Use of Biomarker and Mode of Action Data

Evaluation of mode of action plays a critical role in both the hazard characterization and dose-response portions of assessments.  Some chemicals may be data-rich, but still lack the data addressing key issues related to MOA.  Other chemicals may have data supporting the involvement of multiple MOAs (either simultaneously or dominating different portions of the dose-response curve).  TERA can work with interested parties to design and conduct (either in-house, or in the laboratories of our collaborators) studies targeted to address key MOA questions.  We have active research projects aimed at developing approaches to quantitatively describing the dose-response for chemicals with multiple MOAs.  We are also researching approaches to quantitatively incorporate biomarker data into quantitative assessments.  These approaches allow one to use the biomarker data to inform the dose-response curve and decrease the amount of extrapolation needed, rather than simply using biomarker data to drive down the point of departure.

Key Questions

bullet How much data is enough to meet EPA’s criteria for identifying a mode of action (MOA)?  What studies are needed to address EPA’s framework?


bullet How can data be used to move away from default approaches, and what are the implications for risk assessment?


bullet How can biomarker data be appropriately incorporated quantitatively into assessments?


bullet How should assessors address new categories of materials, such as those resulting from nanotechnology?


bullet How can assessments address human variability, including genetic polymorphisms and other sources of human variability?


TERA scientists have extensive experience with these and related issues. Example projects include [add links to publications page, etc., as noted below]:


  • Detailed evaluation of tumor MOA and human relevance for tumors induced by acrylamide in rats (thyroid, tunica vaginalis mesothelioma, and mammary gland). Papers in press or undergoing peer review (Dourson et al., 2008; Maier et al., 2008, submitted; Haber et al., 2009). 
  • Worked with laboratory researchers to design studies to resolve MOA issues. Example: Perchlorate
  • Published an approach using data on mutations in the tumor target tissue in transgenic animals to inform cancer MOA analysis for mutagenic carcinogens that may have other cancer MOAs (Moore et al., 2008).
  • Documented the pathophysiological progression (including biomarkers) for several endpoints. 
  • Used a Bayesian network to quantitatively incorporate data on early biomarkers of effect for benzene-induced leukemia to inform the dose-response analysis without using the biomarker directly as a point of departure (Hack et al., 2008, submitted). 
  • Evaluating lung dosimetry from inhalation exposure to nanoparticles
  • Participated in an IPCS-led effort to develop guidelines for the development of CSAFs (IPCS, 2005).
  • Used PBPK modeling and Monte Carlo analysis (in collaboration with Environ) to evaluate the impact on tissue dose of polymorphisms in genes for metabolic enzymes (Haber et al., 2002; Gentry et al., 2002).
  • Developed and presented courses in the use of CSAFs in risk assessment, and in using the EPA framework to apply MOA data for cancer risk assessment.