Quantitative Assessment of the Physiological Parameters Influencing QT Interval Response to Medication: Application of Computational Intelligence Tools.

Sebastian Polak,Aleksander Mendyk,Barbara Wiśniowska,Jakub Szlęk,Adam Pacławski

doi:10.1155/2018/3719703

Sebastian Polak, Aleksander Mendyk + Show 3 more

Open Access

https://doi.org/10.1155/2018/3719703

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Abstract

Human heart electrophysiology is complex biological phenomenon, which is indirectly assessed by the measured ECG signal. ECG trace is further analyzed to derive interpretable surrogates including QT interval, QRS complex, PR interval, and T wave morphology. QT interval and its modification are the most commonly used surrogates of the drug triggered arrhythmia, but it is known that the QT interval itself is determined by other nondrug related parameters, physiological and pathological. In the current study, we used the computational intelligence algorithms to analyze correlations between various simulated physiological parameters and QT interval. Terfenadine given concomitantly with 8 enzymatic inhibitors was used as an example. The equation developed with the use of genetic programming technique leads to general reasoning about the changes in the prolonged QT. For small changes of the QT interval, the drug-related IKr and ICa currents inhibition potentials have major impact. The physiological parameters such as body surface area, potassium, sodium, and calcium ions concentrations are negligible. The influence of the physiological variables increases gradually with the more pronounced changes in QT. As the significant QT prolongation is associated with the drugs triggered arrhythmia risk, analysis of the role of physiological parameters influencing ECG seems to be advisable.

Highlights

Human heart electrophysiology is a complex biological phenomenon, which is indirectly assessed by the measured ECG signal and its derivatives
Analysis of the electrographic biomarkers modification is important from the drug development point of view, namely, assessment of drug cardiovascular safety, as it allows for quantification of drugs’ and drugs candidates’ influence on the human heart electrophysiology [1]
Seven clinical studies focused on the electrophysiological consequences of the drug-drug interactions of terfenadine were mimicked in silico with the use of mechanistic models describing drugs pharmacokinetics and pharmacodynamics (PD)

Summary

Introduction

Human heart electrophysiology is a complex biological phenomenon, which is indirectly assessed by the measured ECG (electrocardiography) signal and its derivatives. Analysis of the electrographic biomarkers modification is important from the drug development point of view, namely, assessment of drug cardiovascular safety, as it allows for quantification of drugs’ and drugs candidates’ influence on the human heart electrophysiology [1]. This is possible because of the well-known correlation between the drugs triggered ionic currents disruption, ECG modification, and subsequent increase in the risk of arrhythmia occurrence [2]. Despite the criticism that the specificity of this proarrhythmia risk surrogate is not ideal, it is still commonly used in the drug development process as well as in the clinic

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