EPA to Hold October 12, 2018 Meeting on PBPK/PD Models
For Release: September 14, 2018
On October 12, 2018 from 12:00-1:00 PM Eastern Time, EPA will host an external peer review panel to review the potential use of physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) models in the risk assessments for carbaryl, deltamethrin, and permethrin.
The public can listen to the panel’s meeting via webinar. To register, send an email to Nina Naimy at firstname.lastname@example.org. Following the meeting, EPA will accept written comments on the models at www.regulations.gov in each of the chemicals’ registration review dockets for 30 days (carbaryl, EPA-HQ-OPP-2010-0230; deltamethrin, EPA-HQ-OPP-2009-0637; permethrin, EPA-HQ-OPP-2011-0039). The panel’s charge questions and white paper are also available in the dockets.
The Agency has asked this panel to assess the models’ representation, coding, evaluation, documentation, and applications for carbaryl, deltamethrin, and permethrin. If the models are found to be appropriate for characterizing pharmacokinetic or pharmacodynamic behaviors, they will be used to further refine the risk assessments for these pesticides. The panel consists of experts in human health risk assessments with emphases on biological processes, the kinetics of environmental contaminants in human systems, and the development and use of quantitative tools to simulate such processes.
Technical support files for the models and model inputs are available by contacting Steven Snyderman at email@example.com.
PBPK/PD models are mathematical models based on the body’s anatomical and physiological structure. The models quantitatively describe the processes of chemical absorption, distribution, metabolism, and excretion. Using the PBPK/PD models allows EPA to base its risk assessments on more refined points of departure resulting from different routes and durations of exposure and different ages. The use of PBPK/PD models can enhance the accuracy of human health risk assessments and decrease the reliance on default uncertainty factors.