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SUITABILITY OF USING IN VITRO AND COMPUTATIONALLY ESTIMATED PARAMETERS IN SIMPLIFIED PHARMACOKINETIC MODELS
Citation:
OKINO, M. S., W. CHIU, M. V. EVANS, F. W. POWER, J. C. LIPSCOMB, R. TORNERO-VELEZ, C. C. DARY, J. N. BLANCATO, C. CHEN, AND L. S. BIRNBAUM. SUITABILITY OF USING IN VITRO AND COMPUTATIONALLY ESTIMATED PARAMETERS IN SIMPLIFIED PHARMACOKINETIC MODELS. Presented at North American ISSX Meeting , Maui, HI, October 23 - 27, 2005.
Impact/Purpose:
1) Evaluate and apply advanced computational techniques and emerging 'omics technologies to improve dose modeling and, thereby, reduce uncertainty in human exposure and risk assessment.
2) Employ QSAR-based methods, including quantum-chemical approaches, to estimate critical physiochemical and biochemical constants used in PBPK/PD models.
3) Contribute to next-generation PBPK/PD models by developing methods to predict absorption, distribution, metabolism, elimination (ADME) and toxic effects on the basis of physicochemical properties.
Description:
A challenge in PBPK model development is estimating the parameters for absorption, distribution, metabolism, and excretion of the parent compound and metabolites of interest. One approach to reduce the number of parameters has been to simplify pharmacokinetic models by lumping physiologic compartments. However, the a priori estimation of critical parameters for PBPK models - such as partition coefficients and metabolic rate parameters - is an active area of research involving both in vitro systems and computational algorithms. We present a mathematical analysis of the lumped models compared to comprehensive physiologic descriptions. When a priori parameter estimates are incorporated into PBPK models, the lumping of compartments introduces errors in the metrics of interest, including for peak and integrated (area under the curve) measures. We explore a number of methods to minimize the errors and evaluate the suitability of incorporating the pathway-specific a priori data generated from in vitro or computational methods into simplified pharmacokinetic models.
Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect official Agency policy.