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Cited by 13

The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.

Determination of benchmark concentrations and their statistical uncertainty for cytotoxicity test data and functional in vitro assays

Krebs, Alice·2019·ALTEX
DOI 10.14573/altex.1912021
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Abstract

Many toxicological test methods, including assays of cell viability and function, require an evaluation of concentration-response data. This often involves curve fitting, and the resulting mathematical functions are then used to determine the concentration at which a certain deviation from the control value occurs (e.g. a decrease of cell viability by 15%). Such a threshold is called the benchmark response (BMR). For a toxicological test, it is often of interest to determine the concentration of test compound at which a pre-defined BMR of e.g. 10, 25 or 50% is reached. The concentration at which the modelled curve crosses the BMR is called the benchmark concentration (BMC). We present a user-friendly, web-based tool (BMCeasy), designed for operators without programming skills and profound statistical background, to determine BMCs and their confidence intervals. BMCeasy allows simultaneous analysis of viability plus a functional test endpoint, and it yields absolute BMCs with confidence intervals for any BMR. Besides an explanation of the algorithm underlying BMCeasy, this article also gives multiple examples of data outputs. BMCeasy was used within the EU-ToxRisk project for preparing data packages that were submitted to regulatory authorities, demonstrating the real-life applicability of the tool.

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Crossref · 10.14573/altex.1912021

Cites

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Figures

Fig. 1 The benchmark concentration concept for in vitro toxicology data
Fig. 1 The benchmark concentration concept for in vitro toxicology dataCC-BY · From the PDF
Fig. 2 Graphical representation of the absolute versus the relative BMC50
Fig. 2 Graphical representation of the absolute versus the relative BMC50CC-BY · From the PDF
Image 3
CC-BY · From the PDF
Fig. 3 Overview of the different models to fit concentrationresponse data
Fig. 3 Overview of the different models to fit concentrationresponse dataCC-BY · From the PDF
Image 5
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Image 6
CC-BY · From the PDF

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Citations

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Metadata

Authors
Krebs, A.
Venue
ALTEX
Publisher
ALTEX Edition
Published
2019
ISSN
1868-596X
DOI
10.14573/altex.1912021
Cited by
13
References
33

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CoChat. (2026). Citation check: Determination of benchmark concentrations and their statistical uncertainty for cytotoxicity test data and functional in vitro assays. https://app.cochat.ai/papers/10.14573/altex.1912021
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Krebs, A. (2019). Determination of benchmark concentrations and their statistical uncertainty for cytotoxicity test data and functional in vitro assays. ALTEX. https://doi.org/10.14573/altex.1912021

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.