A normalized drug response metric improves accuracy and consistency of anticancer drug sensitivity quantification in cell-based screening

dc.contributor.authorGupta A
dc.contributor.authorGautam P
dc.contributor.authorWennerberg K
dc.contributor.authorAittokallio T
dc.contributor.organizationfi=matematiikka|en=Mathematics|
dc.contributor.organization-code1.2.246.10.2458963.20.41687507875
dc.converis.publication-id46066102
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/46066102
dc.date.accessioned2022-10-28T14:10:29Z
dc.date.available2022-10-28T14:10:29Z
dc.description.abstractAccurate quantification of drug effects is crucial for identifying pharmaceutically actionable cancer vulnerabilities. Current cell viability-based measurements often lead to biased response estimates due to varying growth rates and experimental artifacts that explain part of the inconsistency in high-throughput screening results. We developed an improved drug scoring model, normalized drug response (NDR), which makes use of both positive and negative control conditions to account for differences in cell growth rates, and experimental noise to better characterize drug-induced effects. We demonstrate an improved consistency and accuracy of NDR compared to existing metrics in assessing drug responses of cancer cells in various culture models and experimental setups. Notably, NDR reliably captures both toxicity and viability responses, and differentiates a wider spectrum of drug behavior, including lethal, growth-inhibitory and growth-stimulatory modes, based on a single viability readout. The method will therefore substantially reduce the time and resources required in cell-based drug sensitivity screening.Abhishekh Gupta et al. present a normalized drug response (NDR) metric for accurate quantification of drug sensitivity in cell-based high-throughput assays. They show that NDR captures both toxicity and viability responses to improve drug effect classification over existing methods.
dc.identifier.eissn2399-3642
dc.identifier.olddbid186708
dc.identifier.oldhandle10024/169802
dc.identifier.urihttps://www.utupub.fi/handle/11111/39497
dc.identifier.urlhttps://www.nature.com/articles/s42003-020-0765-z
dc.identifier.urnURN:NBN:fi-fe2021042825411
dc.language.isoen
dc.okm.affiliatedauthorAittokallio, Tero
dc.okm.discipline111 Mathematicsen_GB
dc.okm.discipline111 Matematiikkafi_FI
dc.okm.internationalcopublicationinternational co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA1 ScientificArticle
dc.publisherNATURE PUBLISHING GROUP
dc.publisher.countryUnited Kingdomen_GB
dc.publisher.countryBritanniafi_FI
dc.publisher.country-codeGB
dc.relation.articlenumber42
dc.relation.doi10.1038/s42003-020-0765-z
dc.relation.ispartofjournalCommunications Biology
dc.relation.issue1
dc.relation.volume3
dc.source.identifierhttps://www.utupub.fi/handle/10024/169802
dc.titleA normalized drug response metric improves accuracy and consistency of anticancer drug sensitivity quantification in cell-based screening
dc.year.issued2020

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