Abstract
Physiologically based toxicokinetic (PBTK) modeling in fish offers great promise in environmental risk assessment, potentially speeding up dose-response studies while minimizing animal testing. PBTK models are generally written as ordinary differential equations (ODEs) and have recently been modeled with Petri nets. Some limitations exist in the PBTK field, such as difficulty of model development and a lack of application specific software tools to help modelers. To address some of these limitations we introduce PBTK Optimizer, an open source tool for optimizing parameters of Petri net PBTK models. The software is demonstrated with a previously published and validated PBTK model of fluoranthene exposure in rainbow trout. We present case studies using PBTK Optimizer to evaluate different parameters of the model. The Python code and conclusions regarding the optimization methods used in this software may be adapted for ODE applications beyond PBTK modeling.
Highlights
Based toxicokinetic (PBTK) modelling helps risk assessors determine the bioaccumulation potential for waterborne anthropogenic compounds in fish [1]
Snoopy is a specific software for Petri net (PN), so it does not have additional features that may be useful for Physiologically based toxicokinetic (PBTK) models, such as Monte Carlo simulations or parameter fitting routines
We examined the optimization of biotransformation equations in a previously published PBTK model
Summary
Based toxicokinetic (PBTK) modelling helps risk assessors determine the bioaccumulation potential for waterborne anthropogenic compounds in fish [1]. A typical goal of optimization in PBTK modeling is for simulated time-course mass of a compound in various tissues to closely match experimental values. The ‘Pick Params File’ button on the ‘Parameter Definition’ tab allows a user to select a comma separated value (CSV) file of all the parameters used in the model. The ‘Pick Model File’ button on the ‘Model Definition’ tab allows the user to select a system of ODEs from a text file, formatted according to the following specifications. We optimized the first order and Michaelis-Menten rate constants (k and Km) and maximum enzymatic rate (Vmax) for each of the metabolizing compartments in the Petri net model to the Smith (2003) in vivo evaluation results.
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