Cargando…

Identifying organic chemicals not subject to bioaccumulation in air‐breathing organisms using predicted partitioning and biotransformation properties

Because the respiration processes contributing to the elimination of organic chemicals deviate between air‐ and water‐breathing organisms, existing and widely used procedures for identifying chemicals not subject to bioaccumulation in aquatic organisms based on the octanol–water partition ratio K (O...

Descripción completa

Detalles Bibliográficos
Autores principales: Wania, Frank, Lei, Ying Duan, Baskaran, Sivani, Sangion, Alessandro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9541168/
https://www.ncbi.nlm.nih.gov/pubmed/34783167
http://dx.doi.org/10.1002/ieam.4555
_version_ 1784803865636372480
author Wania, Frank
Lei, Ying Duan
Baskaran, Sivani
Sangion, Alessandro
author_facet Wania, Frank
Lei, Ying Duan
Baskaran, Sivani
Sangion, Alessandro
author_sort Wania, Frank
collection PubMed
description Because the respiration processes contributing to the elimination of organic chemicals deviate between air‐ and water‐breathing organisms, existing and widely used procedures for identifying chemicals not subject to bioaccumulation in aquatic organisms based on the octanol–water partition ratio K (OW) need to be complemented with similar procedures for organisms respiring air. Here, we propose such a procedure that relies on the comparison of a compound's predicted K (OW), octanol–air partition ratio K (OA), and biotransformation half‐life HL ( B ) with three threshold values, below which elimination is judged to be sufficiently rapid to prevent bioaccumulation. The method allows for the consideration of the effect of dissociation on the efficiency of urinary and respiratory elimination. Explicit application of different types of the prediction error, such as the 95% prediction interval or the standard error, allows for variable tolerance for false‐negative decisions, that is, the potential to judge a chemical as not bioaccumulative even though it is. A test with a set of more than 1000 diverse organic chemicals confirms the applicability of the prediction methods for a wide range of compounds and the procedure's ability to categorize approximately four‐fifth of compounds as being of no bioaccumulation concern, suggesting its usefulness to screen large numbers of commercial chemicals to identify those worthy of further scrutiny. The test also demonstrates that a screening based solely on K (OW) and K (OA) would be far less effective because the fraction of chemicals that can be judged as sufficiently volatile and/or sufficiently water soluble for rapid respiratory and urinary elimination based on the partitioning properties predicted for their neutral form is relatively small. Future improvements of the proposed procedure depend largely on the development of prediction methods for the biotransformation kinetics in air‐breathing organisms and for the potential for renal reabsorption. Integr Environ Assess Manag 2022;18:1297–1312. © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).
format Online
Article
Text
id pubmed-9541168
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-95411682022-10-14 Identifying organic chemicals not subject to bioaccumulation in air‐breathing organisms using predicted partitioning and biotransformation properties Wania, Frank Lei, Ying Duan Baskaran, Sivani Sangion, Alessandro Integr Environ Assess Manag Environmental Policy & Regulation Because the respiration processes contributing to the elimination of organic chemicals deviate between air‐ and water‐breathing organisms, existing and widely used procedures for identifying chemicals not subject to bioaccumulation in aquatic organisms based on the octanol–water partition ratio K (OW) need to be complemented with similar procedures for organisms respiring air. Here, we propose such a procedure that relies on the comparison of a compound's predicted K (OW), octanol–air partition ratio K (OA), and biotransformation half‐life HL ( B ) with three threshold values, below which elimination is judged to be sufficiently rapid to prevent bioaccumulation. The method allows for the consideration of the effect of dissociation on the efficiency of urinary and respiratory elimination. Explicit application of different types of the prediction error, such as the 95% prediction interval or the standard error, allows for variable tolerance for false‐negative decisions, that is, the potential to judge a chemical as not bioaccumulative even though it is. A test with a set of more than 1000 diverse organic chemicals confirms the applicability of the prediction methods for a wide range of compounds and the procedure's ability to categorize approximately four‐fifth of compounds as being of no bioaccumulation concern, suggesting its usefulness to screen large numbers of commercial chemicals to identify those worthy of further scrutiny. The test also demonstrates that a screening based solely on K (OW) and K (OA) would be far less effective because the fraction of chemicals that can be judged as sufficiently volatile and/or sufficiently water soluble for rapid respiratory and urinary elimination based on the partitioning properties predicted for their neutral form is relatively small. Future improvements of the proposed procedure depend largely on the development of prediction methods for the biotransformation kinetics in air‐breathing organisms and for the potential for renal reabsorption. Integr Environ Assess Manag 2022;18:1297–1312. © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). John Wiley and Sons Inc. 2021-12-16 2022-09 /pmc/articles/PMC9541168/ /pubmed/34783167 http://dx.doi.org/10.1002/ieam.4555 Text en © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC) https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Environmental Policy & Regulation
Wania, Frank
Lei, Ying Duan
Baskaran, Sivani
Sangion, Alessandro
Identifying organic chemicals not subject to bioaccumulation in air‐breathing organisms using predicted partitioning and biotransformation properties
title Identifying organic chemicals not subject to bioaccumulation in air‐breathing organisms using predicted partitioning and biotransformation properties
title_full Identifying organic chemicals not subject to bioaccumulation in air‐breathing organisms using predicted partitioning and biotransformation properties
title_fullStr Identifying organic chemicals not subject to bioaccumulation in air‐breathing organisms using predicted partitioning and biotransformation properties
title_full_unstemmed Identifying organic chemicals not subject to bioaccumulation in air‐breathing organisms using predicted partitioning and biotransformation properties
title_short Identifying organic chemicals not subject to bioaccumulation in air‐breathing organisms using predicted partitioning and biotransformation properties
title_sort identifying organic chemicals not subject to bioaccumulation in air‐breathing organisms using predicted partitioning and biotransformation properties
topic Environmental Policy & Regulation
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9541168/
https://www.ncbi.nlm.nih.gov/pubmed/34783167
http://dx.doi.org/10.1002/ieam.4555
work_keys_str_mv AT waniafrank identifyingorganicchemicalsnotsubjecttobioaccumulationinairbreathingorganismsusingpredictedpartitioningandbiotransformationproperties
AT leiyingduan identifyingorganicchemicalsnotsubjecttobioaccumulationinairbreathingorganismsusingpredictedpartitioningandbiotransformationproperties
AT baskaransivani identifyingorganicchemicalsnotsubjecttobioaccumulationinairbreathingorganismsusingpredictedpartitioningandbiotransformationproperties
AT sangionalessandro identifyingorganicchemicalsnotsubjecttobioaccumulationinairbreathingorganismsusingpredictedpartitioningandbiotransformationproperties