EPA Science Inventory

Computational estimation of errors generated by lumping of physiologically-based pharmacokinetic (PBPK) interaction models of inhaled complex chemical mixtures

Citation:

LaFew, W. AND H. A. EL-MASRI. Computational estimation of errors generated by lumping of physiologically-based pharmacokinetic (PBPK) interaction models of inhaled complex chemical mixtures. INHALATION TOXICOLOGY. Informa Healthcare USA, New York, NY, 24(1):36-46, (2012).

Description:

Many cases of environmental contamination result in concurrent or sequential exposure to more than one chemical. However, limitations of available resources make it unlikely that experimental toxicology will provide health risk information about all the possible mixtures to which humans or other species may be exposed. As such, utilizing computational models in order to make toxicological predictions is a useful tool in complementing experimental efforts which examine mixtures in health risk assessment. This paper outlines a novel mathematical method which reduces the complexity of a mixtures model and increases computational efficiency via a biologically-based lumping methodology (BBLM). In contrast to previous chemical lumping methodologies, BBLM allows the computation of error as a measure of the difference between the lumped simulation based on BBLM and the full mathematical model. As a consequence, the modeler has the opportunity to find the optimal configuration in the tradeoff between simplification and accuracy in order to determine an acceptable number and composition of lumped chemicals. To demonstrate this method, lumped equations based on a typical inhalation physiologically-based pharmacokinetic (PBPK) model assuming a competitive inhibition interaction mechanism are developed for a mixture of arbitrary size. The novel methodology is further tested using literature data for a mixture of 10 volatile organic chemicals (VOCs). Through simulation of these chemicals, BBLM is shown to produce good approximations when compared to the unlumped simulation and experimental data.

Purpose/Objective:

Many cases of environmental contamination result in concurrent or sequential exposure to more than one chemical. However, due to limitations of available resources experimental toxicology is not able to provide health risk information about all the possible mixtures to which humans or other species may be exposed. As such, in order to increase the efficiency of risk assessment the utilization of computational models to make toxicological predictions is a useful tool to complement experimental efforts. We have developed a novel mathematical method, biologically-based lumping methodology (BBLM), which reduces the complexity of a mixtures model and increases computational efficiency.

URLs/Downloads:

INHALATION TOXICOLOGY   Exit

Record Details:

Record Type: DOCUMENT (JOURNAL/PEER REVIEWED JOURNAL)
Start Date: 01/01/2012
Completion Date: 01/01/2012
Record Last Revised: 10/22/2012
Record Created: 11/23/2010
Record Released: 11/23/2010
OMB Category: Other
Record ID: 231487

Organization:

U.S. ENVIRONMENTAL PROTECTION AGENCY

OFFICE OF RESEARCH AND DEVELOPMENT

NATIONAL HEALTH AND ENVIRONMENTAL EFFECTS RESEARCH LAB

INTEGRATED SYSTEMS TOXICOLOGY DIVISION

SYSTEMS BIOLOGY BRANCH