Integrated Testing Strategies to Identify Potential Skin Sensitizers

An integrated testing strategy is a type of defined approach to testing and assessment that relies on:

  • Input data generated from identified methods
  • A data interpretation procedure such as a machine-learning model, flowchart, or decision tree, through which the data are evaluated
  • A simultaneous assessment of the input data to arrive at either a hazard prediction or a decision that more testing is needed

More about defined approaches to testing and assessment

An adverse outcome pathway can provide a framework for the development of an integrated testing strategy or a defined approach to testing and assessment. An AOP is a conceptual model that links an exposure to a substance to a toxic effect by identifying the sequence of biochemical events required to produce that toxic effect. In vitro methods that observe or measure the individual events within an AOP can be used as elements of an integrated testing strategy to generate a prediction of whether a chemical might produce that toxic effect. Read More

Substances with the potential to cause allergic contact dermatitis are known as skin sensitizers, and skin sensitization is the process by which a sensitizer induces allergic contact dermatitis. The key biological events of skin sensitization initiated through covalent binding to skin proteins are well characterized and form the basis for an AOP for skin sensitization. NICEATM, working with NTP, ICCVAM, and industry scientists, is creating integrated testing strategies to identify potential skin sensitizers based on this AOP.

Integrated Testing Strategy Developed by ICCVAM

The evaluation and promotion of alternative approaches to replace, reduce, or refine animal use for potential skin sensitizer identification is an ICCVAM priority. NICEATM and ICCVAM developed an integrated testing strategy that uses non-animal data to predict skin sensitization hazard. This integrated testing strategy combines inputs from several sources (data from the direct peptide reactivity assay, the KeratinoSens assay, and the human cell line activation test; a read-across prediction of skin sensitization hazard generated by the QSAR Toolbox software package; and physical property data such as partition coefficients) to predict skin sensitization hazard and potency. Read More

ICCVAM developed three versions of the skin sensitization integrated testing strategy
  • The first version uses computer algorithms to integrate data to predict murine local lymph node assay outcomes.
    Strickland et al. 2016. Integrated decision strategies for skin sensitization hazard. J Appl Toxicol 36(9):1150-62.
  • The second version uses data from human exposures to predict human skin sensitization hazard.
    Strickland et al. 2017. Multivariate models for prediction of skin sensitization hazard. J Appl Toxicol 37(3):347-360.
  • Further development of this approach aimed to predict human or animal skin sensitization potency, enabling the classification of skin sensitizers as “weak” or “strong” without animal tests.
    Zang et al. 2017. Prediction of skin sensitization potency using machine learning approaches. J Appl Toxicol 37(7):792-805.

NICEATM Collaboration With P&G to Develop an Open-source Integrated Testing Strategy

NICEATM and other NTP scientists collaborated with scientists at Procter & Gamble (P&G) to develop an integrated testing strategy to identify potential skin sensitizers without conducting animal tests. Using data from non-animal tests and other information such as solubility and computational predictions of skin sensitizer activity, the strategy produces a numerical probability that a chemical should be placed in a particular skin sensitization hazard class: strong, moderate, weak, or nonsensitizer. This probability could potentially be used to determine if a substance requires hazard labeling without conducting animal tests. P&G and NTP scientists collaborated to develop this integrated testing strategy using free, publicly available software. The goal is to encourage organizations worldwide to use this approach for identifying potential skin sensitizers and support the elimination of animal testing in this area. Read More

Pirone et al. 2014. Open source software implementation of an integrated testing strategy for skin sensitization potency based on a Bayesian network. ALTEX 31:336-340.

P&G updated the integrated testing strategy in 2015. The updated strategy uses only validated non-animal tests, simplifies the bioavailability inputs, and nearly doubles the size of the database used to derive the previous network. The updated P&G integrated strategy is the basis for a free web tool produced by Douglas Connect that can be used to predict skin sensitization potency of a chemical.

Jaworska et al. 2015. Bayesian integrated testing strategy (ITS) for skin sensitization potency assessment: a decision support system for quantitative weight of evidence and adaptive testing strategy. Arch Toxicol 89: 2355-2383.

Files for Running the Open-source Integrated Testing Strategy Analysis

Files to run the analysis described in Pirone et al., including a script that uses the R programming language, are available below. To encourage collaboration and sharing of best practices, NICEATM has established a user community for the integrated test strategy via an NIH listserv. We strongly encourage all users of the R script to join the listserv.

Additional Resources

A bioavailability calculator is available from the National Institute for Occupational Safety and Health (NIOSH) website
Please note that Java must be enabled in your web browser in order to run the calculator.

The software for running R can be obtained from the R Project website
Refer to the FAQs on the R Project website for system requirements and installation instructions.

The OECD QSAR Toolbox can be obtained from the OECD website
Installation instructions and user documentation are available on this page.

NICEATM Murine Local Lymph Node Assay (LLNA) Database

On behalf of ICCVAM, NICEATM conducted a number of analyses to evaluate the usefulness of the LLNA to identify potential skin sensitizers. Data from these analyses are available to interested stakeholders as a reference for developing and evaluating alternative approaches to testing and assessment that replace, reduce, or refine the use of animals for identification of potential skin sensitizers.


Notes for Database Users
  • The Excel spreadsheet contains three pages: (1) data, (2) references, and (3) abbreviations.
  • The database includes data published through 2010.
  • These data have been extracted from published and unpublished data sources with permission. Users of this database should consult the original data source for questions regarding data quality and/or authenticity.