Integrated in silico strategy for PBT assessment and prioritization under REACH.

Chemicals may persist in the environment, bioaccumulate and be toxic for humans and wildlife, posing great concern. These three properties, persistence (P), bioaccumulation (B), and toxicity (T) are the key targets of the PBT-hazard assessment. The European regulation for the Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) requires assessment of PBT-properties for all chemicals that are produced or imported in Europe in amounts exceeding 10 tonnes per year, checking whether the criteria set out in REACH Annex XIII are met, so the substance should therefore be considered to have properties of very high concern. Considering how many substances can fall under the REACH regulation, there is a pressing need for new strategies to identify and screen large numbers fast and inexpensively. An efficient non-testing screening approach to identify PBT candidates is necessary, as a valuable alternative to money- and time-consuming laboratory tests and a good start for prioritization since few tools exist (e.g. the PBT profiler developed by US EPA). The aim of this work was to offer a conceptual scheme for identifying and prioritizing chemicals for further assessment and if appropriate further testing, based on their PBT-potential, using a non-testing screening approach. We integrated in silico models (using existing and developing new ones) in a final algorithm for screening and ranking PBT-potential, which uses experimental and predicted values as well as associated uncertainties. The Multi-Criteria Decision-Making (MCDM) theory was used to integrate the different values. Then we compiled a new set of data containing known PBT and non-PBT substances, in order to check how well our approach clearly differentiated compounds labeled as PBT from those labeled as non-PBT. This indicated that the integrated model distinguished between PBT from non-PBT compounds.

[1]  M. Pavan,et al.  The role of the European Chemicals Bureau in promoting the regulatory use of (Q)SAR methods , 2007, SAR and QSAR in environmental research.

[2]  Emilio Benfenati,et al.  Assessment and validation of the CAESAR predictive model for bioconcentration factor (BCF) in fish , 2010, Chemistry Central journal.

[3]  Paola Gramatica,et al.  Are some "safer alternatives" hazardous as PBTs? The case study of new flame retardants. , 2016, Journal of hazardous materials.

[4]  E. Benfenati,et al.  Evaluation of QSAR models for predicting the partition coefficient (log P) of chemicals under the REACH regulation. , 2015, Environmental research.

[5]  L. Su,et al.  The discrimination of excess toxicity from baseline effect: effect of bioconcentration. , 2014, The Science of the total environment.

[6]  P. Calow,et al.  Extrapolation in Ecological Risk Assessment: Balancing Pragmatism and Precaution in Chemical Controls Legislation , 2002 .

[7]  Paola Gramatica,et al.  PBT assessment and prioritization by PBT Index and consensus modeling: comparison of screening results from structural models. , 2015, Environment international.

[8]  A. Smilde,et al.  Multicriteria decision making , 1992 .

[9]  Manuela Pavan,et al.  A set of case studies to illustrate the applicability of DART (Decision Analysis by Ranking Techniques) in the ranking of chemicals , 2008 .

[10]  Ralph Kühne,et al.  Acute to chronic ratios in aquatic toxicity—variation across trophic levels and relationship with chemical structure , 2006, Environmental toxicology and chemistry.

[11]  E. Benfenati,et al.  Assessment of in silico models for acute aquatic toxicity towards fish under REACH regulation , 2015, SAR and QSAR in environmental research.

[12]  T M Martin,et al.  Prediction of the acute toxicity (96-h LC50) of organic compounds to the fathead minnow (Pimephales promelas) using a group contribution method. , 2001, Chemical research in toxicology.

[13]  Traas Tp,et al.  Identifying potential POP and PBT substances : Development of a new Persistence/Bioaccumulation-score , 2011 .

[14]  W. Meylan,et al.  Atom/fragment contribution method for estimating octanol-water partition coefficients. , 1995, Journal of pharmaceutical sciences.

[15]  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.

[16]  Manuela Pavan,et al.  Scientific data ranking methods : theory and applications , 2008 .

[17]  Paola Gramatica,et al.  QSPR as a support for the EU REACH regulation and rational design of environmentally safer chemicals: PBT identification from molecular structure , 2010 .

[18]  Paola Gramatica,et al.  Identification of potential PBT behavior of personal care products by structural approaches , 2015 .

[19]  Emilio Benfenati,et al.  A new in silico classification model for ready biodegradability, based on molecular fragments. , 2014, Chemosphere.

[20]  David E. G. Shuker,et al.  Characterization of azo coupling adducts of benzenediazonium ions with aromatic amino acids in peptides and proteins. , 1997 .

[21]  Emilio Benfenati,et al.  A comparison of DEMETRA individual QSARs with an index for evaluation of uncertainty. , 2008, Chemosphere.

[22]  Emilio Benfenati,et al.  ERICA: A multiparametric toxicological risk index for the assessment of environmental healthiness. , 2010, Environment international.

[23]  E Benfenati,et al.  Automatic knowledge extraction from chemical structures: the case of mutagenicity prediction , 2013, SAR and QSAR in environmental research.

[24]  S. Caudill,et al.  Levels in the U.S. population of those persistent organic pollutants (2003-2004) included in the Stockholm Convention or in other long range transboundary air pollution agreements. , 2009, Environmental science & technology.

[25]  Lu Sun,et al.  Computational models to predict endocrine-disrupting chemical binding with androgen or oestrogen receptors. , 2014, Ecotoxicology and environmental safety.

[26]  Jie Shen,et al.  admetSAR: A Comprehensive Source and Free Tool for Assessment of Chemical ADMET Properties , 2012, J. Chem. Inf. Model..

[27]  S. Hirono,et al.  Simple Method of Calculating Octanol/Water Partition Coefficient. , 1992 .

[28]  Konrad Hungerbühler,et al.  Screening for PBT chemicals among the "existing" and "new" chemicals of the EU. , 2012, Environmental science & technology.

[29]  Tala Henry,et al.  Integrated Approach to PBT and POP Prioritization and Risk Assessment , 2009, Integrated environmental assessment and management.

[30]  Emilio Benfenati,et al.  A new hybrid system of QSAR models for predicting bioconcentration factors (BCF). , 2008, Chemosphere.

[31]  Emilio Benfenati,et al.  Predicting persistence in the sediment compartment with a new automatic software based on the k-Nearest Neighbor (k-NN) algorithm. , 2016, Chemosphere.

[32]  A. Ghose,et al.  Prediction of Hydrophobic (Lipophilic) Properties of Small Organic Molecules Using Fragmental Methods: An Analysis of ALOGP and CLOGP Methods , 1998 .

[33]  Emilio Benfenati,et al.  A new integrated in silico strategy for the assessment and prioritization of persistence of chemicals under REACH. , 2016, Environment international.

[34]  S. Hirono,et al.  Comparison of Reliability of log P Values for Drugs Calculated by Several Methods , 1994 .

[35]  A. Ghose,et al.  Atomic Physicochemical Parameters for Three‐Dimensional Structure‐Directed Quantitative Structure‐Activity Relationships I. Partition Coefficients as a Measure of Hydrophobicity , 1986 .

[36]  Emilio Benfenati,et al.  Evaluation and comparison of benchmark QSAR models to predict a relevant REACH endpoint: The bioconcentration factor (BCF). , 2015, Environmental research.

[37]  M. Rami Reddy,et al.  Assessment of methods used for predicting lipophilicity: Application to nucleosides and nucleoside bases , 1993, J. Comput. Chem..

[38]  E. Benfenati,et al.  Comparison of in silico models for prediction of Daphnia magna acute toxicity , 2014, SAR and QSAR in environmental research.

[39]  G. Veith,et al.  Application of in Silico Metabolism and Environmental Degradation Data to Support Chemical PBT Assessment , 2014 .

[40]  Mark H M M Montforts,et al.  PBT assessment using the revised annex XIII of REACH: a comparison with other regulatory frameworks. , 2012, Integrated environmental assessment and management.

[41]  Jie Shen,et al.  In Silico Assessment of Chemical Biodegradability , 2012, J. Chem. Inf. Model..

[42]  P. Howard,et al.  Identifying new persistent and bioaccumulative organics among chemicals in commerce. , 2010, Environmental science & technology.