Peer Consultation on Relationship Between PAC Profile and Toxicity of Petroleum Substances


Four manuscripts from the September 2010 Nuclear Receptor Workshop organized by TERA have been published in Critical Reviews in Toxicology (January 2014). The workshop explored the development of dose‐response approaches to nuclear receptor‐mediated liver cancer, within a Mode of Action (MOA) Human Relevance Framework (HRF). Workshop case study teams prepared papers on the AHR, CAR, and PPARalpha receptors, and TERA and the workshop co‐chairs authored an additional overview paper describing the workshop and overarching issues. For each case study a diverse and multi-disciplinary panel of experts from academia, industry, government, and other organizations evaluated the key events leading to liver tumors, and discussed whether the biology of the nuclear receptor necessitates a minimum threshold of ligand to affect activation, gene expression, and subsequent biological and toxicological responses.



Peer Consultation Workshop on the Relationship between PAC Profile and Toxicity of Petroleum Substances

In 2007 TERA organized and conducted an expert peer consultation to review a report by Petroleum HPV Testing Group that hypothesized that toxicity observed in repeated-dose dermal toxicity studies is related to polycyclic aromatic compound (PAC) content. A statistical method using the PAC profile to predict dose–response for untested high-boiling petroleum substances was evaluated.  A series of papers describing the PAC method, underlying data, statistical validation, predictive modeling results, and possible applications of the results, has been published.  TERA scientists authored a paper on the peer consultation process, including an evaluation of the PAC authors’ responsiveness to the peer panel’s recommendations.  Assessing the mammalian toxicity of high-boiling point petroleum substances, Reg. Tox and Pharm (Volume 67, Issue 2, Supplement - pp. S1-S94 (1 November 2013).


What:    Peer Consultation
When:   October 8-9, 2007
Northern Kentucky University Metropolitan Education and Training Services (METS)


Toxicology Excellence for Risk Assessment (TERA) convened a peer consultation on a methodology called Quantitative Composition Activity Relationship (QCAR) October 8-9, 2007.  The PAC Analysis Task Group (TG) of the Petroleum HPV Testing Group proposed new methodology to predict the toxicity of untested petroleum substances based on the relationship between polycyclic aromatic compound (PAC) profile of petroleum substances and select mammalian toxicity responses.  The TG has named this methodology ‘Quantitative Composition Activity Relationship’ or ‘QCAR.’  The goal of the methodology is to predict dose levels of untested substances that will produce a pre-defined change for selected repeat-dose and developmental toxicity endpoints.  The TG proposes to use these calculated values in place of empirically-derived Lowest Observed Adverse Effect Levels (LOAELs) in partial fulfillment of the TG’s data commitments in the EPA’s High Production Volume (HPV) Chemical Challenge Program.



Peer Consultation Meeting Report


Peer Consultation Report


Revised Document (March 31, 2008)


After the peer consultation, the Task group updated and revised their document to respond to the peer consultation. Future updates are planned.


Subject Documents for Peer Consultation (August, 2007)

Volume 1 - Description on US HPV Program

Appendix A - Supportive Information

Volume 2-Investigation into the Relationship between PAC Content & Acute, Repeat-Dose, Development, & Reproductive Tox of Petroleum

Appendix 1 - PAC: Nomenclature and Analysis

Appendix 2 - Company Report/Studies

Appendix 3 - ID of Biological Endpoints for Mathematical Characterization of DR Curve

Appendix 4  - Biological Endpoints for Which Data Were Captured from Study Reports

Appendix 5 - Summary of Analytical Data

Appendix 6 - Statistical Evaluation of Data and Model Development

Appendix 7 - Utility of the model(s) for Predictive Purposes

Appendix 8 - Reproductive Toxicity

Appendix 9 - Observed and Predicted DR curves

Appendix 10 - Raw Data

Appendix 11 - Commentary on C0ncordance/Lack of Concordance Between Endpoints Selected for Modeling and Data from Other Reviews


Contact Jacqueline Patterson for more information (