TY - JOUR
KW - Animal Testing Alternatives
KW - Animals
KW - BenchMarks series
KW - Reproducibility of Results
KW - basic quality tools
KW - in vitro methods
KW - reliability
KW - reproducibility
KW - standardization
AU - Elijah J. Petersen
AU - John T. Elliott
AU - John Gordon
AU - Nicole C. Kleinstreuer
AU - Emily Reinke
AU - Mattias Roesslein
AU - Blaza Toman
AB - New approach methodologies (NAMs) are in vitro, in chemico, and in silico or computational approaches that can potentially be used to reduce animal testing. For NAMs that require laboratory experiments, it is critical that they provide consistent and reliable results. While guidance has been provided on improving the reproducibility of NAMs that require laboratory experiments, there is not yet an overarching technical framework that details how to add measurement quality features into a protocol. In this manuscript, we discuss such a framework and provide a step-by-step process describing how to refine a protocol using basic quality tools. The steps in this framework include 1) conceptual analysis of sources of technical variability in the assay, 2) within-laboratory evaluation of assay performance, 3) statistical data analysis, and 4) determination of method transferability (if needed). While each of these steps has discrete components, they are all inter-related, and insights from any step can influence the others. Following the steps in this framework can help reveal the advantages and limitations of different choices during the design of an assay such as which in-process control measurements to include and how many replicates to use for each control measurement and for each test substance. Overall, the use of this technical framework can support optimizing NAM reproducibility, thereby supporting meeting research and regulatory needs.
BT - Alternatives to Animal Experimentation
DA - 2023
DO - 10.14573/altex.2205081
IS - 1
LA - eng
N2 - New approach methodologies (NAMs) are in vitro, in chemico, and in silico or computational approaches that can potentially be used to reduce animal testing. For NAMs that require laboratory experiments, it is critical that they provide consistent and reliable results. While guidance has been provided on improving the reproducibility of NAMs that require laboratory experiments, there is not yet an overarching technical framework that details how to add measurement quality features into a protocol. In this manuscript, we discuss such a framework and provide a step-by-step process describing how to refine a protocol using basic quality tools. The steps in this framework include 1) conceptual analysis of sources of technical variability in the assay, 2) within-laboratory evaluation of assay performance, 3) statistical data analysis, and 4) determination of method transferability (if needed). While each of these steps has discrete components, they are all inter-related, and insights from any step can influence the others. Following the steps in this framework can help reveal the advantages and limitations of different choices during the design of an assay such as which in-process control measurements to include and how many replicates to use for each control measurement and for each test substance. Overall, the use of this technical framework can support optimizing NAM reproducibility, thereby supporting meeting research and regulatory needs.
PY - 2023
SP - 174
EP - 186
T2 - Alternatives to Animal Experimentation
TI - Technical framework for enabling high quality measurements in new approach methodologies (NAMs)
VL - 40
SN - 1868-8551
ER -