RESUMO
Sources of uncertainty involved in exposure reconstruction for short half-life chemicals were characterized using computational models that link external exposures to biomarkers. Using carbaryl as an example, an exposure model, the Cumulative and Aggregate Risk Evaluation System (CARES), was used to generate time-concentration profiles for 500 virtual individuals exposed to carbaryl. These exposure profiles were used as inputs into a physiologically based pharmacokinetic (PBPK) model to predict urinary biomarker concentrations. These matching dietary intake levels and biomarker concentrations were used to (1) compare three reverse dosimetry approaches based on their ability to predict the central tendency of the intake dose distribution; and (2) identify parameters necessary for a more accurate exposure reconstruction. This study illustrates the trade-offs between using non-iterative reverse dosimetry methods that are fast, less precise and iterative methods that are slow, more precise. This study also intimates the necessity of including urine flow rate and elapsed time between last dose and urine sampling as part of the biomarker sampling collection for better interpretation of urinary biomarker data of short biological half-life chemicals. Resolution of these critical data gaps can allow exposure reconstruction methods to better predict population-level intake doses from large biomonitoring studies.
Assuntos
Carbaril/farmacocinética , Carbaril/urina , Monitoramento Ambiental/métodos , Contaminação de Alimentos , Inseticidas/farmacocinética , Inseticidas/urina , Modelos Biológicos , Poluentes Químicos da Água/farmacocinética , Poluentes Químicos da Água/urina , Poluição Química da Água , Teorema de Bayes , Biomarcadores/urina , Carbaril/efeitos adversos , Simulação por Computador , Dieta , Relação Dose-Resposta a Droga , Exposição Ambiental/efeitos adversos , Meia-Vida , Humanos , Inseticidas/efeitos adversos , Cadeias de Markov , Método de Monte Carlo , Medição de Risco , Urinálise , Poluentes Químicos da Água/efeitos adversos , Qualidade da ÁguaRESUMO
Drug-induced liver injury (DILI) remains a great challenge and a major concern during late-stage drug development. Induced pluripotent stem cells (iPSC) represent an exciting alternative in vitro model system to explore the role of genetic diversity in DILI, especially when derived from patients who have experienced drug-induced hepatotoxicity. The development and validation of the iPSC-derived hepatocytes as an in vitro cell-based model of DILI is an essential first step in creating more predictive tools for understanding patient-specific hepatotoxic responses to drug treatment. In this study, we performed extensive morphological and functional analyses on iPSC-derived hepatocytes from a commercial source. iPSC-derived hepatocytes exhibit many of the key morphological and functional features of primary hepatocytes, including membrane polarity and production of glycogen, lipids, and key hepatic proteins, such as albumin, asialoglycoprotein receptor and α1-antitrypsin. They maintain functional activity for many drug-metabolizing enzyme pathways and possess active efflux capacity of marker substrates into bile canalicular compartments. Whole genome-wide array analysis of multiple batches of iPSC-derived cells showed that their transcriptional profiles are more similar to those from neonatal and adult hepatocytes than those from fetal liver. Results from experiments using prototype DILI compounds, such as acetaminophen and trovafloxacin, indicate that these cells are able to reproduce key characteristic metabolic and adaptive responses attributed to the drug-induced hepatotoxic effects in vivo. Overall, this novel system represents a promising new tool for understanding the underlying mechanisms of idiosyncratic DILI and for screening new compounds for DILI-related liabilities.