Hierarchical Bayesian inference for ion channel screening dose-response data [version 2; peer review: 2 approved]

Johnstone, Ross H; Gavaghan, David J; Johnstone, Ross H.; Bardenet, R�mi; Gavaghan, David J.; Mirams, Gary R

Abstract

Dose-response (or 'concentration-effect') relationships commonly occur in biological and pharmacological systems and are well characterised by Hill curves. These curves are described by an equation with two parameters: the inhibitory concentration 50% (IC50); and the Hill coefficient. Typically just the 'best fit' parameter values are reported in the literature. Here we introduce a Python-based software tool, PyHillFit , and describe the underlying Bayesian inference methods that it uses, to infer probability distributions for these parameters as well as the level of experimental observation noise. The tool also allows for hierarchical fitting, characterising the effect of inter-experiment variability. We demonstrate the use of the tool on a recently published dataset on multiple ion channel inhibition by multiple drug compounds. We compare the maximum likelihood, Bayesian and hierarchical Bayesian approaches. We then show how uncertainty in dose-response inputs can be characterised and propagated into a cardiac action potential simulation to give a probability distribution on model outputs.

Citation

Johnstone, R. H., Gavaghan, D. J., Johnstone, R. H., Bardenet, R., Gavaghan, D. J., & Mirams, G. R. (2017). Hierarchical Bayesian inference for ion channel screening dose-response data [version 2; peer review: 2 approved]. Wellcome Open Research, 1, 1-23. https://doi.org/10.12688/wellcomeopenres.9945.2

• Journal Article Type: Article
• Acceptance Date: Mar 10, 2017
• Online Publication Date: Mar 13, 2017
• Publication Date: Mar 13, 2017
• Deposit Date: May 10, 2017
• Publicly Available Date: May 10, 2017
• Journal: Wellcome Open Research
• Electronic ISSN: 2398-502X
• Publisher: F1000Research
• Peer Reviewed: Peer Reviewed
• Volume: 1
• Article Number: 6
• Pages: 1-23
• DOI: https://doi.org/10.12688/wellcomeopenres.9945.2
• Public URL: https://nottingham-repository.worktribe.com/output/850025
• Publisher URL: https://wellcomeopenresearch.org/articles/1-6/v2