Fate and exposure modeling in regulatory chemical evaluation: new directions from retrospection.

The development and application of fate and exposure modeling has undergone fundamental changes over the last 20 years. This has, in part, been driven by different needs within the regulatory community to address chemicals of concern using different approaches. Here we present a retrospective look at fate and exposure model application over the last two decades keeping an international regulatory perspective and using the Government of Canada's Chemicals Management Plan to illustrate concepts. We discuss the important role fate and exposure modeling has played to help address key data gaps when evaluating the risk of chemicals for both human health and ecological reasons. Yet limitations for more widespread model application within a regulatory context remain. Consequently, we identify specific data gaps and regulatory needs with an eye towards new directions for 21st century chemical evaluation. We suggest that one factor limiting greater model application is the need for increased awareness and agreement of what chemical exposure assessment encompasses within the risk assessment paradigm. This is of particular importance today because of the increased availability of computational and high-throughput data and methods for chemical assessment allowing evaluators to potentially examine exposure from site of release to site of toxic action, thus linking exposure with toxicology. We further suggest there is a need for discussion at a global level to promote the awareness of new tools and approaches available for fate and exposure modeling and suggest that this could be organized using the aggregate exposure pathways concept.

[1]  P. Howard,et al.  Are there other persistent organic pollutants? A challenge for environmental chemists. , 2006, Environmental science & technology.

[2]  Konrad Hungerbühler,et al.  Measures of overall persistence and the temporal remote state. , 2004, Environmental science & technology.

[3]  Robert S. Boethling,et al.  Improved method for estimating bioconcentration/bioaccumulation factor from octanol/water partition coefficient , 1999 .

[4]  S. Trapp,et al.  An unexpected challenge: ionizable compounds in the REACH chemical space , 2010 .

[5]  Daniel L Villeneuve,et al.  Adverse outcome pathways: A conceptual framework to support ecotoxicology research and risk assessment , 2010, Environmental toxicology and chemistry.

[6]  K. Goss,et al.  Ion-exchange affinity of organic cations to natural organic matter: influence of amine type and nonionic interactions at two different pHs. , 2013, Environmental science & technology.

[7]  Mark Bonnell,et al.  Bioaccumulation Assessment Using Predictive Approaches , 2009, Integrated environmental assessment and management.

[8]  J. Hermens,et al.  Phospholipophilicity of CxHyN(+) amines: chromatographic descriptors and molecular simulations for understanding partitioning into membranes. , 2016, Environmental science. Processes & impacts.

[9]  J. Arnot,et al.  Development and evaluation of a database of dietary bioaccumulation test data for organic chemicals in fish. , 2015, Environmental science & technology.

[10]  Jon A Arnot,et al.  Screening level risk assessment model for chemical fate and effects in the environment. , 2006, Environmental science & technology.

[11]  Antonio Di Guardo,et al.  Evaluating the environmental fate of a variety of types of chemicals using the EQC model , 1996 .

[12]  Frank A. P. C. Gobas,et al.  A Generic QSAR for Assessing the Bioaccumulation Potential of Organic Chemicals in Aquatic Food Webs , 2003 .

[13]  Frank A. P. C. Gobas,et al.  A model for predicting the bioaccumulation of hydrophobic organic chemicals in aquatic food-webs: application to Lake Ontario , 1993 .

[14]  F. Gobas,et al.  Quantitative Structure Activity Relationships for Predicting the Bioaccumulation of POPs in Terrestrial Food‐Webs , 2003 .

[15]  Todd Gouin,et al.  Prioritising chemicals used in personal care products in China for environmental risk assessment: application of the RAIDAR model. , 2012, Environmental pollution.

[16]  Jon A Arnot,et al.  Modeling Exposure to Persistent Chemicals in Hazard and Risk Assessment , 2009, Integrated environmental assessment and management.

[17]  A. Zidek,et al.  A review of human biomonitoring data used in regulatory risk assessment under Canada's Chemicals Management Program. , 2017, International journal of hygiene and environmental health.

[18]  Konrad Hungerbühler,et al.  Inter-comparison of multimedia modeling approaches: modes of transport, measures of long range transport potential and the spatial remote state. , 2004, The Science of the total environment.

[19]  Jon A Arnot,et al.  A food web bioaccumulation model for organic chemicals in aquatic ecosystems , 2004, Environmental toxicology and chemistry.

[20]  Frank A. P. C. Gobas,et al.  A review of bioconcentration factor (BCF) and bioaccumulation factor (BAF) assessments for organic chemicals in aquatic organisms , 2006 .

[21]  D. Mackay,et al.  Policies for chemical hazard and risk priority setting: can persistence, bioaccumulation, toxicity, and quantity information be combined? , 2008, Environmental science & technology.

[22]  Jon A Arnot,et al.  A quantitative structure‐activity relationship for predicting metabolic biotransformation rates for organic chemicals in fish , 2009, Environmental toxicology and chemistry.

[23]  Helmut Greim,et al.  Application of the threshold of toxicological concern (TTC) to the safety evaluation of cosmetic ingredients. , 2007, Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association.

[24]  Antonio Di Guardo,et al.  Regional differences in chemical fate model outcome. , 2004, Chemosphere.

[25]  Michael Matthies,et al.  Assessing Long-Range Transport Potential of Persistent Organic Pollutants , 2000 .

[26]  L. Burkhard,et al.  Review of existing terrestrial bioaccumulation models and terrestrial bioaccumulation modeling needs for organic chemicals , 2016, Integrated environmental assessment and management.

[27]  Jon A Arnot,et al.  Development and evaluation of a mechanistic bioconcentration model for ionogenic organic chemicals in fish , 2013, Environmental toxicology and chemistry.

[28]  S. Trapp,et al.  A multimedia activity model for ionizable compounds: Validation study with 2,4‐dichlorophenoxyacetic acid, aniline, and trimethoprim , 2010, Environmental toxicology and chemistry.

[29]  S Dimitrov,et al.  Base-line model for identifying the bioaccumulation potential of chemicals , 2005, SAR and QSAR in environmental research.

[30]  F. Gobas,et al.  In Vivo Biotransformation Rates of Organic Chemicals in Fish: Relationship with Bioconcentration and Biomagnification Factors. , 2016, Environmental science & technology.

[31]  D. Mackay,et al.  A quantitative water, air, sediment interaction (QWASI) fugacity model for describing the fate of chemicals in rivers , 1983 .

[32]  Sneha Bhatia,et al.  An in silico skin absorption model for fragrance materials. , 2014, Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association.

[33]  Stephen W. Edwards,et al.  Completing the Link between Exposure Science and Toxicology for Improved Environmental Health Decision Making: The Aggregate Exposure Pathway Framework. , 2016, Environmental science & technology.

[34]  Konrad Hungerbühler,et al.  The OECD software tool for screening chemicals for persistence and long-range transport potential , 2009, Environ. Model. Softw..

[35]  Antonio Franco,et al.  Evolution of the sewage treatment plant model SimpleTreat: Use of realistic biodegradability tests in probabilistic model simulations , 2013, Integrated environmental assessment and management.

[36]  Mark Bonnell,et al.  The role of persistence in chemical evaluations , 2014, Integrated environmental assessment and management.

[37]  Jon A Arnot,et al.  Estimating metabolic biotransformation rates in fish from laboratory data , 2008, Environmental toxicology and chemistry.

[38]  R. Guy Predicting the rate and extent of fragrance chemical absorption into and through the skin. , 2010, Chemical research in toxicology.

[39]  Michael S McLachlan,et al.  Bioaccumulation potential of persistent organic chemicals in humans. , 2004, Environmental science & technology.

[40]  Jon A Arnot,et al.  A database of fish biotransformation rates for organic chemicals , 2008, Environmental toxicology and chemistry.

[41]  Helga Rothe,et al.  Assessing the safety of cosmetic chemicals: Consideration of a flux decision tree to predict dermally delivered systemic dose for comparison with oral TTC (Threshold of Toxicological Concern). , 2016, Regulatory toxicology and pharmacology : RTP.

[42]  K. Bull,et al.  Protocol to the 1979 Convention on Long-Range Transboundary Air Pollution on Persistent Organic Pollutants: The 1998 Agreement for the UNECE Region , 2003 .

[43]  Melvin E. Andersen,et al.  Incorporating High-Throughput Exposure Predictions With Dosimetry-Adjusted In Vitro Bioactivity to Inform Chemical Toxicity Testing , 2015, Toxicological sciences : an official journal of the Society of Toxicology.

[44]  L. Geraets,et al.  Human risk assessment of dermal and inhalation exposures to chemicals assessed by route-to-route extrapolation: the necessity of kinetic data. , 2014, Regulatory toxicology and pharmacology : RTP.

[45]  Frank Wania,et al.  Assessing the Potential of Persistent Organic Chemicals for Long-Range Transport and Accumulation in Polar Regions , 2003 .

[46]  Jon A Arnot,et al.  Iterative fragment selection: a group contribution approach to predicting fish biotransformation half-lives. , 2012, Environmental science & technology.

[47]  K. Goss,et al.  Development and evaluation of a new sorption model for organic cations in soil: contributions from organic matter and clay minerals. , 2013, Environmental science & technology.

[48]  Michael Matthies,et al.  Comparing estimates of persistence and long-range transport potential among multimedia models. , 2005, Environmental science & technology.