Multilevel models improve precision and speed of IC50 estimates

Daniel J. Vis, Lorenzo Bombardelli, Howard Lightfoot, Francesco Iorio, MJ Garnett, Lodewyk Wessels

Research output: Contribution to journalArticleScientificpeer-review

16 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)691-700
Number of pages10
JournalPharmacogenomics
Volume17
Issue number7
DOIs
Publication statusPublished - 2016

Keywords

  • dose–response
  • IC50
  • mixed effects
  • nonlinear

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