Animal metrics: Tracking contributions of new approach methods to reduced animal use

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M. Sue Marty
Amanda K. Andrus
Katherine A. Groff


Many companies and global regulatory programs have expressed the intent to move away from in vivo animal testing to new approach methods (NAMs) as part of product safety assessments. NAMs, which include non-animal approaches for testing and assessment – from computer-based modeling to in chemico or in vitro models – allow faster data gener­ation with potentially greater relevance to humans while avoiding animal use. To monitor progress implementing NAMs, each organization first must define what is in scope, starting with the definition of “animal” (e.g., mammals, vertebrates) and applicable studies (e.g., animals used for “in-house” experiments, at contract research organizations, as part of envi­ronmental monitoring). Next, organizations must establish baseline animal use, including defined rules for inclusion/ exclusion of animals that ensure consistency in future assessments. Lastly, organizations must establish metrics for animal savings based on the utility of NAM data. This paper presents one approach to establish “animal use” metrics in a toxi­cology program at The Dow Chemical Company. The premise of our program is that most NAM information has value for animal savings, but the value depends on how data are used (e.g., research and development, screening, or regulatory requirements) and the level of certainty for internal decision-making. This manuscript provides metrics on the impact of NAMs, allowing a quantitative assessment of animal use numbers over time, accountability for resources spent on NAM development, and identification of areas where NAM development is still needed. This approach can be refined for use at other organizations.

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Marty, M. S., Andrus, A. K. and Groff, K. A. (2022) “Animal metrics: Tracking contributions of new approach methods to reduced animal use ”, ALTEX - Alternatives to animal experimentation, 39(1), pp. 95–112. doi: 10.14573/altex.2107211.

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