Evaluating the predictive accuracy of ion channel models using data from multiple experimental designs

Shuttleworth, Joseph G.; Lei, Chon Lok; Windley, Monique J.; Hill, Adam P.; Preston, Simon P.; Mirams, Gary R.

Abstract

Mathematical models are increasingly being relied upon to provide quantitatively accurate predictions of cardiac electrophysiology. Many such models concern the behaviour of particular subcellular components (namely, ion channels) which, together, allow the propagation of electrical signals through heart-muscle tissue—namely, the firing of action potentials. In particular, IKr, a voltage-sensitive potassium ion-channel current, is of interest owing to its central pore’s propensity for blockage by various small molecules. We use newly collected data obtained from an ensemble of voltage-clamp experiments to validate the predictive accuracy of various dynamical models of IKr. To do this, we fit models to each protocol individually, and quantify the error in the resultant model predictions. This allows the comparison of predictive accuracy for IKr models under a diverse collection of previously unexplored dynamics. Our results highlight heterogeneity between parameter estimates obtained from different cells, suggesting the presence of latent effects not yet accounted for in our models. This heterogeneity has a significant impact on our parameter estimates and suggests routes for model improvement.

Citation

Shuttleworth, J. G., Lei, C. L., Windley, M. J., Hill, A. P., Preston, S. P., & Mirams, G. R. Evaluating the predictive accuracy of ion channel models using data from multiple experimental designs

• Working Paper Type: Preprint
• Deposit Date: Sep 1, 2024
• Publicly Available Date: Sep 3, 2024
• DOI: https://doi.org/10.1101/2024.08.16.608289
• Public URL: https://nottingham-repository.worktribe.com/output/38649731
• Publisher URL: https://www.biorxiv.org/content/10.1101/2024.08.16.608289v1
• Additional Information: This article is a preprint and has not been certified by peer review.