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Cited by 92Animal testing and alternativesComputational Drug Discovery MethodsMathematical Biology Tumor Growth

An unbiased metric of antiproliferative drug effect in vitro

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Harris, Leonard A, Frick, Peter L, Garbett, Shawn P, Hardeman, Keisha N, Paudel, B Bishal, Lopez, Carlos F, Quaranta, Vito, Tyson, Darren R·2016·Nature Methods
DOI 10.1038/nmeth.3852PMC PMC4887341
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Abstract

In vitro cell proliferation assays are widely used in pharmacology, molecular biology, and drug discovery. Using theoretical modeling and experimentation, we show that current metrics of antiproliferative small molecule effect suffer from time-dependent bias, leading to inaccurate assessments of parameters such as drug potency and efficacy. We propose the drug-induced proliferation (DIP) rate, the slope of the line on a plot of cell population doublings versus time, as an alternative, time-independent metric.

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Crossref · 10.1038/nmeth.3852

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  • eGR is similar to the DIP rate and drug-induced GR inhibition, two unbiased metrics of in vitro antiproliferative drug effect.

    “Our method is based on eGR, an unbiased metric of in vivo antiproliferative drug effect (30), which is similar to two unbiased metrics of in vitro antiproliferative drug effect, the DIP rate proposed by Harris and colleagues (33), and the drug-induced GR inhibition by Hafner and colleagues (32), and it offers an easy algebraic way for calculating GR for in vivo studies.”

    From Statistical Assessment of Drug Synergy from <i>In Vivo</i> Combination Studies Using Mouse Tumor Models (2023) · cites this paper as [33]

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Research works printed but not linked: 23

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Authors
Harris, L. A., Frick, P. L., Garbett, S. P., Hardeman, K. N., Paudel, B. B., Lopez, C. F., Quaranta, V., & Tyson, D. R.
Affiliations
Vanderbilt University (US)
Corresponding author
Tyson, Darren R
ORCID
Venue
Nature Methods
Publisher
Springer Science and Business Media LLC
Published
2016-05-02
Volume
13
Issue
6
Pages
497-500
ISSN
  • 1548-7091 (ISSN-L)
  • 1548-7105
DOI
10.1038/nmeth.3852
PMC
PMC4887341
OpenAlex
W2345299709
Cited by
92
References
3
Citations by year
2026: 2 · 2025: 6 · 2024: 6 · 2023: 11 · 2022: 9 · 2021: 14 · 2020: 12 · 2019: 10 · 2018: 8 · 2017: 12 · 2016: 2
FWCI
16.40
Type
journal article
Language
en
Open access
Licence
www.springer.com/tdm (tdm)
Locations
  • Nature Methods (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • arXiv (Cornell University)
Funders
  • National Institutes of Health (UL1TR000445)
  • National Cancer Institute (U54CA113007, R01CA186193, F31CA174365, U01CA174706, P50CA098131, T32CA119925)
  • U.S. National Library of Medicine (T15LM007450)
  • National Center for Advancing Translational Sciences
Topics
  • Health Sciences › Veterinary › Small Animals › Animal testing and alternatives
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
  • Physical Sciences › Mathematics › Modeling and Simulation › Mathematical Biology Tumor Growth
Keywords
antiproliferative agents, cell proliferation assay, time-dependent bias, drug potency, drug efficacy, small molecule drug screening
MeSH terms
Computer Simulation, Dose-Response Relationship, Drug, Humans, Microscopy, Fluorescence, Models, Theoretical, Molecular Biology, Sensitivity and Specificity, Time Factors, Cell Line, Tumor, Cell Proliferation, Small Molecule Libraries, Drug Discovery

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