Skin sensitization in silico protocol
Candice Johnson, Ernst Ahlberg, Lennart T. Anger, Lisa Beilke, Romualdo Benigni, Joel P. Bercu, Sol Bobst, David Bower, Alessandro Brigo, Sarah Campbell, M Cronin, Ian Crooks, Kevin P. Cross, Tatyana Y. Doktorova, Thomas E. Exner, David Faulkner, Ian M. Fearon, Markus Fehr, Shayne C. Gad, Véronique Gervais, Amanda Giddings, Susanne Glowienke, Barry Hardy, Catrin Hasselgren, Jedd Hillegass, Robert A. Jolly, Eckart Krupp, Liat Lomnitski, Jason Magby, Jordi Mestres, Lawrence Milchak, Scott A. Miller, Wolfgang Muster, Louise Neilson, R. Parakhia, Alexis Parenty, Patricia Parris, Alexandre Tadeu Paulino, Ana Theresa Paulino, David W. Roberts, Harald Schlecker, Reinhard Stidl, Diana Suarez-Rodrigez, David T. Szabo, Raymond R. Tice, Daniel Urbisch, Anna Vuorinen, B. Wall, Thibaud Weiler, Angela White, Jessica Whritenour, Joerg Wichard, David Woolley, Craig Zwickl, Glenn J. Myatt
Abstract
The assessment of skin sensitization has evolved over the past few years to include in vitro assessments of key events along the adverse outcome pathway and opportunistically capitalize on the strengths of in silico methods to support a weight of evidence assessment without conducting a test in animals. While in silico methods vary greatly in their purpose and format; there is a need to standardize the underlying principles on which such models are developed and to make transparent the implications for the uncertainty in the overall assessment. In this contribution, the relationship between skin sensitization relevant effects, mechanisms, and endpoints are built into a hazard assessment framework. Based on the relevance of the mechanisms and effects as well as the strengths and limitations of the experimental systems used to identify them, rules and principles are defined for deriving skin sensitization in silico assessments. Further, the assignments of reliability and confidence scores that reflect the overall strength of the assessment are discussed. This skin sensitization protocol supports the implementation and acceptance of in silico approaches for the prediction of skin sensitization.