scholarly journals Integrating in vitro data and physiologically based kinetic modeling-facilitated reverse dosimetry to predict human cardiotoxicity of methadone

2020 ◽  
Vol 94 (8) ◽  
pp. 2809-2827
Author(s):  
Miaoying Shi ◽  
Hans Bouwmeester ◽  
Ivonne M. C. M. Rietjens ◽  
Marije Strikwold
Keyword(s):  
In Vitro Toxicity ◽  
Response Curves ◽  
Chemical Safety ◽  
Safety Testing ◽  
Reverse Dosimetry ◽  
Physiologically Based ◽  
Vitro Data ◽  
In Vitro Data

Abstract Development of novel testing strategies to detect adverse human health effects is of interest to replace in vivo-based drug and chemical safety testing. The aim of the present study was to investigate whether physiologically based kinetic (PBK) modeling-facilitated conversion of in vitro toxicity data is an adequate approach to predict in vivo cardiotoxicity in humans. To enable evaluation of predictions made, methadone was selected as the model compound, being a compound for which data on both kinetics and cardiotoxicity in humans are available. A PBK model for methadone in humans was developed and evaluated against available kinetic data presenting an adequate match. Use of the developed PBK model to convert concentration–response curves for the effect of methadone on human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM) in the so-called multi electrode array (MEA) assay resulted in predictions for in vivo dose–response curves for methadone-induced cardiotoxicity that matched the available in vivo data. The results also revealed differences in protein plasma binding of methadone to be a potential factor underlying variation between individuals with respect to sensitivity towards the cardiotoxic effects of methadone. The present study provides a proof-of-principle of using PBK modeling-based reverse dosimetry of in vitro data for the prediction of cardiotoxicity in humans, providing a novel testing strategy in cardiac safety studies.

scholarly journals Integrating in vitro data and physiologically based kinetic (PBK) modelling to assess the in vivo potential developmental toxicity of a series of phenols

2016 ◽  
Vol 91 (5) ◽  
pp. 2119-2133 ◽  
Author(s):  
Marije Strikwold ◽  
Bert Spenkelink ◽  
Laura H. J. de Haan ◽  
Ruud A. Woutersen ◽  
Ans Punt ◽  
...  
Keyword(s):  
Developmental Toxicity ◽  
Physiologically Based ◽  
Vitro Data ◽  
In Vitro Data

scholarly journals The Use of In Vitro Toxicity Data and Physiologically Based Kinetic Modeling to Predict Dose-Response Curves for In Vivo Developmental Toxicity of Glycol Ethers in Rat and Man

2010 ◽  
Vol 118 (2) ◽  
pp. 470-484 ◽  
Author(s):  
Jochem Louisse ◽  
Esther de Jong ◽  
Johannes J. M. van de Sandt ◽  
Bas J. Blaauboer ◽  
Ruud A. Woutersen ◽  
...  
Keyword(s):  
Kinetic Modeling ◽  
Dose Response ◽  
Developmental Toxicity ◽  
In Vitro Toxicity ◽  
Toxicity Data ◽  
Glycol Ethers ◽  
Response Curves ◽  
Physiologically Based

scholarly journals Prediction of the dose range for adverse neurological effects of amiodarone in patients from an in vitro toxicity test by in vitro–in vivo extrapolation

2021 ◽  
Vol 95 (4) ◽  
pp. 1433-1442
Author(s):  
Engi Abd el-Hady Algharably ◽  
Emma Di Consiglio ◽  
Emanuela Testai ◽  
Reinhold Kreutz ◽  
Ursula Gundert-Remy
Keyword(s):  
Adverse Effects ◽  
Dose Range ◽  
Benchmark Dose ◽  
In Vitro Toxicity ◽  
Neurological Effects ◽  
In Vivo Extrapolation ◽  
Vitro Data ◽  
In Vitro Data

AbstractAmiodarone is an antiarrhythmic agent inducing adverse effects on the nervous system, among others. We applied physiologically based pharmacokinetic (PBPK) modeling combined with benchmark dose modeling to predict, based on published in vitro data, the in vivo dose of amiodarone which may lead to adverse neurological effects in patients. We performed in vitro–in vivo extrapolation (IVIVE) from concentrations measured in the cell lysate of a rat brain 3D cell model using a validated human PBPK model. Among the observed in vitro effects, inhibition of choline acetyl transferase (ChAT) was selected as a marker for neurotoxicity. By reverse dosimetry, we transformed the in vitro concentration–effect relationship into in vivo effective human doses, using the calculated in vitro area under the curve (AUC) of amiodarone as the pharmacokinetic metric. The upper benchmark dose (BMDU) was calculated and compared with clinical doses eliciting neurological adverse effects in patients. The AUCs in the in vitro brain cell culture after 14-day repeated dosing of nominal concentration equal to 1.25 and 2.5 µM amiodarone were 1.00 and 1.99 µg*h/mL, respectively. The BMDU was 385.4 mg for intravenous converted to 593 mg for oral application using the bioavailability factor of 0.65 as reported in the literature. The predicted dose compares well with neurotoxic doses in patients supporting the hypothesis that impaired ChAT activity may be related to the molecular/cellular mechanisms of amiodarone neurotoxicity. Our study shows that predicting effects from in vitro data together with IVIVE can be used at the initial stage for the evaluation of potential adverse drug reactions and safety assessment in humans.

Use of Toxicokinetics in Risk Assessment Based on In Vitro Data

1993 ◽  
Vol 21 (2) ◽  
pp. 173-180
Author(s):  
Gunnar Johanson
Keyword(s):  
Risk Assessment ◽  
Whole Body ◽  
External Exposure ◽  
Target Dose ◽  
Toxic Response ◽  
Route Of Exposure ◽  
Vitro Data ◽  
In Vitro Data

This presentation addresses some aspects of the methodology, advantages and problems associated with toxicokinetic modelling based on in vitro data. By using toxicokinetic models, particularly physiologically-based ones, it is possible, in principle, to describe whole body toxicokinetics, target doses and toxic effects from in vitro data. Modelling can be divided into three major steps: 1) to relate external exposure (applied dose) of xenobiotic to target dose; 2) to establish the relationship between target dose and effect (in vitro data, e.g. metabolism in microsomes, partitioning in tissue homogenates, and toxicity in cell cultures, are useful in both steps); and 3) to relate external exposure to toxic effect by combining the first two steps. Extrapolations from in vitro to in vivo, between animal and man, and between high and low doses, can easily be carried out by toxicokinetic simulations. In addition, several factors that may affect the toxic response by changing the target dose, such as route of exposure and physical activity, can be studied. New insights concerning the processes involved in toxicity often emerge during the design, refinement and validation of the model. The modelling approach is illustrated by two examples: 1) the carcinogenicity of 1,3-butadiene; and 2) the haematotoxicity of 2-butoxyethanol. Toxicokinetic modelling is an important tool in toxicological risk assessment based on in vitro data. Many factors, some of which can, and should be, studied in vitro, are involved in the expression of toxicity. Successful modelling depends on the identification and quantification of these factors.

Sign in / Sign up

Export Citation Format

Share Document