scholarly journals The long and winding road of progress in the use of in vitro data for risk assessment purposes: From “carnation test” to integrated testing strategies

Toxicology ◽  
2015 ◽  
Vol 332 ◽  
pp. 4-7 ◽  
Author(s):  
Bas J. Blaauboer
1993 ◽  
Vol 21 (2) ◽  
pp. 173-180
Author(s):  
Gunnar Johanson

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.


2005 ◽  
Vol 96 (3) ◽  
pp. 176-181 ◽  
Author(s):  
Ulrike Bernauer ◽  
Axel Oberemm ◽  
Stephan Madle ◽  
Ursula Gundert-Remy

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