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Advancing Alternatives Analysis: The Role of Predictive Toxicology in Selecting Safer Chemical Products and Processes

Timothy Malloy, Virginia Zaunbrecher, Elizabeth Beryt, Richard Judson, Raymond Tice, Patrick Allard, Ann Blake, Ila Cote, Hilary Godwin, Lauren Heine, Patrick Kerzic, Jakub Kostal, Gary Marchant, Jennifer McPartland, Kelly Moran, Andre Nel, Oladele Ogunseitan, Mark Rossi, Kristina Thayer, Joel Tickner, Margaret Whittaker, Ken Zarker.
Integrated Environmental Assessment and Management (2017) DOI: https://doi.org/10.1002/ieam.1923 PMID: 28247928


Publication


Abstract

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.

Figures


Figure 1. Uses of predictive toxicology in alternatives analysis.

Tables


Table 1. Major advantages and limitations of grouping in AA.

Table 2. Major advantages and limitations of high‐throughput in vitro assays in AA.

Table 3. Major advantages and limitations of in silico modeling in AA.

Table 4. Major advantages and limitations of nontraditional in vivo testing in AA.