Innovative Research for a Sustainable Future www.epa.gov/research Concept Methods Results Additional Sources of Error Conclusion Replication of PBTK Models for Bisphenol A with High-Throughput TK Models Deep Compartment Clearance Compartment Chemical In Chemical Out Qhepatic Lung Blood Qcardiac Qliver Qgut Qrichly perfused Richly Perfused Blood Gut Blood Gut Lumen QGFR Richly Perfused Tissue Liver Blood Liver Tissue Qkidney Lung Tissue CLmetabolism Tissue Blood Kidney Tissue Qgut Arterial Blood Venous Blood Gut Tissue kgutabs Poorly Perfused Tissue Poorly Perfused Blood Doerge i.v. 0.1 mg/kg 1 comp. 2 comp pbtk Yang 2013 pbtk with Yang CL AFE 2.8 2.7 2.7 1.5 2.3 RMSE (nM) 27 24 24 53 22 • High-throughput toxicokinetics can inform the regulation of thousands of untested chemicals currently in use as a new alternative method to animal testing. • Several physiologically-based toxicokinetic (PBTK) models have been developed for Bisphenol A in human and rat. • These models involve extra-hepatic metabolism and contain additional compartments and clearances relative to a basic TK model with parameters fit to in vivo data. • In a high-throughput context, using minimal in vitro and in silico data, models such as these are not practical because of the inability to determine the necessary parameters for many chemicals. • Here we evaluate the performance of various levels of model complexity in the prediction of BPA TK. Chemical Out Compartment Chemical In • Three models from the R package ‘httk’, a PBTK, 2 compartment, and 1 compartment model, were compared against 2 human and 3 rat models from the literature, all evaluated against in vivo data. • Three of the rat studies used iv dosing, one simulating steady-state. The rest of the studies used oral dosing and single doses. • Literature models were translated to code and simulated where possible. • Root-mean-square-error (RMSE, the square root of the average squared difference in measured and predicted concentrations) and average fold error (AFE, the geometric mean of the quotient of the measured and predicted concentrations when the dividend is larger than the divisor) were used as metrics in the evaluation. • Non-restrictive clearance was used, where the total rather than free concentration is subject to clearance. • In the majority of cases, all ‘httk’ models predicted the in vivo data within an order of magnitude, with neither of the 2 compartment and pbtk models performing significantly better than the 1 compartment. Using the Yang et al. 2015 clearance value in rats, the pbtk model predicted the majority of data within a factor of 3. • In rats, the pbtk model predicted as well as the model in Yang et al. 2013 when using the same flow-limited clearance, both having AFE of 5.1, although in vivo measurements sometimes differed by more than a factor of 10 at the same time point. • A limited number of models were available for comparison due to poor reproducibility. • Depending on the necessary level of accuracy, simpler TK models successfully make predictions using limited in vitro and in silico data, with the advantage of greater reproducibility and fewer sources for error. • Enterohepatic recirculation is likely responsible for the changes in the effective elimination rate of the literature models, especially noticeable in rat. This requires additional modeling of the metabolites. • Models were not fully reproducible, due to lack of information or other problems. Many other BPA models could not be included in the analysis for this reason. Additionally, parameters were used in reproduced models not mentioned in the corresponding paper. • Compounds with very abnormal behavior such as PFOS and PFOA cannot be accurately predicted with high- throughput models. This poster dose not necessarily reflect EPA policy. Mention of trade names or commercial products does not constitute endorsement or recommendation for use. 3201/P841 Human Evaluation Rat Steady State Evaluation Rat Single Dose Eva