Integrated Approaches to Testing and Assessment
Traditional toxicity testing approaches using laboratory animals are expensive and time-consuming, and the use of animals raises both ethical concerns and issues of interspecies differences. The drawbacks of traditional testing may be overcome by the use of human cell-based, biochemical, and/or computational methods to predict chemical toxicity. But because of the complexity of toxicity mechanisms, data from several methods usually need to be considered in combination to adequately predict toxic effects.
Integrated approaches to testing and assessment (IATAs) use an iterative approach to answer a defined hazard characterization question within a specific regulatory context. An IATA integrates and weights all relevant and reliable existing information about a chemical, such as toxicity data, exposure routes, use cases, and production volumes; guides the targeted generation of new data, preferably using non-animal approaches, to inform regulatory decision-making; and provides a conclusion, sometimes based on expert judgment, that can inform regulatory decision-making. Read More
A defined approach to testing and assessment can be used as part of an IATA or on its own to satisfy a need for hazard information. A defined approach consists of input data generated from identified methods and a data interpretation procedure, such as a machine-learning model, flowchart, or decision tree, through which the data are evaluated. Defined approaches are rule-based and do not utilize expert judgment. Input data may be derived from in vitro test methods or from computational approaches such as “read-across,” in which toxicity data from a known chemical is used to predict toxicity for another, similar chemical. The input data is run through the data interpretation procedure to generate a hazard prediction. Read More
Two examples of defined approaches: sequential testing strategies and integrated testing strategies.
- A sequential testing strategy is a fixed stepwise approach for obtaining and assessing test data. It includes interim decision points at which the user may either proceed to additional testing steps or stop testing and make a hazard prediction.
- An integrated testing strategy is an approach in which multiple sources of data or information are assessed at the same time to arrive at either a hazard prediction or a decision that more testing is needed.
More information about IATAs and defined approaches is available on the website of the Organisation for Economic Co-operation and Development.
NICEATM and its collaborators have developed integrated testing strategies to identify potential skin sensitizers (substances with the potential to cause allergic contact dermatitis).
- NICEATM and other NTP scientists collaborated with Procter & Gamble to develop an open-source version of a previously published proprietary integrated testing strategy.
- NICEATM and ICCVAM developed integrated testing strategies that use data from three non-animal tests, read-across predictions of skin sensitization hazard, and physical properties such as partition coeffiecient to predict skin sensitization hazard and potency.
- NICEATM and industry scientists from Cosmetics Europe are writing open-source code to reproduce defined approaches submitted to the OECD for skin sensitization testing and assessment.
Integrated Testing Strategy to Identify Potential Endocrine Disruptors
NICEATM validated an integrated testing strategy developed by EPA that combines data from 18 high throughput screening assays with a computational model to identify chemicals with the potential to interact with the estrogen receptor. Use of this integrated testing strategy has been accepted by the EPA as an alternative to three assays currently used in its Endocrine Disruptor Screening Program Tier I battery.
Browne et al. 2015. Screening chemicals for estrogen receptor bioactivity using a computational model. Environ Sci Technol 49:8804-8814.
Similarly, NICEATM and EPA have developed an integrated testing strategy that combines data from 11 high throughput screening assays with a computational model to identify chemicals with the potential to interact with the androgen receptor. EPA is currently considering whether this approach is potentially useful for replacement of existing tests currently required in the Endocrine Disruptor Screening Program.
Kleinstreuer et al. 2017. Development and validation of a computational model for androgen receptor activity. Chem Res Toxicol 30(4):946-964.