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Multilevel models improve precision and speed of IC50 estimates.

ABSTRACT: AIM:Experimental variation in dose-response data of drugs tested on cell lines result in inaccuracies in the estimate of a key drug sensitivity characteristic: the IC50. We aim to improve the precision of the half-limiting dose (IC50) estimates by simultaneously employing all dose-responses across all cell lines and drugs, rather than using a single drug-cell line response. MATERIALS & METHODS:We propose a multilevel mixed effects model that takes advantage of all available dose-response data. RESULTS:The new estimates are highly concordant with the currently used Bayesian model when the data are well behaved. Otherwise, the multilevel model is clearly superior. CONCLUSION:The multilevel model yields a significant reduction of extreme IC50 estimates, an increase in precision and it runs orders of magnitude faster.

SUBMITTER: Vis DJ

PROVIDER: S-EPMC6455999 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

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Multilevel models improve precision and speed of IC50 estimates.

Vis Daniel J DJ Bombardelli Lorenzo L Lightfoot Howard H Iorio Francesco F Garnett Mathew J MJ Wessels Lodewyk Fa LF

Pharmacogenomics 20160516 7

<h4>Aim</h4>Experimental variation in dose-response data of drugs tested on cell lines result in inaccuracies in the estimate of a key drug sensitivity characteristic: the IC50. We aim to improve the precision of the half-limiting dose (IC50) estimates by simultaneously employing all dose-responses across all cell lines and drugs, rather than using a single drug-cell line response.<h4>Materials & methods</h4>We propose a multilevel mixed effects model that takes advantage of all available dose-r ...[more]

PMID: 27180993

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Multilevel models improve precision and speed of IC50 estimates.

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Multilevel models improve precision and speed of IC50 estimates.

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