2020
DOI: 10.1021/acs.chemrestox.0c00317
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Leveraging the Value of CDISC SEND Data Sets for Cross-Study Analysis: Incidence of Microscopic Findings in Control Animals

Abstract: Implementation of the Clinical Data Interchange Standards Consortium (CDISC)’s Standard for Exchange of Nonclinical Data (SEND) by the United States Food and Drug Administration Center for Drug Evaluation and Research (US FDA CDER) has created large quantities of SEND data sets and a tremendous opportunity to apply large-scale data analytic approaches. To fully realize this opportunity, differences in SEND implementation that impair the ability to conduct cross-study analysis must be addressed. In this manuscr… Show more

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Cited by 8 publications
(3 citation statements)
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“…Therefore, normalization methods were needed to enable comparison of disparate endpoints and to account for these variations ( Carfagna et al, 2024 ). Finally, SEND control data can provide insights into background finding incidence for cohorts of animals; however, access to harmonized SEND data for this purpose may be restrictive for individuals without a programming background ( Carfagna et al, 2021 ). Therefore, there was a need to develop an R Shiny user interface to provide an intuitive front-end for non-programmers to explore their SEND control data ( Chang et al, 2020 ; R Core Team, 2022 ).…”
Section: Introductionmentioning
confidence: 99%
“…Therefore, normalization methods were needed to enable comparison of disparate endpoints and to account for these variations ( Carfagna et al, 2024 ). Finally, SEND control data can provide insights into background finding incidence for cohorts of animals; however, access to harmonized SEND data for this purpose may be restrictive for individuals without a programming background ( Carfagna et al, 2021 ). Therefore, there was a need to develop an R Shiny user interface to provide an intuitive front-end for non-programmers to explore their SEND control data ( Chang et al, 2020 ; R Core Team, 2022 ).…”
Section: Introductionmentioning
confidence: 99%
“…SEND provides standardization and digitization of data to enable the opportunity to perform automated analyses. Application of the SEND standard to enable cross-study analysis requires harmonization of key terms ( Carfagna et al 2021 ). Implementation of data harmonization approaches further enabled the application of SEND data to improve drug development.…”
mentioning
confidence: 99%
“…Several papers discussed in silico approaches for drug safety prediction and evaluation. Carfagna et al 25 illustrated the importance of standards by analyzing microscopic findings in control animals across different study sources which were captured in standard exchange nonclinical data format. Hughes et al 26 discussed the importance of bioactivation and reactivity of drugs.…”
mentioning
confidence: 99%