Nontesting Data

This chapter will describe the various types of data used in the hazard assessment process, including human data, data from laboratory animal studies, data from in vitro studies, and nontesting data that can be deducted from the physico-chemical structure of the substance. 

A wide spectrum of in silico techniques can be used to generate nontesting data for filling in data gaps needed in hazard assessment. The meanings of the different terms used to indicate the estimation methods employed within various regulatory frameworks worldwide are given below. 

Eventually the workflow should be automated as much as possible into a computer-based decision support system (DSS) that aids the process of decision making when generating and using nontesting data for regulatory purposes. The DSS may prove invaluable as a means of promoting the regulatory use of in silico methods. 

It should provide guidance and support for selecting relevant in silico methods and for generating reliable and nontesting data. 

It should provide all the necessary supporting information needed to document the nontesting strategy, to help the user make informed judgments on the adequacy of the nontesting data. 

An important building block of a DSS for generating nontesting data for a given chemical is, of course, an inventory of chemicals that stores a variety of... 

In the final step (step 7) an overall analysis of the outcome of steps 1 through 6 for the endpoint of interest is performed. The toxicity of the parent compound is assessed via the information obtained for all the query compounds (metabolites, reaction products, analogues). The overall assessment should make use of all the available information (testing and nontesting data). A formal logical approach, such as decision theory, that evaluates all the possible options and uses probabilistic calculations to identify the best decision could be used to support the overall assessment process. This implies that additional decision analysis tools will need to be integrated into the DSS. 

The availability of publicly accessible tools should encourage a coordinated use of nontesting data by different authorities across countries. 

Whether information from physico-chemical data, from nontesting methods, from in vitro studies, from animal studies, or from human experience provides evidence that the substance is, or is likely to be, corrosive. 

But when they use these data to produce nontestable astrological revelations, they have crossed over into pseudoscience. 

One of the first steps in the risk assessment process involves the collection of available information on the physicochemical properties, ecological effects, environmental fate, and health effects for a given chemical. In a nontesting strategy, data are also essential to make predictions by means of the read-across approach. Data can be retrieved from books, Internet-based resources (free and commercial resources), or commercial databases. This is a vast and rapidly developing field, so the reader is referred elsewhere for discussions of data sources [28-31],... 

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