Multilevel models improve precision and speed of IC50 estimates

Pharmacogenomics. 2016 May;17(7):691-700. doi: 10.2217/pgs.16.15. Epub 2016 May 16.


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.

Keywords: IC50; dose–response; mixed effects; nonlinear.

MeSH terms

  • Algorithms
  • Bayes Theorem
  • Cell Line, Tumor
  • Dose-Response Relationship, Drug
  • Drug Resistance, Neoplasm
  • Drug Screening Assays, Antitumor
  • Humans
  • Inhibitory Concentration 50*
  • Models, Biological*
  • Nonlinear Dynamics
  • Pharmacogenomic Testing / methods*
  • Pharmacogenomic Testing / statistics & numerical data
  • Precision Medicine