Integrated Testing Strategy (ITS) – Opportunities to better use existing data and guide future testing in toxicology

Jaworska, Joanna

doi:10.14573/altex.2010.4.231

Cited by 62 publications

(81 citation statements)

References 71 publications

(61 reference statements)

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“…During the past decade, a lot of attention has been dedicated to developing non-animal testing methods and testing strategies for the toxicological endpoint skin sensitisation (Jaworska and Hoffmann, 2010;Jaworska et al, 2011;Hartung et al, 2013;Rovida et al, 2015;Jaworska, 2016). Skin sensitisation is the toxicological endpoint assessing a substance's ability to cause allergic contact dermatitis (ACD) (UNECE, 2011).…”

Section: Addressing the Development Of Efficient Toxicity Testing Strmentioning

confidence: 99%

“…an ACD incident). Since non-animal testing methods are not considered suitable to provide sufficient information to draw conclusions upon the skin sensitisation potential of chemicals (Mehling et al, 2012;Reisinger et al, 2015), a solution suggested is to integrate information from different sources and testing methods by using hypothesis-based approaches such as Bayesian networks (Jaworska and Hoffmann, 2010;Jaworska et al, 2011;Hartung et al, 2013;Jaworska et al, 2013;Jaworska, 2016) or deterministic ITS approaches (Bauch et al, 2012;Urbisch et al, 2015a). For the development of integrated strategies assessing skin sensitisation potential and potency (Jaworska, 2016) different sets of criteria have been proposed including transparency, coherency, ambiguity, or cost effectiveness (Hartung et al, 2013;Rovida et al, 2015) which are applicable also for other toxicological endpoints .…”

Section: Addressing the Development Of Efficient Toxicity Testing Strmentioning

confidence: 99%

“…For skin sensitisation potential and potency assessment criteria for developing nonanimal testing strategies have been suggested in the literature (Jaworska and Hoffmann, 2010;Jaworska et al, 2011;Hartung et al, 2013;Rovida et al, 2015;Jaworska, 2016).…”

Section: Addressing the Development Of Efficient Toxicity Testing Strmentioning

confidence: 99%

“…There is a need (i) to accelerate risk assessment of chemicals in order to fill information gaps for large numbers of chemicals according to the requirements of REACH legislation, (ii) to replace animal testing, and (iii) to account for the limitations of animal tests and standalone nonanimal testing methods for assessing chemicals' hazardous properties. Therefore, several concepts for integrated approaches to testing have been proposed as an innovative solution for the improvement of toxicity testing of chemicals (Grindon et al, 2006a;Nordberg et al, 2008;Jaworska and Hoffmann, 2010;Balls et al, 2012).…”

mentioning

confidence: 99%

“…In particular, the fundamental questions of (i) how to integrate information from different sources in a transparent and coherent way, (ii) how to update information gains across testing sequential steps, (iii) how to quantify and reduce uncertainty across sequential steps, (iv) with which testing method to start a testing sequence, and (v) when to stop testing, have been discussed (Jaworska and Hoffmann, 2010;Jaworska et al, 2011). Answering, however, these questions, is ultimately, an economic optimisation problem (Gabbert and Weikard, 2013).…”

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confidence: 99%

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An economic approach to non-animal toxicity testing for skin sensitisation

Leontaridou¹

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Section: Addressing the Development Of Efficient Toxicity Testing Strmentioning

confidence: 99%

Section: Addressing the Development Of Efficient Toxicity Testing Strmentioning

confidence: 99%

Section: Addressing the Development Of Efficient Toxicity Testing Strmentioning

confidence: 99%

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confidence: 99%

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An economic approach to non-animal toxicity testing for skin sensitisation

Leontaridou¹

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Bayesian integrated testing strategy to assess skin sensitization potency: from theory to practice

Jaworska

Dancik

Kern

et al. 2013

J of Applied Toxicology

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106

131

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Frameworks to predict in vivo effects by integration of in vitro, in silico and in chemico information using mechanistic insight are needed to meet the challenges of 21(st) century toxicology. Expert-based approaches that qualitatively integrate multifaceted data are practiced under the term 'weight of evidence', whereas quantitative approaches remain rare. To address this gap we previously developed a methodology to design an Integrated Testing Strategy (ITS) in the form of a Bayesian Network (BN). This study follows up on our proof of concept work and presents an updated ITS to assess skin sensitization potency expressed as local lymph node assay (LLNA) potency classes. Modifications to the ITS structure were introduced to include better mechanistic information. The parameters of the updated ITS were calculated from an extended data set of 124 chemicals. A detailed validation analysis and a case study were carried out to demonstrate the utility of the ITS for practical application. The improved BN ITS predicted correctly 95% and 86% of chemicals in a test set (n = 21) for hazard and LLNA potency classes, respectively. The practical value of using the BN ITS is far more than a prediction framework when all data are available. The BN ITS can develop a hypothesis using subsets of data as small as one data point and can be queried on the value of adding additional tests before testing is commenced. The ITS represents key steps of the skin sensitization process and a mechanistically interpretable testing strategy can be developed. These features are illustrated in the manuscript via practical examples.

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Towards a Fuzzy Expert System on Toxicological Data Quality Assessment

Yang

Neagu

Cronin

et al. 2013

Molecular Informatics

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Quality assessment (QA) requires high levels of domain-specific experience and knowledge. QA tasks for toxicological data are usually performed by human experts manually, although a number of quality evaluation schemes have been proposed in the literature. For instance, the most widely utilised Klimisch scheme1 defines four data quality categories in order to tag data instances with respect to their qualities; ToxRTool2 is an extension of the Klimisch approach aiming to increase the transparency and harmonisation of the approach. Note that the processes of QA in many other areas have been automatised by employing expert systems. Briefly, an expert system is a computer program that uses a knowledge base built upon human expertise, and an inference engine that mimics the reasoning processes of human experts to infer new statements from incoming data. In particular, expert systems have been extended to deal with the uncertainty of information by representing uncertain information (such as linguistic terms) as fuzzy sets under the framework of fuzzy set theory and performing inferences upon fuzzy sets according to fuzzy arithmetic. This paper presents an experimental fuzzy expert system for toxicological data QA which is developed on the basis of the Klimisch approach and the ToxRTool in an effort to illustrate the power of expert systems to toxicologists, and to examine if fuzzy expert systems are a viable solution for QA of toxicological data. Such direction still faces great difficulties due to the well-known common challenge of toxicological data QA that "five toxicologists may have six opinions". In the meantime, this challenge may offer an opportunity for expert systems because the construction and refinement of the knowledge base could be a converging process of different opinions which is of significant importance for regulatory policy making under the regulation of REACH, though a consensus may never be reached. Also, in order to facilitate the implementation of Weight of Evidence approaches and in silico modelling proposed by REACH, there is a higher appeal of numerical quality values than nominal (categorical) ones, where the proposed fuzzy expert system could help. Most importantly, the deriving processes of quality values generated in this way are fully transparent, and thus comprehensible, for final users, which is another vital point for policy making specified in REACH. Case studies have been conducted and this report not only shows the promise of the approach, but also demonstrates the difficulties of the approach and thus indicates areas for future development.

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Integrated Testing Strategy (ITS) – Opportunities to better use existing data and guide future testing in toxicology

Cited by 62 publications

References 71 publications

An economic approach to non-animal toxicity testing for skin sensitisation

An economic approach to non-animal toxicity testing for skin sensitisation

Bayesian integrated testing strategy to assess skin sensitization potency: from theory to practice

Towards a Fuzzy Expert System on Toxicological Data Quality Assessment

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