Selection of Representative Constituents for Unknown, Variable, Complex, or Biological Origin Substance Assessment Based on Hierarchical Clustering.

Many of the newly produced and registered substances are complex mixtures or substances of unknown or variable composition, complex reaction products, and biological materials (UVCBs). The latter often consist of a large number of constituents, some of them difficult-to-identify constituents, which complicates their (eco)toxicological assessment. In the present study, through a series of examples, different scenarios for selection of representatives via hierarchical clustering of UVCB constituents are exemplified. Hierarchical clustering allows grouping of the individual chemicals into small sets, where the constituents are similar to each other with respect to more than one criterion. To this end, various similarity criteria and approaches for selection of representatives are developed and analyzed. Two types of selection are addressed: (1) selection of the most "conservative" constituents, which could be also used to support prioritization of UVCBs for evaluation, and (2) obtaining of a small set of chemical representatives that covers the structural and metabolic diversity of the whole target UVCBs or a mixture that can then be evaluated for their environmental and (eco)toxicological properties. The first step is to generate all plausible UVCB or mixture constituents. It was found that the appropriate approach for selecting representative constituents depends on the target endpoint and physicochemical parameters affecting the endpoint of interest. Environ Toxicol Chem 2021;40:3205-3218. © 2021 SETAC.

UVCB substances II: Development of an endpoint-nonspecific procedure for selection of computationally generated representative constituents.

Substances of unknown or variable composition, complex reaction products, and biological materials (UVCBs) comprise approximately 40% of all registered substances submitted to the European Chemicals Agency. One of the main characteristics of UVCBs is that they have no unique representation. Industry scientists who are part of the scientific community have been working with academics and consultants to address the problem of a lack of a defined structural description. It has been acknowledged that one of the obstacles is the large number of possible structural isomers. We have recently proposed and published a methodology, based on the generic substance identifiers, to address this issue. The methodology allows for the coding of constituents, their generation, calculation of important characteristics of UVCB constituents, and selection of representative constituents. In the present study we introduce a statistical selection of the minimum number of generated constituents representing a UVCB. This representative sample was selected in such a way that the structural variability and the properties of concern of the UVCB were approximated within a predefined tolerable error. The aim of the statistical selection was to enable the assessment of UVCB substances by decreasing the number of constituents that need to be evaluated. The procedure, which was shown to be endpoint-independent, was validated theoretically and on real case studies. Environ Toxicol Chem 2019;38:682-694. © 2019 SETAC.