A framework for application of quantitative property-property relationships (QPPRs) in physiologically based pharmacokinetic (PBPK) models for high-throughput prediction of internal dose of inhaled organic chemicals.
Chemosphere
; 215: 634-646, 2019 Jan.
Article
en En
| MEDLINE
| ID: mdl-30347358
ABSTRACT
New generation of toxicological tests and assessment strategies require validated toxicokinetic data or models that are lacking for most chemicals. This study aimed at developing a quantitative property-property relationship (QPPR)-based human physiologically based pharmacokinetic (PBPK) modeling framework for high-throughput predictions of inhalation toxicokinetics of organic chemicals. A PBPK model was parameterized with QPPR-derived values for hepatic clearance (CLh) and partition coefficients (P) [bloodair (Pba) and tissueair (Pta) and tissueblood (Ptb)]. The model was initially applied to an evaluation dataset of 40 organic chemicals in the applicability domain, and then to an expanded dataset of 249 organic chemicals from diverse chemical classes. 'Batch' analyses were performed for rapid assessments of hundreds of chemicals. The simulations of inhalation toxicokinetics following an 8-h exposure to 1â¯ppm of each chemical were successful. The mean ratios of their predicted-to-experimental values were within a factor of 1.36-2.36 for Ptb and 1.18 for CLh, for 80% of the chemicals in the evaluation dataset. The predicted 24-h area under the venous blood concentration-time curve (AUC24) values were within the predicted envelopes obtained while using experimental values of Pba and considering either no or maximal hepatic extraction. The reliability analysis (based on combined sensitivity and uncertainty analyses) indicated that AUC24 predictions for 55% of the expanded dataset were moderately to highly reliable, with 46% exhibiting highly reliable values. Overall, the modeling framework suggests that molecular structure and chemical properties can together be effectively used to obtain first-cut estimates of the toxicokinetics of data-poor organic chemicals for screening and prioritization purposes.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Compuestos Orgánicos
/
Relación Estructura-Actividad Cuantitativa
/
Modelos Biológicos
Tipo de estudio:
Etiology_studies
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Prognostic_studies
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Risk_factors_studies
Límite:
Animals
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Humans
Idioma:
En
Revista:
Chemosphere
Año:
2019
Tipo del documento:
Article