A computationally efficient algorithm for fitting ion channel parameters

Continuous time Markov models have been widely used to describe ion channel kinetics, providing explicit representation of channel states and transitions. Fitting models to experimental data remains a computationally demanding task largely due to the high cost of model evaluation. Here, we propose a method to efficiently optimize model parameters and structure. Voltage clamp channel protocols can be decomposed into a series of fixed steps of constant voltage resulting in a set of linear systems of differential equations. Given the linear systems, ODE integration can be swapped for the faster matrix exponential routine. With our parallelized implementation, optimized models are able to reproduce a wide range of experimentally collected data within one minute, a 50 times speedup over ODE integration. • The cost of the objective function is reduced by employing the matrix exponential; • The likelihood of convergence is improved by applying synchronous start simulated annealing; • The approach was tested by optimizing parameters for a model of the cardiac voltage-gated Na(+) channel, Na(V)1.5, and the KCNQ1 K(+) channel.