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

Abstract

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

Improving the Environmental Risk Assessment of Substances of Unknown or Variable Composition, Complex Reaction Products, or Biological Materials

“…To some extent, UVCBs are considered in endpoint‐specific guidance (Organisation for Economic Co‐operation and Development 2000; European Chemicals Agency 2014, 2016, 2017a) and in guidance pertaining to ecological assessment approaches (Organisation for Economic Co‐operation and Development 2000). Further, UVCBs have been considered in several articles on the ecological assessment of mixtures (e.g., Dimitrov et al 2015; Kutsarova et al 2019).…”

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

“…To validate the adequacy of their selection, the ranges of variation of parameters associated with the branching and BOD ranges for the large number of initially generated DITA constituents and those of the final selection are compared. For the BOD ranges of the initial DITA set to be defined, an endpoint‐independent sample was statistically selected by the validated procedure implemented in the UVCB Explorer software (Kutsarova et al, 2019). Based on the procedure, a sample of 382 constituents that represent the entire UVCB was selected.…”

“…Applying the methodology for UVCB characterization implemented in UVCB Explorer, 29 755 potential HC constituents in ULSD were generated. To reduce the number of constituents without losing any specific property of the entire UVCB, a non‐endpoint‐specific sample is selected using the validated statistical procedure for each of the 12 chemical blocks (Kutsarova et al, 2019). In total, the number of constituents generated for the whole UVCB is reduced to a sample of 1838 HCs.…”

“…A statistical procedure for an endpoint‐independent selection of representative constituents of complex mixtures has been recently published (Kutsarova et al, 2019). This was a continuation of the methodology developed for UVCB characterization (Dimitrov et al, 2015).…”

“…By applying this approach, it could be claimed with certain confidence that the ratio between the constituents with the property of concern and all constituents in the selected sample is the same (within a tolerated error) as this ratio for the entire population. The statistical procedure is implemented in the UVCB Explorer software and was validated theoretically by a case study described by Kutsarova et al (2019).…”