Glossary of reference terms for alternative test methods and their validation

Ferrario, Daniele; Brustio, Roberta; Hartung, Thomas

doi:10.14573/altex.1403311

Cited by 9 publications

(9 citation statements)

References 14 publications

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“…Bar graphs were used to plot average of QIF scores and percentage of PD-L1+ cells and OD/mm 2 for DAB staining quantified by QuPath, per cell line from for each assay. Due to the complexity of this work, we define the following terms and concepts related to standardization of measurement: reproducibility, a component of the precision, determines the agreement among results obtained from testing the same substance by using the same test protocol under repeatable conditions (different operators, locations and time); correlation, a statistical relationship to quantify the strength of association between two variables; and concordance, the proportion of the outcomes of a specific test which are identical to an agreed upon reference [19][20][21] . Comparison between blocks, antibodies/assays and laboratories was assessed for correlation using a linear regression coefficient (R 2 ) and Bland-Altman plots 22 were used to assess correlation and concordance, respectively, between PD-L1 assays.…”

Section: Discussionmentioning

confidence: 99%

Quantitative assessment of PD-L1 as an analyte in immunohistochemistry diagnostic assays using a standardized cell line tissue microarray

Martinez-Morilla

McGuire

Gaule

et al. 2020

Laboratory Investigation

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Programmed Death 1 Ligand 1 (PD-L1) Immunohistochemistry (IHC) is the key FDA-approved predictive marker to identify responders to anti-PD1 axis drugs. Multiple PD-L1 IHC assays with various antibodies and cut-points have been used in clinical trials across tumor types. Comparative performance characteristics of these assays have been extensively studied qualitatively but not quantitatively. Here we evaluate the use of a standardized PD-L1 Index TMA to objectively determine agreement between antibody assays for PD-L1 applying quantitative digital image analysis. Using a specially constructed Index Tissue Microarray (TMA) containing a panel of 10 isogenic cell lines in triplicate, we tested identical but independently grown batches of isogenic cells to prove Index TMAs can be produced in large quantities and hence serve as a standardization tool. Then the Index TMAs were evaluated using quantitative immunofluorescence (QIF) to validate the TMA itself and also to compare antibodies including E1L3N, SP142 and SP263. Next, an inter-laboratory and inter-assay comparison of 5 PD-L1 chromogenic IHC assays (US Food and Drug Administration (FDA) approved and lab developed test (LDT)) were performed at 12 sites around the USA. As previously reported, the SP142-FDA assay failed to detect low levels of PD-L1 in cell lines distinguished by the other 4 assays. The assays for 22C3-FDA, 28-8-FDA, SP263-FDA and E1L3N-LDT were highly similar across sites and all laboratories showed a high consistency over time for all assays using this Index TMA. In conclusion, we were able to objectively quantify PD-L1 expression on a standardized Index TMA using digital image analysis and we confirmed previous subjective assessments of these assays, but now in a multi-institutional setting. We envision commercial use of this Index TMA or similar smaller version as a useful standardization mechanism to compare results between institutions and to identify abnormalities while running routine clinical samples.

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Section: Discussionmentioning

confidence: 99%

Quantitative assessment of PD-L1 as an analyte in immunohistochemistry diagnostic assays using a standardized cell line tissue microarray

Martinez-Morilla

McGuire

Gaule

et al. 2020

Laboratory Investigation

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“…Extrapolation depends as much on the model system it does on what we measure to characterize the response. The term biomarker is defined as follows 61 : ''Indicator signaling an event or condition in a biological system or sample and giving a measure of exposure, effect, or susceptibility.'' We addressed the biomarkers of in vitro systems in an earlier workshop.…”

Section: Biomarkers-the Meaningful Endpoints To Measurementioning

confidence: 99%

Perspectives onIn VitrotoIn VivoExtrapolations

Hartung

2018

Applied In Vitro Toxicology

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Quantitative in vitro to in vivo extrapolation (QIVIVE) is broadly considered a prerequisite bridge from in vitro findings to a dose paradigm. Quality and relevance of cell systems are the first prerequisite for QIVIVE. Information-rich and mechanistic endpoints (biomarkers) improve extrapolations, but a sophisticated endpoint does not make a bad cell model a good one. The next need is reverse toxicokinetics (TK), which estimates the dose necessary to reach a tissue concentration that is active in vitro. The Johns Hopkins Center for Alternatives to Animal Testing (CAAT) has created a roadmap for animal-free systemic toxicity testing, in which the needs and opportunities for TK are elaborated, in the context of different systemic toxicities. The report was discussed at two stakeholder forums in Brussels in 2012 and in Washington in 2013; the key recommendations are summarized herein. Contrary to common belief and the Paracelsus paradigm of everything is toxic, the majority of industrial chemicals do not exhibit toxicity. Strengthening the credibility of negative results of alternative approaches for hazard identification, therefore, avoids the need for QIVIVE. Here, especially the combination of methods in integrated testing strategies is most promising. Two further but very different approaches aim to overcome the problem of modeling in vivo complexity: The human-on-a-chip movement aims to reproduce large parts of living organism's complexity via microphysiological systems, that is, organ equivalents combined by microfluidics. At the same time, the Toxicity Testing in the 21st Century (Tox-21c) movement aims for mechanistic approaches (adverse outcome pathways as promoted by Organisation for Economic Co-operation and Development (OECD) or pathways of toxicity in the Human Toxome Project) for high-throughput screening, biological phenotyping, and ultimately a systems toxicology approach through integration with computer modeling. These 21st century approaches also require 21st century validation, for example, by evidence-based toxicology. Ultimately, QIVIVE is a prerequisite for extrapolating Tox-21c such approaches to human risk assessment.

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“…As such, the effort needed to construct a robust and credible read-across justification is not trivial. Prediction from data for reference substance(s) within the group or 'category' of substances by interpolation to other substances in the group" (Ferrario et al, 2014).…”

Section: Read-across Considerations Before and During Developmentmentioning

confidence: 99%

Read-across approaches - misconceptions, promises and challenges ahead

Patlewicz

2014

ALTEX

109

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Summary Read-across is a data gap filling technique used within category and analogue approaches. It has been utilized as an alternative approach to address information requirements under various past and present regulatory programs such as the OECD High Production Volume Programme as well as the EU's Registration, Evaluation, Authorisation and restriction of CHemicals (REACH) regulation. Although read-across raises a number of expectations, many misconceptions still remain around what it truly represents; how to address its associated justification in a robust and scientifically credible manner; what challenges/issues exist in terms of its application and acceptance; and what future efforts are needed to resolve them. In terms of future enhancements, read-across is likely to embrace more biologicallyorientated approaches consistent with the Toxicity in the 21 st Century vision (Tox-21c). This Food forThought article, which is notably not a consensus report, aims to discuss a number of these aspects and, in doing so, to raise awareness of the ongoing efforts and activities to enhance read-across. It also intends to set the agenda for a CAAT read-across initiative in 2014CAAT read-across initiative in -2015 to facilitate the proper use of this technique.

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Glossary of reference terms for alternative test methods and their validation

Cited by 9 publications

References 14 publications

Quantitative assessment of PD-L1 as an analyte in immunohistochemistry diagnostic assays using a standardized cell line tissue microarray

Quantitative assessment of PD-L1 as an analyte in immunohistochemistry diagnostic assays using a standardized cell line tissue microarray

Perspectives onIn VitrotoIn VivoExtrapolations

Read-across approaches - misconceptions, promises and challenges ahead

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