Open source software implementation of an integrated testing strategy for skin sensitization potency based on a Bayesian network

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Jason R. Pirone
Marjolein Smith
Nicole C. Kleinstreuer
Thomas A. Burns
Judy Strickland
Yuri Dancik
Richard Morris
Lori A. Rinckel
Warren Casey
Joanna S. Jaworska

Abstract

An open source implementation of a previously published integrated testing strategy (ITS) for skin sensitization using a Bayesian network has been developed using R, a free and open source statistical computing language. The ITS model provides probabilistic predictions of skin sensitization potency based on in silico and in vitro information as well as skin penetration characteristics from a published bioavailability model (Kasting et al., 2008). The structure of the Bayesian network was designed to be consistent with the adverse outcome pathway published by the OECD (Jaworska et al., 2011, 2013). In this paper, the previously published data set (Jaworska et al., 2013) is improved by two data corrections and a modified application of the Kasting model. The new data set implemented in the original commercial software package and the new R version produced consistent results. The data and a fully documented version of the code are publicly available (http://ntp.niehs.nih.gov/go/its).

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How to Cite
[1]
Pirone, J., Smith, M., Kleinstreuer, N., Burns, T., Strickland, J., Dancik, Y., Morris, R., Rinckel, L., Casey, W. and Jaworska, J. 2014. Open source software implementation of an integrated testing strategy for skin sensitization potency based on a Bayesian network. ALTEX - Alternatives to animal experimentation. 31, 3 (Aug. 2014), 336-340. DOI:https://doi.org/10.14573/altex.1310151.
Section
Short communications