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A comprehensive physiologically based pharmacokinetic knowledgebase and web-based interface for rapid model ranking and querying
Lu, J., M. Goldsmith, Chris Grulke, D. Chang, J. Leonard, E. Hypes, AND C. Tan. A comprehensive physiologically based pharmacokinetic knowledgebase and web-based interface for rapid model ranking and querying. Society of Toxicology 55th Annual Meeting and ToxExpo, New Orleans, LA, March 13 - 17, 2016.
The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.
Published physiologically based pharmacokinetic (PBPK) models from peer-reviewed articles are often well-parameterized, thoroughly-vetted, and can be utilized as excellent resources for the construction of models pertaining to related chemicals. Specifically, chemical-specific parameters and in vivo pharmacokinetic data used to calibrate these published models can act as valuable starting points for model development of new chemicals with similar molecular structures. A knowledgebase for published PBPK-related articles was compiled to support PBPK model construction for new chemicals based on their close analogues within the knowledgebase, and a web-based interface was developed to allow users to query those close analogues. A list of 689 unique chemicals and their corresponding 1751 articles was created after analysis of 2,245 PBPK-related articles. For each model, the PMID, chemical name, major metabolites, species, gender, life stages and tissue compartments were extracted from the published articles. PaDEL-Descriptor, a Chemistry Development Kit based software, was used to calculate molecular fingerprints. Tanimoto index was implemented in the user interface as measurement of structural similarity. The utility of the PBPK knowledgebase and web-based user interface was demonstrated using two case studies with ethylbenzene and gefitinib. Our PBPK knowledgebase is a novel tool for ranking chemicals based on similarities to other chemicals associated with existing PBPK models and for rapid accessing of model-constraining publications.