Dataset Information

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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Publications

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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Dataset Information

Multilevel models improve precision and speed of IC50 estimates.

Aim

Materials & methods

Results

Conclusion

Publications

Multilevel models improve precision and speed of IC50 estimates.

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