Advancing alternatives analysis: The role of predictive toxicology in selecting safer chemical products and processes

Alternatives analysis (AA) is a method used in regulation and product design to identify, assess, and evaluate the safety and viability of potential substitutes for hazardous chemicals. It requires toxicological data for the existing chemical and potential alternatives. Predictive toxicology uses in silico and in vitro approaches, computational models, and other tools to expedite toxicological data generation in a more cost-effective manner than traditional approaches. The present article briefly reviews the challenges associated with using predictive toxicology in regulatory AA, then presents 4 recommendations for its advancement. It recommends using case studies to advance the integration of predictive toxicology into AA, adopting a stepwise process to employing predictive toxicology in AA beginning with prioritization of chemicals of concern, leveraging existing resources to advance the integration of predictive toxicology into the practice of AA, and supporting transdisciplinary efforts. The further incorporation of predictive toxicology into AA would advance the ability of companies and regulators to select alternatives to harmful ingredients, and potentially increase the use of predictive toxicology in regulation more broadly. Integr Environ Assess Manag 2017;13:915-925. © 2017 SETAC.

[1]  Ruili Huang,et al.  Dose-Response Modeling of High-Throughput Screening Data , 2009, Journal of biomolecular screening.

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

[3]  John P. Overington,et al.  ChEMBL: a large-scale bioactivity database for drug discovery , 2011, Nucleic Acids Res..

[4]  M. T. D. Cronin,et al.  Chapter 1:An Introduction to Chemical Grouping, Categories and Read-Across to Predict Toxicity , 2013 .

[5]  Murray He,et al.  Implementing systematic review in toxicological profiles: ATSDR and NIEHS/NTP collaboration. , 2014 .

[6]  J. C. Madden Chapter 2:Introduction to QSAR and Other In Silico Methods to Predict Toxicity , 2010 .

[7]  Linda S. Birnbaum,et al.  Intersection of Systematic Review Methodology with the NIH Reproducibility Initiative , 2014, Environmental health perspectives.

[8]  Abid Latif,et al.  The Viability of Professional Wet Cleaning as a Pollution Prevention Alternative to Perchloroethylene Dry Cleaning , 2007, Journal of the Air & Waste Management Association.

[9]  D. W. Roberts,et al.  Chapter 2:Approaches for Grouping Chemicals into Categories , 2013 .

[10]  H. Ellinger-Ziegelbauer,et al.  Prediction of a carcinogenic potential of rat hepatocarcinogens using toxicogenomics analysis of short-term in vivo studies. , 2008, Mutation research.

[11]  T. Hartung Food for thought ... on validation. , 2007, ALTEX.

[12]  Sebastian Hoffmann,et al.  Food for thought ... on in silico methods in toxicology. , 2009, ALTEX.

[13]  Valérie Zuang,et al.  A Modular Approach to the ECVAM Principles on Test Validity , 2004, Alternatives to laboratory animals : ATLA.

[14]  Patrick Allard,et al.  Using the Alternative Model C. elegans in Reproductive and Developmental Toxicology Studies , 2014 .

[15]  Andreas Hartmann,et al.  Towards the creation of an international toxicology information centre. , 2005, Toxicology.

[16]  Ann Richard,et al.  ACToR--Aggregated Computational Toxicology Resource. , 2008, Toxicology and applied pharmacology.

[17]  Patience Browne,et al.  Screening Chemicals for Estrogen Receptor Bioactivity Using a Computational Model. , 2015, Environmental science & technology.

[18]  Huixiao Hong,et al.  Predicting hepatotoxicity using ToxCast in vitro bioactivity and chemical structure. , 2015, Chemical research in toxicology.

[19]  Igor Linkov,et al.  Use of multi‐criteria decision analysis in regulatory alternatives analysis: A case study of lead free solder , 2013, Integrated environmental assessment and management.

[20]  Patrice Sutton,et al.  An evidence-based medicine methodology to bridge the gap between clinical and environmental health sciences. , 2011, Health affairs.

[21]  Margaret H. Whittaker,et al.  Risk Assessment and Alternatives Assessment: Comparing Two Methodologies , 2015, Risk analysis : an official publication of the Society for Risk Analysis.

[22]  Thomas Hartung,et al.  Food for thought... on cell culture. , 2007, ALTEX.

[23]  M Balls,et al.  Defining the role of ECVAM in the development, validation and acceptance of alternative tests and testing strategies. , 1995, Toxicology in vitro : an international journal published in association with BIBRA.

[24]  David M. Reif,et al.  In Vitro Screening of Environmental Chemicals for Targeted Testing Prioritization: The ToxCast Project , 2009, Environmental health perspectives.

[25]  S. Dimitrov,et al.  Chapter 15:An Introduction to Read-Across for the Prediction of the Effects of Chemicals , 2010 .

[26]  David M. Reif,et al.  Aggregating Data for Computational Toxicology Applications: The U.S. Environmental Protection Agency (EPA) Aggregated Computational Toxicology Resource (ACToR) System , 2012, International journal of molecular sciences.

[27]  Y. Cohen,et al.  In silico analysis of nanomaterials hazard and risk. , 2013, Accounts of chemical research.

[28]  J Jaworska,et al.  How can structural similarity analysis help in category formation? , 2007, SAR and QSAR in environmental research.

[29]  Chihae Yang,et al.  Toxicity Data Informatics: Supporting a New Paradigm for Toxicity Prediction , 2008, Toxicology mechanisms and methods.

[30]  Kristina A Thayer,et al.  Implementing systematic review in toxicological profiles: ATSDR and NIEHS/NTP collaboration. , 2014, Journal of environmental health.

[31]  Daniele Mandrioli,et al.  Evidence from Toxicology: The Most Essential Science for Prevention , 2015, Environmental health perspectives.

[32]  Ruili Huang,et al.  Analysis of eight oil spill dispersants using rapid, in vitro tests for endocrine and other biological activity. , 2010, Environmental science & technology.

[33]  Sharon Munn,et al.  Adverse outcome pathway (AOP) development I: strategies and principles. , 2014, Toxicological sciences : an official journal of the Society of Toxicology.

[34]  Jennifer Kuzma,et al.  Societal Risk Evaluation Scheme (SRES): Scenario-Based Multi-Criteria Evaluation of Synthetic Biology Applications , 2017, PloS one.

[35]  Oladele A Ogunseitan,et al.  Dempster‐Shafer theory applied to regulatory decision process for selecting safer alternatives to toxic chemicals in consumer products , 2014, Integrated environmental assessment and management.

[36]  Leonard M. Schechtman,et al.  Validation and Regulatory Acceptance of New, Revised and Alternative Toxicological Methods , 2007 .

[37]  Raymond R Tice,et al.  FutureTox II: in vitro data and in silico models for predictive toxicology. , 2015, Toxicological sciences : an official journal of the Society of Toxicology.

[38]  Sharon Munn,et al.  Adverse outcome pathway development II: best practices. , 2014, Toxicological sciences : an official journal of the Society of Toxicology.

[39]  K R Przybylak,et al.  Assessing toxicological data quality: basic principles, existing schemes and current limitations , 2012, SAR and QSAR in environmental research.

[40]  Mark T. D. Cronin,et al.  Prediction of Harmful Human Health Effects of Chemicals from Structure , 2010 .

[41]  R. Joynt Department , 1999, Neurology.

[42]  Robert J Kavlock,et al.  Incorporating human dosimetry and exposure into high-throughput in vitro toxicity screening. , 2010, Toxicological sciences : an official journal of the Society of Toxicology.

[43]  Thomas Hartung,et al.  Perspectives on validation of high-throughput assays supporting 21st century toxicity testing. , 2013, ALTEX.

[44]  Timothy F. Malloy,et al.  Principled Prevention , 2013 .

[45]  S. Bradbury,et al.  Meeting the scientific needs of ecological risk assessment in a regulatory context. , 2004, Environmental science & technology.

[46]  Richard Judson,et al.  Public Databases Supporting Computational Toxicology , 2010, Journal of toxicology and environmental health. Part B, Critical reviews.

[47]  Suryanarayana V Vulimiri,et al.  The use of genetically modified mice in cancer risk assessment: Challenges and limitations , 2013, Critical reviews in toxicology.

[48]  Jo Anne Shatkin,et al.  A multi-stakeholder perspective on the use of alternative test strategies for nanomaterial safety assessment. , 2013, ACS nano.

[49]  Vera Rogiers,et al.  Adverse outcome pathways: hype or hope? , 2013, Archives of Toxicology.

[50]  Keith R Shockley,et al.  Quantitative high-throughput screening data analysis: challenges and recent advances. , 2015, Drug discovery today.

[51]  Imran Shah,et al.  Virtual Tissues in Toxicology , 2010, Journal of toxicology and environmental health. Part B, Critical reviews.

[52]  Nicholas Ball,et al.  Use of category approaches, read-across and (Q)SAR: general considerations. , 2013, Regulatory toxicology and pharmacology : RTP.

[53]  John R. Bucher,et al.  Systematic Review and Evidence Integration for Literature-Based Environmental Health Science Assessments , 2014, Environmental health perspectives.

[54]  C Winder,et al.  Toxicity Assessment of Industrial Chemicals and Airborne Contaminants: Transition from In Vivo to In Vitro Test Methods: A Review , 2005, Inhalation toxicology.