routes. Therefore, in accordance with EPA’s cancer guidelines, it is 

consistent with the “likely human carcinogen” cancer descriptor. 

 To paraphrase the International Agency for Research on Cancer (IARC) Monographs 

Preamble, in the absence of tumor data in humans it is both reasonable and prudent to regard 

evidence of carcinogenicity in experimental animals as evidence for a probable cancer hazard to 

humans. This conclusion is consistent with both national and international guidelines for 

carcinogenic hazard identification. The U.S. National Toxicology Program (NTP) has long 

emphasized that chemicals that cause tumors at multiple sites or in more than a single species are 

reasonably anticipated to be human carcinogens. Both the NTP and IARC have placed 

acrylamide in cancer classifications similar to that of EPA’s “likely human carcinogen” (This 

could be noted in the Toxicological Review). 

 When experimental exposure of rats or mice to known human carcinogens is via diet or 

drinking water, tumor sites observed in those species do not necessarily correspond to the same 

tumor sites in humans. Exposure to chemicals that cause tumors of the mammary gland or the 

liver in mice or rats, for example, does not necessarily correspond to increased cancer risk 

specifically for female breast or liver in humans. The essential point to be considered is that in 

any given case a tumor at these or any other site(s) results from an MOA known to operate in 

humans, such as somatic cell mutagenicity. 

 Primary CNS tumors as a group, which are discussed at considerable length in the draft 

document, should be restored to the list of experimental tumors produced by acrylamide and that 

are of interest for the MOA discussion. The Panel cautions that the viruses that can cause 

primary CNS tumors in hamsters and other non-human species are not relevant to this 

discussion. 

 It should be emphasized that the spectrum of tumors consistently seen in acrylamideexposed rats is completely consistent with a DNA-reactive MOA, based on published data about 

other substances that induce or initiate the same kinds of neoplasms. The only agents known 

conclusively to induce tumors of the brain and peritesticular mesothelium in rats are all DNA43
reactive, and in fact a single exposure to a direct-acting mutagenic carcinogen has been observed 

to suffice for tumor induction at either site. The concept that acrylamide acts by a mutagenic 

MOA is thus supported by the spectrum of acrylamide-associated tumors that occur in exposed 

rats and mice, as well as by the biotransformation pathway of acrylamide in vivo. 

 Tumor initiation – promotion data for mouse skin are perhaps not sufficiently emphasized 

in the draft document. First, only DNA-reactive chemicals or chemicals biotransformed to 

DNA-reactive metabolites are established tumor initiators. As acrylamide is an initiator, and by 

multiple routes of administration, it is a permissible inference that acrylamide is also acting by a 

DNA-reactive MOA in mouse skin, as do other initiators. It is most striking that, in mice, 

systemic exposure to acrylamide is more effective for skin tumor initiation than direct 

application to the skin. The order of efficiency, oral > ip > dermal application, for initiation of 

TPA-promotable squamous cell papillomas and carcinomas on mouse skin strongly supports the 

importance of systemic exposure and post-hepatic distribution of a reactive metabolite in the 

MOA for carcinogenicity at this site. 

Charge Question 19. Do you agree that weight of the available evidence supports a 

mutagenic mode of carcinogenic action, primarily for the acrylamide epoxide metabolite, 

glycidamide (GA)? Has the rationale for this MOA been clearly and objectively presented, 

and is it reflective of the current science? 

 A sound rationale and justification already supports the mutagenic mode of action 

(MOA), and this evidence is further supported by additional new data as described below. The 

weight of evidence supports a mutagenic MOA, and overall the rationale for this MOA has been 

clearly and objectively presented. Some improvements to the presentation are as follows. The 

discussion of biological plausibility and coherence could be expanded beyond DNA adducts and 

the human relevance section could be somewhat more expansive without being repetitive. The 

argument on page 145 regarding the lack of relationship of cytogenetic damage to a mutagenic 

MOA should be carefully re-considered, as the literature is full of these correlations. Evidence 

for and against the arguments set out should be carefully evaluated, and much better referencing 

included. Reports from Bonassi and Hagmar are cited as supportive, yet contradictory findings 

44
from the same authors supporting an alternative argument could just as easily have been cited. 

The discussion includes strong generalizations that may not hold up to close scrutiny. 

 There has been one published study to date that has examined biomarkers of acrylamide 

exposure and human cancer risk. Olesen et al. (2008) characterized hemoglobin adducts of 

acrylamide and glycidamide in a case-control study of post-menopausal breast cancer. The 

authors found no association between levels of glycidamide hemoglobin adducts and breast 

cancer risk. Moreover, they found no overall association between acrylamide adducts and risk. 

Upon adjustment for smoking status, however, they observed a 2.7-fold (1.1-6.6) increased risk 

restricted to ER+ breast cancer per 10-fold increase in acrylamide-hemoglobin level. With 

respect to this study design, the authors did not match or restrict the cases and controls on 

smoking status, which raises concern given the very strong link between smoking and 

acrylamide adducts. Interpretability of the Olesen study with respect to supporting the mode of 

carcinogenic action should be taken cautiously. 

 For very high levels of acrylamide exposure, the animal and other experimental data do 

support a mutagenic effect of acrylamide. It has been questioned whether such a mechanism 

might also apply to lower doses (and indeed, at the lowest doses to which humans are exposed), 

because of uncertainty about whether the compensatory mechanisms are in place to detoxify 

acrylamide. But data clearly indicate that glycidamide is formed. There are the consistent 

observations in humans of glycidamide-hemoglobin adducts (Bjellaas et al., 2007; Chevolleau et 

al., 2007; Vesper et al., 2006, 2007) or glycidamide urinary metabolites (Urban et al., 2006) , 

including children (Heudorf et al. 2008), thus demonstrating the widespread internal exposure to 

the putative mutagenic metabolite of acrylamide at ongoing low levels of exposure in the general 

population. 

 The Panel did not consider the carcinogenicity to be hormonally-related. The existing 

short-term mouse studies in SENCAR, ICR (skin) and A/J (lung) show no such selectivity of 

carcinogenicity for hormonally regulated tissues. Also, the Panel discussed the fact 

acrylamide/glycidamide is not unique among DNA-reactive epoxides for carcinogenic action in 

thyroid, peritesticular mesothelium, and mammary tissue (e.g., glycidol, ethylene oxide). In 

addition, this argument does not consider the CNS tumors observed in both chronic acrylamide 

cancer bioassays, a site that was discussed by the Panel as representing strong evidence for a 

DNA-damaging mechanism (cf. Rice, 2005). Finally, a recent publication considered by the 

45
Panel of short-term exposures to high doses of acrylamide in male F344 rats found essentially no 

evidence for hormonal dysregulation in the hypothalamus-pituitary-thyroid axis based on 

measurements of gene expression, neurotransmitters, hormones, and histopathology (Bowyer et 

al., 2008). Some studies of chronic low dose exposure, such as the cohort study of acrylamide 

and ovarian/endometrial cancers (Hogervorst et al., 2007) and others (Khan et al., 1999) have 

shown positive associations with hormones. The Panel encourages the Agency to review all 

relevant new data that has been published since their completion of the current draft assessment 

as they revise and finalize this IRIS document. 

Charge Question 20. Are there other MOAs that should be considered? Is there significant 

biological support for alternative MOAs for tumor formation, or for alternative MOAs to be 

considered to occur in conjunction with a mutagenic MOA? Please specifically comment on 

the support for hormonal pathway disruption. Are data available on alternate MOAs sufficient 

to quantitate a dose-response relationship? 

 No, there is not significant biological support for MOA alternatives to the mutagenic 

MOA, and data on any putative alternate MOAs are not sufficient to quantify dose response 

relationships. It must be emphasized that more than one MOA may operate for a given 

carcinogenic chemical, and the likelihood that more than a single MOA is operative increases as 

levels of exposure increase. Some well-documented non-DNA reactive MOAs appear to be 

high-dose phenomena. These are often important for understanding bioassay results in 

experimental animals, and sometimes for high-exposure situations in human experience, but they 

are usually less important because they represent negligible risks when cumulative human 

exposures to these and similarly acting compounds fall considerably below bioassay dosage 

levels. MOAs that can occur both in experimental rodents and in humans and that operate both 

at bioassay dosage levels in experimental animals and at lower levels as well, into the human 

exposure range, are most significant for humans. In general, for chemicals such as acrylamide 

where there is a compelling body of data to support a DNA-reactive MOA via biotransformation 

to glycidamide, the evidence for alternative or additional high-dose MOAs would have to be 

convincing to explore alternative approaches to dose response and risk assessment. One caveat 

that should be mentioned is that mutations induced by acrylamide are observed following high 

46
doses. There are similarly acting agents, such as methylmethanesulfonate (MMS) that create N7-

Guanine, the same DNA adducts, as does glycidamide yet show a threshold for mutations. These 

data are consistent with robust repair mechanisms for the specific type of DNA adducts produced 

by glycidamide and MMS. However, it should also be noted that low dose exposures have not 

been tested in animal mutation studies and NOAELs have not yet been established. Therefore 

future research should include dose response analyses to stringently test the relationship between 

DNA adducts and mutations and gain a better understanding of the effects at lower doses. The 

Agency should mention the finding of inhibition of kinesin motor proteins as a newly-identified 

and potential site of action of AA or GA in the production of carcinogenicity (Sickles et al., 

2007). 

 Occasionally high-dose or “unique rodent-specific” MOAs may be invoked or postulated 

to discredit bioassay results as irrelevant to humans, especially when such putative MOAs are 

observed uniquely in non-human species. Such a postulated MOA needs to be very precisely 

defined and its relevance thoroughly investigated and critically tested before the postulated MOA 

is accepted by the biomedical and risk assessment communities. Any MOA developed for a 

single substance is at best speculative until a general pattern can be rigorously demonstrated for a 

family of substances that operate via the same MOA. The hormonal disruption MOAs proposed 

for acrylamide as tissue-specific alternatives to a DNA-reactive MOA are highly speculative, are 

supported by at most limited evidence, and do not meet this standard as noted in response to 

charge question 19. The data are insufficient for characterizing dose-response relationships for 

any of these proposed alternatives. 

Charge Question 21. Two chronic drinking water exposure bioassays in Fischer 344 rats 

(Friedman et al., 1995; Johnson et al., 1986) were used to derive the oral slope factor, and to 

identify the tumors of interest for the MOA discussion. Are the choices for the studies, 

tumors, and methods to quantify risk transparent, objective, and reflective of the current 

science? Do you have any suggestions that would improve the presentation or further reduce 

the uncertainty in the derived values? 

 The two chronic bioassay studies in F344 rats are the main studies to consider in dose 

response analysis. Overall the document does a good job discussing these studies, but the 

47
rationale for using only the Friedman et al. study for derivation of the oral slope factor is 

problematic. The strengths and limitations of both studies should be discussed in greater depth. 

The text describes the Friedman et al. study as “superior” and “larger and better designed” but 

the Panel does not agree that this is the case, and recommends that both studies be subjected to 

modeling for the purposes of deriving oral slope factors. The two studies may have fairly 

similar oral slope factors. At a minimum, estimates for the second study should also be presented 

to clarify the impact of study selection in the uncertainty discussion. 

 The methods to quantify risk are transparently presented and reflective of current science, 

with the exception that a factor to scale for pharmacodynamic differences in potency between 

humans and animals has not been applied. The development of unit risk based on HEC accounts 

for the pharmacokinetic but not pharmacodynamic differences, and in such situations EPA’s 

2005 Guidelines for Carcinogen Risk Assessment (p. 3-7) indicates inclusion of a 

pharmacodynamic factor be considered. The potential human variability in cancer response 

attributable to human pharmacokinetic variability in handling acrylamide should be discussed 

qualitatively and analyzed quantitatively. Hemoglobin adduct data could provide the basis for 

such an analysis. The assumption underlying the modeling, that each and every individual of 

the same age exposed to the same external dose faces the same risk of cancer, is inconsistent 

with these data. 

 With respect to study selection, one of the reasons for not using the Johnson study had to 

do with the rates of CNS tumors in this study, particularly in the controls. The Friedman et al.

study was designed “to investigate whether glial tumors in the Johnson et al. study were 

significant.” But, as Rice (2005) points out, the histopathological examination for glial tumors 

was incomplete. Only one-fifth of the 1.0 mg/kg-day dose females’ spinal cords were subjected 

to histopathological examination, even though one-third of the glial tumors in the Johnson et al.

study were seen in the spinal cord. The approach to the evaluation of CNS tumors in Friedman et 

al. was seen by the Panel as a significant study limitation. 

 Another improvement over the Johnson study noted in the document for the Friedman et 

al. study was different and presumably better dose intervals. The doses for males in the 

Friedman et al. and Johnson et al. studies were the same, except Johnson et al. had one 

additional lower dose group. The doses in Friedman for females were 1.0 and 3.0 mg/kg-day 

compared to 0.01, 0.1, 0.5 and 2.0 mg/kg-day for the Johnson study. The Friedman study did 

48
extend the high end of the dose response range for females and did offer a more complete dose 

response function for thyroid tumors, employed somewhat larger dose groups (100 per group and 

two control groups). But Johnson et al. did have 60 animals per dose group, did provide a 

complete histopathological evaluation, and had more dose groups than a standard bioassay. 

 Another limitation of the Friedman et al. study is that the degree of histopathological 

examination of oral tissue is unclear. The Friedman study does not tabulate findings for certain 

tumor sites seen in the Johnson study, so quantitative comparisons are not possible and the reader 

is not able to consider these sites or perform independent evaluations regarding the significance 

of the findings. It appears EPA may have the data needed to do the analysis since it was able to 

do a time-dependent analysis for slope estimation using the Tegeris Lab report. EPA could then 

look at the data and analyze as appropriate the data for these sites. 

 A criticism about the possible impact of a sialodacryoadenitis virus on tumor findings 

had been raised and was another reason given for using the Friedman study. On the other hand, 

US FDA had raised some issues in auditing the Friedman et al. study regarding environmental 

controls at the lab facility and the possibility of some under-dosing of animals. Ultimately both 

studies have strengths and weaknesses and on balance neither seems clearly superior. Both are 

reasonably strong studies, and thus oral slope estimates should be presented for both studies. 

 Some comments regarding details on tumor data presentation and analysis in the EPA 

draft document follow: 

 Tests for dose-related trends should be conducted and presented for the all tabulated sites. 

By Fisher’s exact test, the mammary tumors in the 0.5 mg/kg-d group in the Friedman et al.

study are significant (p<0.05). The statistics used in the draft document that correct for 

intercurrent mortality should be re-checked. It appears this group has a treatment-related finding 

and this should be noted and the discussion that this group is devoid of treatment-related tumors 

(page 75) changed. The clitoral gland findings in the Johnson et al. study stand out because 

histology was done only on clitoral tissues observed with gross masses. This is worth an 

explanatory footnote. Also given the approach taken to collecting this tissue, the clitoral tumors 

in the 0.5 mg/kg dose group also appear worthy of note. All four masses analyzed indicated 

tumor compared to none in controls (p<0.1). In the Friedman et al. study, CNS tumors of glial 

origin should be combined for analysis as was done by WHO 2006. Considering the findings of 

glial tumors in females in the Johnson study, the dose related trend for both sexes in the 

49
Friedman study, although falling a hair short of statistical significance at the p < 0.05 level, 

provide some evidence of a CNS glial cell effect in the Friedman study. This should be 

discussed. Also, the extent of examination of oral tissue in the Friedman study is unclear. 

Finally, the Friedman study employed two control groups for the male rats that do not differ 

from one another. For the statistical treatments, there is no apparent reason why these groups 

should not be combined. The Toxicological Review did this for the dose response analysis but 

may not have done the same for the pair-wise comparisons. 

 The data choice for modeling to address the discrepancy between the Friedman et al. and 

the Tegeris laboratory reporting of thyroid tumors for the male noted in Appendix D of EPA’s 

draft document was appropriate. A final minor point, in the discussion of the confidence in dose 

response analysis in chapter 6 (page 229), issues are raised that seem better placed in the 

discussion of the hazard characterization. 

Charge Question 22. The cancer slope factor (CSF) derivation includes an adjustment for 

early mortality (i.e., time-to-tumor analysis). Is this adjustment scientifically supported in 

estimating the risk from the 2-year bioassay data for increased incidence of tumors in the 

rats? 

 The use of the Weibull-in-time multistage-in-dose analysis is a reasonable and 

scientifically justifiable way to take into account the early mortality in the high dose group in the 

male study. The decision not to employ this analysis in the case of the females is also reasonable 

since mortality across treatment and control groups did not differ and the overall survival appears 

to be fairly good. 

Charge Question 23. Please comment on whether AUC for glycidamide is the best choice of 

the dose metric in estimating human equivalent concentration to derive the oral slope factor.

 The Panel agreed that using the AUC for glycidamide is the best choice for estimating the 

human equivalent concentration to derive the oral slope factor. This decision was based on the 

strong evidence from experimental results that the AUC was linearly correlated with adduct 

levels in single/repeat dosing studies. There was agreement that glycidamide is the more 

50
mutagenic metabolite based on experimental studies. The Panel felt there was good 

documentation in the report regarding the correlation between levels of DNA adducts and extent 

of mutations in vivo. Moreover, the metabolic conversion of acrylamide to glycidamide supports 

the MOA. 

 One consideration in using this as the dose metric, however, comes from some of the 

human studies in which variability is not accounted for adequately, specifically, inter-individual 

variation is not assessed and that the value used for cross-species comparisons is based on small 

numbers of healthy adult male humans. This is discussed at greater length in response to 

Question 8. Consideration of additional human data (e.g., Vesper et al., 2006) to evaluate the 

degree humans form glycidamide from acrylamide is clearly warranted. Such data may provide 

the basis for comparing human acrylamide and glycidamide AUCs, using methodology of 

Calleman, Bergmark and colleagues (Bergman et al., 1991). This in turn can provide an 

improved basis for adjustments for cross-species differences in pharmacokinetics, as well as 

human variability in glycidamide formation from acrylamide. 

Charge Question 24. As with the RfC, there were insufficient cancer inhalation data to derive 

an inhalation unit risk (IUR). The PBTK model was used in a route-to-route extrapolation of 

the dose-response relationship from the oral data, and to estimate the human equivalent 

concentration for inhalation exposure to acrylamide. Please comment on whether this 

extrapolation to derive the inhalation unit risk was correctly performed and sufficiently well 

documented. 

 The response to this question is nearly identical to the response to charge question #11. 

The Panel agreed with the use of PBTK modeling to conduct dose-route extrapolation and 

commended the EPA for using the PBTK model to fill the gap resulting from the absence of 

robust animal toxicology studies investigating neurotoxicity via the inhalation route that would 

support the development of an IUR. The Panel agreed that the absence of evidence for route of 

entry specific effects would allow route-to-route extrapolation for deriving an IUR based on 

using the PBTK model to calculate the human equivalent concentration (HEC). This would yield 

an equivalent internal dose (Glycidamide- AUC) associated with those achieved at the point of 

departure from the oral sentinel (Johnson et al.) studies. The Panel noted that few inhalation PK 

51
studies exist to allow a robust parameterization of the inhalation component of the PBTK model 

for either rats or humans. Despite this, the Panel noted that acrylamide is very water soluble and 

non-volatile, and the compound has a relatively long half life. Therefore, the absorption of 

acryalmide via inhalation should be nearly complete, and first pass effects are negligible, thereby 

making the pharmacokinetics of acrylamide via inhalation easy to extrapolate from simple 

principles of pharmacokinetics. The Panel agreed that the application of pharmacokinetic 

approaches (e.g,, the use of the PBTK model) reduces uncertainty associated with animal to 

human extrapolation and thus warrants replacing the default uncertainty factor associated with 

interspecies extrapolation for pharmacokinetic differences as was done for deriving the RfD. 

The use of the PBTK model however does not address cross-species differences in 

pharmacodynamics, which should be considered, following the Agency’s 2005 Guidelines for 

Carcinogen Risk Assessment. 

 The Panel noted that the air concentration one would derive using the default approach 

(multiply the HED by body weight [70 kg] and dividing by daily inhalation rate [20 m3/day] 

yielding 0.266 μg/m3

) is very similar to the HEC derived using the PBTK model (0.25 μg/m3). 

Therefore, if the EPA decides to also provide an extrapolation based on measured data (as 

described in the response to charge question 8), the default approach of extrapolating from an 

absorbed oral dose to an equivalent intake from the inhalation route (multiplying by 70 kg and 

dividing by 20 m3/day) can be used with confidence to calculate the IUR. 

Charge Question 25. The recommendation to use the age-dependent adjustment factors 

(ADAFs) is based on the determination of a mutagenic MOA for carcinogenicity. Is this 

recommendation scientifically justifiable and transparently and objectively described? 

 The recommendation to use the age-dependent adjustment factors is well justified and 

transparently and objectively described. The Panel’s deliberations regarding quantitating agedependent adjustment factors (Section 5.4.6) followed from discussions of a mutagenic mode of 

action for acrylamide and the typically enhanced sensitivity of fetal and neonatal animals from 

exposure to such agents in accordance with EPA’s Supplemental Guidance for Assessing 

Susceptibility from Early Life Exposure to Carcinogens (2005b). The Panel also discussed the 

value of using the PBTK model to evaluate the effect of lifestage on CYP 2E1 and glutathione 

52
levels that could modify internal exposure to glycidamide. Such modeling results could be used 

to reduce the uncertainty associated with lifestage extrapolations and the derivation of agedependent adjustment factors. Such efforts would be directed at pharmacokinetic aspects of the 

age-dependent adjustment factors. Uncertainty regarding pharmacodynamics would remain to 

be addressed by the age-dependent adjustment factors. 

Charge Question 26. Please provide any other comments on the CSF or IUR, and on the 

discussion of uncertainties in the cancer assessment. 

 The discussion of uncertainties is good, but human variability could be addressed in 

greater length. It is unclear why in Table 5-13 the consideration/approach is “Method used to 

protect sensitive populations.” There is no characterization of sensitive populations, and this 

could be explored and discussed to a much greater extent.

 Specifically, not enough attention was paid to consequences of individual differences in 

metabolism and cancer risk. Both the CYP2E1 polymorphisms and glutathione transferase(s) 

(even though rodent data suggests no role for this pathway) polymorphisms could be looked at in 

human populations. The degree to which increased activity influences the risk should be 

considered, including whether this might be tumor site dependent. Also, much weight is put on 

the two chronic studies in the Fischer344 rat. The limitations of not having another rodent 

species should be discussed in more detail with respect to other carcinogens where 2 species 

were evaluated and similar or different results were found. 

 A factor to scale for toxicodynamic differences between humans and animals was not 

included in the derivation of the CSF and IUR. The 2005 EPA Carcinogenic Risk Assessment 

Guidelines (see e.g., Guidelines pp 1-13 and 3-7) discusses how toxicodynamics can be 

addressed by such a factor. The development of unit risk-based on HEC accounts for the 

toxicokinetic but not toxicodynamic interspecies differences. 

53
ABREVIATIONS 

ADAF age-dependent adjustment factor 

AM-GSH Acrylamide-Glutathione 

AUC area under the curve 

BMD benchmark dose 

BMDL benchmark dose level 

BMR benchmark response 

CNS Central Nervous System 

CSAF Chemical-specific Adjustment Factors 

CSF Cancer slope factor 

DNA Deoxyribonucleic Acid 

EPA Environmental Protection Agency 

FQPA Food Quality Protection Act 

GA or Gly Glycidamide 

GA-GSH Glycidamide-Glutathione 

HEC Human Equivalent Concentration 

IARC International Agency for Research on Cancer () 

IRIS Integrated Risk Information System 

IUR inhalation unit risk 

LOAEL Lowest Adverse Effect Level 

MMS Methylmethanesulfonate 

MOA mode of action 

MOE Margin of Exposure 

NMA N-Methylolacrylamide 

NO Nitric Oxide 

NOAEL No Adverse Effect Level 

NTP/CERHR National Toxicology Program 

PBPK physiologically-based pharmacokinetic 

PBTK physiologically-based toxicokinetic 

PK Pharmacokinetic 

POD point of departure 

RfC reference concentration 

RfD reference dose 

TP tumor promoter 

UF uncertainty Factor 

WHO World Health Organization 

54
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67
Appendix A Memorandum and Charge Questions 

68
Charge Questions 

Selection of Studies and Endpoints for the Oral Reference Dose (RfD) 

In the draft document, the proposed most sensitive noncancer effect from exposure to acrylamide 

is neurotoxicity. This endpoint is based on an extensive database of animal and human studies. 

The next most sensitive effect is reproductive toxicity, which was in the 3-5 fold higher exposure 

range for a no effect response in animal studies. No human data were identified for acrylamide 

related reproductive effects. Heritable germ cell effects, a potentially serious noncancer effect, 

have been observed in male mice, however, the lowest dose levels tested are considerably higher 

(two orders of magnitude) than the doses where neurotoxicity were observed, and there is 

uncertainty about the shape of the low-dose-response relationship. 

1. Please comment on the selection of neurotoxicity as the most appropriate choice for the most 

sensitive endpoint (in contrast to reproductive toxicity, heritable germ cell effects, or other 

endpoint) based upon the available animal and human data. 

2. Please comment on the discussion of mode of action for acrylamide-induced neurotoxicity. 

Is the discussion clear, transparently and objectively described, and accurately reflective of 

the current scientific understanding? 

3. Please comment on the qualitative discussion of acrylamide’s heritable germ cell effects and 

whether the discussion is clear, transparently and objectively described, and reflective of the 

current science. 

Derivation of the Reference Dose (RfD)

The proposed RfD (0.003 mg/kg-day) for acrylamide is based on a benchmark dose analysis of 

the dose-response relationship for neurotoxicity in two chronic drinking water exposure 

bioassays using Fischer 344 rats. Uncertainty factors and a PBPK model are used to extrapolate 

the animal dose-response to a human equivalent dose-response in the derivation of the RfD. 

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4. Please comment on whether the selection of the Friedman et al., (1995) and Johnson et al., 

(1986) studies as co-principal studies has been scientifically justified. Although EPA 

considers Friedman et al. and Johnson et al. to be co-principal studies, the final quantitative 

RfD value is derived only from the Johnson study. Please comment on this aspect of EPA's 

approach. Please also comment on whether this choice is transparently and objectively 

described in the document. Please identify and provide the rationale for any other studies 

that should be selected as the principal study(s). 

5. Please comment on the benchmark dose methods and the choice of response level used in the 

derivation of the RfD, and whether this approach is accurately and clearly presented. Do 

these choices represent the most scientifically justifiable approach for modeling the slope of 

the dose-response for neurotoxicity? Are there other response levels or methodologies that 

EPA should consider? Please provide a rationale for alternative approaches that should be 

considered or preferred to the approach presented in the document. 

6. Please comment on the selection of the uncertainty factors (other than the interspecies 

uncertainty factor) applied to the point of departure (POD) for the derivation of the RfD. For 

instance, are they scientifically justified and transparently and objectively described in the 

document? [Note: This question does not apply to the interspecies uncertainty factor which is 

addressed in the questions on the use of the PBPK model (see PBPK model questions 

below)] 

7. Please provide any other comments on the derivation of the RfD and on the discussion of 

uncertainties in the RfD. 

Use of a PBPK Model in the Derivation of the RfD and the Inhalation Reference 

Concentration (RfC)

A physiologically-based toxicokinetic (PBTK) model originally developed by Kirman et al.

(2003), and recalibrated by EPA with more recent kinetic and hemoglobin binding data in rats, 

mice, and humans (Boettcher et al., 2005; Doerge et al., 2005a,b; Fennell et al., 2005) was used 

in the derivation of the RfD to extrapolate from the animal dose-response relationship (observed 

in the co-principal oral exposure studies for neurotoxicity) to derive a human equivalent 

concentration (HEC). The HEC is the external acrylamide exposure level that would produce the 

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same internal level of parent acrylamide (in this case the area under the curve [AUC] of 

acrylamide in the blood) that was estimated to occur in the rat following an external exposure to 

acrylamide at the level of the proposed point of departure, and related to a response level of 5% 

(i.e., the BMDL5). The model results were used in lieu of the default interspecies uncertainty 

factor for toxicokinetics differences of 101/2, which left a factor of 101/2 (which is rounded to 3) 

for interspecies differences in toxicodynamics. 

With respect to the RfC, there are presently insufficient human or animal data to directly derive 

an RfC for acrylamide. The PBPK model was thus used to conduct a route-to-route extrapolation 

(oral-to-inhalation) to derive an RfC based on the dose-response relationship observed in the coprincipal oral exposure studies for neurotoxicity. In this case, the HEC was based on a 

continuous inhalation exposure to acrylamide in the air that would yield the same AUC for the 

parent acrylamide in the blood as that estimated for the rat following an external oral exposure to 

acrylamide at the level of the proposed point of departure (i.e., the BMDL5). 

8. Please comment on whether the documentation for the recalibrated Kirman et al. (2003) 

PBTK model development, evaluation, and use in the assessment is sufficient to determine if 

the model was adequately developed and adequate for its intended use in the assessment. 

Please comment on the use of the PBTK model in the assessment, e.g., are the model 

structure and parameter estimates scientifically supportable? Is the dose metric of areaunder-the-curve (AUC) for acrylamide in the blood the best choice based upon what is 

known about the mode of action for neurotoxicity and the available kinetic data? Please 

provide a rationale for alternative approaches that should be considered or preferred to the 

approach presented in the document. 

9. Is the Young et al. (2007) PBTK model adequately discussed in the assessment with respect 

to model structure, parameter values, and data sets used to develop the model? Do you agree 

with the conclusion (and supporting rationale) that the recalibrated Kirman et al. (2003) 

model (model structure and parameter values presented in the Toxicological Review) 

currently represents the best model to use in the derivation of the toxicity values? 

10. According to US EPA’s RfC Methodology (1994), the use of PBTK models is assumed to 

account for uncertainty associated with the toxicokinetic component of the interspecies 

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uncertainty factor across routes of administration. Does the use of the PBTK model for 

acrylamide objectively predict internal dose differences between the F344 rat and humans, is 

the use of the model scientifically justified, and does the use of the PBTK reduce the overall 

uncertainty in this estimate compared to the use of the default factor? Are there sufficient 

scientific data and support for use of this PBTK model to estimate interspecies toxicokinetic 

differences and to replace the default interspecies factor for toxicokinetic differences (i.e., 

101/2)? Is the remaining uncertainty factor for toxicodynamic differences scientifically 

justified, appropriate and correctly used? 

11. Please comment on whether the PBTK model is adequate for use to conduct a route-to-route 

extrapolation for acrylamide to derive an RfC in the absence of adequate inhalation animal or 

human dose-response data to derive the RfC directly. Was the extrapolation correctly 

performed and sufficiently well documented? 

12. Please provide any other comments on the derivation of the RfC and on the discussion of 

uncertainties in the RfC. 

Margin of Exposure (MOE) Analysis 

IRIS documents do not include exposure assessments, which precludes the ability to conduct a 

Margin of Exposure (MOE) analysis. It has been suggested, however, that the acrylamide 

assessment include a Table that lists points of departure for various endpoints to facilitate a MOE 

evaluation by EPA’s Regional or Program offices, or by other end users of the assessment. 

13. Would you suggest that EPA include a Table that lists points of departure (e.g., NOAELs, 

BMDs, etc.) for various endpoints that could be used, in conjunction with exposure 

assessments, to conduct a MOE analysis? 

Quantitating Heritable Germ Cell Effects

The Toxicological Review includes a discussion of methods to quantitate the risk for heritable 

germ cell effects (Section 5.4). The questions below address the uncertainty and utility of the 

quantitative results. 

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14. Please comment on the discussion of methods to quantitate the dose-response for heritable 

germ cell effects as to whether it is appropriate, clear and objective, and reflective of the 

current science. Has the uncertainty in the quantitative characterization of the heritable germ 

cell effects been accurately and objectively described? 

15. Please comment on the scientific support for the hypothesis that heritable germ cell effects 

are likely to occur at doses lower than those seen for neurotoxicity? What on-going or future 

research might help resolve this issue? 

16. The risks of heritable germ cell effects (i.e., number of induced genetic diseases per million 

offspring) for some estimated exposure in workers and the population are presented in Table 

5-11, and are based on the quantitative methods and parameter estimates discussed in Section 

5.4 of the Toxicological Review. Please comment on whether or not the quantitation of 

heritable germ effects should be conducted, the level of uncertainty in the results, if Table 5-

11 is useful for risk assessment purposes, and if the RfD should be included in the Table as 

one of the exposure levels. 

17. Do you know of any additional data or analyses that would improve the quantitative 

characterization of the dose-response for acrylamide-induced heritable germ cell effects? 

Would these data also support the quantitative characterization of “total” male-mediated 

reproduction risks to offspring (i.e., lethality + heritable defect)? If data are not available, do 

you have any recommendations for specific needed studies? 

Carcinogenicity of Acrylamide

In accordance with EPA’s 2005 Guidelines for Carcinogen Risk Assessment

(www.epa.gov/iris/backgr-d.htm), acrylamide is described as likely to be carcinogenic to humans

based on: (1) significant increased incidences of thyroid tumors in male and female rats, scrotal 

sac mesotheliomas in male rats, and mammary gland tumors in female rats in two drinking water 

bioassays; (2) initiation of skin tumors following oral, intraperitoneal, or dermal exposure to 

acrylamide and the tumor promoter, TPA, in two strains of mice; and (3) increased incidence of 

lung adenomas in another mouse strain following intraperitoneal injection of acrylamide. 

Evidence from available human studies is judged to be limited to inadequate. 

73
The mechanisms by which acrylamide may cause cancer are poorly understood, but EPA has 

determined that the weight of the available evidence supports a mutagenic mode of carcinogenic 

action, primarily for the acrylamide epoxide metabolite, glycidamide (GA). Other mode(s) of 

action (MOA) have been proposed for the carcinogenicity of acrylamide, but there is less 

support. 

18. Have the rationale and justification for the cancer designation for acrylamide been clearly 

described? Is the conclusion that acrylamide is a likely human carcinogen scientifically 

supportable? 

19. Do you agree that weight of the available evidence supports a mutagenic mode of 

carcinogenic action, primarily for the acrylamide epoxide metabolite, glycidamide (GA)? 

Has the rationale for this MOA been clearly and objectively presented, and is it reflective of 

the current science? 

20. Are there other MOAs that should be considered? Is there significant biological support for 

alternative MOAs for tumor formation, or for alternative MOAs to be considered to occur in 

conjunction with a mutagenic MOA? Please specifically comment on the support for 

hormonal pathway disruption. Are data available on alternate MOAs sufficient to quantitate a 

dose-response relationship? 

21. Two chronic drinking water exposure bioassays in Fischer 344 rats (Friedman et al., 1995; 

Johnson et al., 1986) were used to derive the oral slope factor, and to identify the tumors of 

interest for the MOA discussion. Are the choices for the studies, tumors, and methods to 

quantify risk transparent, objective, and reflective of the current science? Do you have any 

suggestions that would improve the presentation or further reduce the uncertainty in the 

derived values? 

22. The cancer slope factor (CSF) derivation includes an adjustment for early mortality (i.e., 

time-to-tumor analysis). Is this adjustment scientifically supported in estimating the risk from 

the 2-year bioassay data for increased incidence of tumors in the rats? 

23. The dose metric used in the PBTK model analysis to derive the human equivalent 

concentration was area under the curve (AUC) in the blood for the putative genotoxic 

metabolite, glycidamide. Please comment on whether AUC for glycidamide is the best 

choice of the dose metric in estimating the human equivalent concentration to derive the oral 

74
slope factor. If other dose metrics are preferable, please provide the scientific rationale for 

their selection. 

24. As with the RfC, there were insufficient cancer inhalation data to derive an inhalation unit 

risk (IUR). The PBTK model was used in a route-to-route extrapolation of the dose-response 

relationship from the oral data, and to estimate the human equivalent concentration for 

inhalation exposure to acrylamide. Please comment on whether this extrapolation to derive 

the inhalation unit risk was correctly performed and sufficiently well documented. 

25. The recommendation to use the age-dependent adjustment factors (ADAFs) is based on the 

determination of a mutagenic MOA for carcinogenicity. Is this recommendation scientifically 

justifiable and transparently and objectively described 

26. Please provide any other comments on the CSF or IUR, and on the discussion of 

uncertainties in the cancer assessment. 

75
Appendix B 

Proposed Modes of Action (MOAs) for Acrylamide Neurotoxicity 

 The following text on the two proposed MOAs for acrylamide neurotoxicity was written 

by one panel member. It is offered for the Agency’s consideration in writing the revised version 

of the acrylamide IRIS document: 

1. Disruption of Nitric Oxide (NO) Signaling at the Nerve Terminal Hypothesis 

 Acrylamide is a conjugated α,β-unsaturated carbonyl derivative in the type-2 alkene 

chemical class. Because electrons in pi orbitals of a conjugated system are mobile, the α,βunsaturated carbonyl structure of acrylamide is characterized as a soft electrophile according to 

the hard-soft, acid-base principle (reviewed in Pearson, 1967). Characteristically, soft 

electrophiles will preferentially form Michael-type adducts with soft nucleophiles, which in 

biological systems are primarily sulfhydryl groups on cysteine residues (Hinson and Roberts, 

1992; LoPachin and DeCaprio, 2005). Free sulfhydryl groups can exist in the reduced thiol-state 

or in the anionic thiolate-state and recent research indicates that the highly nucleophilic thiolate 

is the preferential adduct target for acrylamide (LoPachin et al., 2007b; see also Friedman et al., 

1995). Based on the pKa of cysteine (pH 8.5), at physiological pH (7.4) the thiolate state exists 

only in unique protein motifs called catalytic triads, where proton shuttling through an acid-base 

pairing of proximal amino acids (e.g., aspartic acid and lysine) regulates the protonation and 

deprotonation of the cysteine sulfhydryl group. Indeed, both mass spectrometric and kinetic data 

have demonstrated the selective adduction of cysteine residues on many neuronal proteins 

(Barber and LoPachin, 2004; Barber et al., 2007). Furthermore, it is now recognized that the 

redox state or nucleophilicity of cysteine sulfhydryl groups within catalytic triads can determine 

the functionality of these proteins (reviewed in LoPachin and Barber, 2006; Stamler et al., 2001). 

In contrast to acrylamide, the epoxide metabolite glycidamide (Gly), is a hard electrophile that 

preferentially forms adducts with hard nucleophiles such as nitrogen, carbon and oxygen. 

Nucleotide residues of DNA contain abundant hard nucleophilic targets, which is consistent with 

the formation of glycidamide adducts on adenine and guanine bases in acrylamide-intoxicated 

animals (Doerge et al., 2005; reviewed in Besaratinia and Pfeifer, 2007). 

 Based on the observation that the processes affected (e.g., neurotransmitter release and 

storage) and corresponding kinetics (Km, Vmax) were similar in synaptosomes exposed in vitro to 

76
acrylamide and those isolated from acrylamide-intoxicated rats (Barber and LoPachin, 2004; 

LoPachin et al., 2004, 2006), LoPachin and colleagues have reasoned that the parent compound, 

acrylamide, is responsible for neurotoxicity. Moreover, cysteine thiolate groups have clear 

regulatory functions in many critical neuronal processes (LoPachin and Barber, 2006), whereas 

protein valine, lysine and histidine residues, which are the likely hard nucleophilic targets for a 

hard electrophile such as Gly, have unclear functional and therefore toxicological relevance. 

Quantitative morphometric and silver stain analyses of PNS and CNS of acrylamide-intoxicated 

animals have shown that axon degeneration was an epiphenomenon related to dose-rate; i.e., 

degeneration occurred at lower but not higher dose-rates. In contrast, nerve terminal 

degeneration occurred regardless of dose-rate and in correspondence with the onset and 

development of neurological deficits (Crofton et al., 1996; Lehning et al., 1998, 2002a,b, 2003; 

reviewed in LoPachin et al., 1994, 2002, 2003), suggesting the nerve terminals as a primary site 

of action. Subsequent neurochemical studies showed that both in vitro and in vivo acrylamide 

exposure produced early disruptions of neurotransmitter release, reuptake and vesicular storage 

(Barber and LoPachin, 2004; LoPachin et al., 2004, 2006, 2007a). Further, proteomic analyses 

indicated that the inhibition of presynaptic function was due to the formation of cysteine adducts 

on proteins that regulate neurotransmitter handling; e.g., Cys 264 of N-ethylmaleimide sensitive 

factor, Cys 254 of v-ATPase (see Barber and LoPachin, 2004; Barber et al., 2007; Feng and 

Forgac, 1992; LoPachin et al., 2007a,b, 2008b; reviewed in LoPachin and Barber, 2006). The 

anionic sulfhydryl state, which is only found in the catalytic triads of regulatory proteins, is an 

acceptor for nitric oxide (NO) and, therefore, has lead to the proposal that acrylamide-induced 

neurotoxicity results from disruption of neuronal NO signaling (LoPachin and Barber, 2006; 

LoPachin et al., 2008a). 

2. Fast Axonal Transport Disruption Hypothesis 

Another proposed MOA is that both acrylamide and Gly inhibit the movement of 

materials in fast axonal transport (Sickles et al., 2002). According to the “kinesin/axonal 

transport” hypothesis, toxicant inhibition of kinesin could lead to reductions in the axonal 

delivery of macromolecules that would eventually produce a deficiency of essential proteins 

required to maintain axon structure and/or function. Distal axons and nerve terminals are 

particularly vulnerable to transport defects based upon an exceptionally large axonal volume (as 

77
much as 1000 times the volume of the neuron cell body) and the dependence of these distal 

regions on long distance transport (100 fold longer length than diameter of the cell body). This 

regional sensitivity is consistent with the previously identified distal spatial distribution of 

toxicant-induced damage (Cavanagh, 1964). 

Microtubule motility assays using purified kinesin from bovine brain identified a dosedependent inhibition of kinesin as well as a less sensitive effect on microtubules (Sickles et al., 

1996). Preincubation of either kinesin or taxol-stabilized microtubules produced a reduction in 

the affinity between kinesin and microtubules, recognized as a reduced number of microtubules 

bound or locomoting on an absorbed bed of kinesin. Microtubules that were locomoting did so in 

a less directed or staggering type of progression. The inhibitions were due to covalent adduction, 

presumably through sulfhydryl alkylation, although adduction of other amino acid residues such 

as valine was possible. The non-neurotoxic analogue, propionamide had no effect. Other 

investigators have identified kinesin inhibition by sulfhydryl reagents such as N-ethylmaleimide 

and ethacrynic acid (Walker et al., 1997). As with acrylamide, inhibition by these sulfhydryl 

reagents produced the characteristic staggering movement of microtubules. The reaction was 

slow and temperature dependent suggesting a sterically hindered cysteine residue as an important 

adduct target. Additional studies have demonstrated a comparable effect of glycidamide on 

kinesin (Sickles, unpublished data). The predicted outcome of such an effect would be reduced 

quantity of flow, precisely the outcome from several experiments where rate of transport versus 

quantity could be discriminated (Sickles, 1989a; Sickles, 1989b; Stone et al., 1999). 

Fast axonal transport has been studied in a variety of model systems using diverse 

techniques. A comprehensive survey of acrylamide effects on fast anterograde and retrograde 

axonal transport (Sickles et al. ,2002) revealed that all studies measuring fast transport within 24 

hours of acrylamide exposure demonstrated significant reductions, whereas longer postexposure 

delay was not associated with changes in transport. Furthermore, a reduction in transport 

quantity (but not rate) has been reported within 20 minutes of exposure. The duration of this 

effect was 16 hours, with full recovery at 24 hours (Sickles, 1991). Quantitation of transport 

after multiple dosings (i.e. 4, 7 or 10 doses) had a similar effect on transport in the proximal 

sciatic nerve (Sickles, 1991). The changes in transport were not due to an effect on protein 

synthesis and exposure of only the axons confirmed that the target was axonal (Sickles, 1989a; 

Sickles, 1992). Collectively, these results suggested action on a target that is replaced via the fast 

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transport system, consistent with kinesin. The actions of acrylamide on fast axonal transport 

were independent of effects on axonal neurofilaments, as similar reductions were observed in 

wild-type and transgenic mice lacking axonal neurofilaments (Stone et al., 1999; Stone et al., 

2000). The same results were observed using radiolabelling of proteins in mouse optic nerves 

and differential interference microscopy of isolated sciatic nerve axons. Other recent studies 

have identified a parallel inhibition of retrograde axonal transport by acrylamide (Sabri and 

Spencer, 1990), although it is unclear whether this effect is due to inhibition of cytoplasmic 

dynein, the retrograde axonal transport motor, or whether this is a result of indirect effects of 

kinesin motor inhibition (Brady et al., 1990). 

The predicted outcome from axonal transport compromise is a reduction in vital 

macromolecules in the distal axons and an accumulation of transported material within the axon. 

Morphological studies have consistently identified accumulations of tubulovesicular profiles and 

neurofilaments in axons of acrylamide-intoxicated animals (Spencer and Schaumburg, 1991), 

which are morphological elements transported via kinesin along microtubules. Other studies 

have identified reduced synaptic vesicles in neuromuscular junctions (DeGrandchamp and 

Lowndes, 1990; DeGrandchamp et al., 1990). A reduction in GAP-43 in the terminal neurites of 

cultured primary spinal cord neurons following acrylamide exposure has been observed (Clarke 

and Sickles, 1996). Future studies are required to quantitate reductions in specific axonal 

compartments using a variety of neurotoxic and non-neurotoxic dosing regimens in vivo to 

confirm the loss of physiologically or structurally important macromolecules. 

Additional supportive data for the axonal transport hypothesis comes from several studies 

of kinesin knockouts as well as similarity to human diseases. While most knockouts are lethal, 

low level mutations of kinesin motors in Drosophila have identified an identical spatial pattern of 

dysfunction and morphological similarity in axonal pathology (Gho et al., 1992; Hurd and 

Saxton, 1996) as with acrylamide intoxication. The group of neurological disorders classified as 

hereditary spastic paraplegias has a spatial pattern of ataxia, spasticity and muscle weakness as 

observed with acrylamide intoxication. Some of these types have been associated with mutations 

in kinesin motors (Reid et al., 2002), while others are the result of either axonal or glial protein 

mutations. However, the common theme is alteration in axonal transport (Reid, 2003; Gould and 

Brady, 2004). 

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Role of Acrylamide vs. Glycidamide 

 The respective adduct chemistries of acrylamide and glycidamide are well understood 

and could have fundamental implications for neurotoxicity regardless of the proposed 

mechanism; i.e., kinesin inhibition (Sickles et al., 2002) or blockade of NO signaling (LoPachin 

and Barber, 2006; LoPachin et al., 2008). Accordingly, an obvious data gap in the current 

mechanistic understanding of acrylamide neurotoxicity, is the relative roles of the parent 

compound and Gly. Thus, although early research suggested that Gly produced neurotoxicity 

both in whole animal (Abou-Donia et al., 1993) and in vitro (Harris et al., 1994) model systems, 

other studies using similar models failed to find neurotoxic effects associated with this 

metabolite (Brat and Brimijoin, 1993; Costa et al., 1992, 1995; Moser et al., 1992). Clearly, 

resolving the relative roles of acrylamide vs. glycidamide is an important issue that will require 

more research. Although the adduct chemistry of these toxicants has been reasonably defined, 

the precise molecular mechanisms and sites of neurotoxicity are unknown.