Quantification and classification of potassium and calcium disorders with the electrocardiogram: What do clinical studies, modeling, and reconstruction tell us?

Diseases caused by alterations of ionic concentrations are frequently observed challenges and play an important role in clinical practice. The clinically established method for the diagnosis of electrolyte concentration imbalance is blood tests. A rapid and non-invasive point-of-care method is yet needed. The electrocardiogram (ECG) could meet this need and becomes an established diagnostic tool allowing home monitoring of the electrolyte concentration also by wearable devices. In this review, we present the current state of potassium and calcium concentration monitoring using the ECG and summarize results from previous work. Selected clinical studies are presented, supporting or questioning the use of the ECG for the monitoring of electrolyte concentration imbalances. Differences in the findings from automatic monitoring studies are discussed, and current studies utilizing machine learning are presented demonstrating the potential of the deep learning approach. Furthermore, we demonstrate the potential of computational modeling approaches to gain insight into the mechanisms of relevant clinical findings and as a tool to obtain synthetic data for methodical improvements in monitoring approaches

Electrocardiogram Signal Analysis and Simulations for Non-Invasive Diagnosis - Model-Based and Data-Driven Approaches for the Estimation of Ionic Concentrations and Localization of Excitation Origins

Das Elektrokardiogramm (EKG) ist die Standardtechnik zur Messung der elektrischen Aktivität des Herzens. EKG-Geräte sind verfügbar, kostengünstig und erlauben zudem eine nichtinvasive Messung. Das ist insbesondere wichtig für die Diagnose von kardiovaskulären Erkrankungen (KVE). Letztere sind mit verursachten Kosten von 210 Milliarden Euro eine der Hauptbelastungen für das Gesundheitssystem in Europa und dort der Grund für 3,9 Millionen Todesfälle – dies entspricht 45% aller Todesfälle. Neben weiteren Risikofaktoren spielen chronische Nierenerkrankungen und strukturelle Veränderungen des Herzgewebes eine entscheidende Rolle für das Auftreten von KVE. Deshalb werden in dieser Arbeit zwei Pathologien, die in Verbindung zu KVE stehen, betrachtet: Elektrolytkonzentrationsveränderungen bei chronisch Nierenkranken und ektope Foki, die autonom Erregungen iniitieren. In beiden Projekten ist die Entwicklung von Methoden mithilfe von simulierten Signalen zur Diagnoseunterstützung das übergeordnete Ziel. Im ersten Projekt helfen simulierte EKGs die Signalverarbeitungskette zur EKG-basierten Schätzung der Ionenkonzentrationen von Kalium und Calcium zu optimieren. Die Erkenntnisse dieser Optimierung fließen in zwei patienten-spezifische Methoden zur Kaliumkonzentrationsschätzung ein, die wiederum mithilfe von Patientendaten ausgewertet werden. Die Methoden lieferten im Mittel einen absoluten Fehler von 0,37 mmol/l für einen patienten-spezifischen Ansatz und 0,48 mmol/l für einen globalen Ansatz mit zusätzlicher patienten-spezifischer Korrektur. Die Vorteile der Schätzmethoden werden gegenüber bereits existierender Ansätze dargelegt. Alle entwickelten Algorithmen sind ferner unter einer Open-Source-Lizenz veröffentlicht. Das zweite Projekt zielte auf die Lokalisierung von ektopen Foki mithilfe des EKGs ohne die Nutzung der individuellen Patientengeometrie. 1.766.406 simulierte EKG-Signale (Body Surface Potential Maps (BSPMs)) wurden zum Trainieren von zwei Convolutional Neural Networks (CNNs) erzeugt. Das erste CNN sorgt für die Schätzung von Anfang und Ende der Depolarisation der Ventrikel. Das zweite CNN nutzt die Information der Depolarisation im BSPM zur Schätzung des Erregungsurpsrungs. Der spezielle Aufbau des CNNs ermöglicht die Darstellung mehrerer Lösungen, wie sie durch Mehrdeutigkeiten im BSPM vorliegen können. Der kleinste Median des Lokalisierungsfehlers lag bei 1,54 mm für den Test-Datensatz der simulierten Signale, bzw. bei 37 mm für Patientensignale. Somit erlaubt die Kombination beider CNNs die verlässliche Lokalisierung von ektopen Foki auch anhand von Patientendaten, obwohl Patientendaten vorher nicht im Training genutzt wurden. Die Resultate dieser zwei Projekte demonstrieren, wie EKG-Simulationen zur Entwicklung und Verbesserung von EKG-Signalverarbeitungsmethoden eingesetzt werden und bei der Diagnosefindung helfen können. Zudem zeigt sich das Potential der Kombination von Simulationen und CNNs, um einerseits die zumeist raren klinischen Signale zu ersetzen und andererseits Modelle zu finden, die für mehrere Patienten/-innen gültig sind. Die vorgestellten Methoden bergen die Möglichkeit, die Diagnosestellungen zu beschleunigen und mit hoher Wahrscheinlichkeit den Therapieerfolg der Patienten zu verbessern

Advances in Digital Processing of Low-Amplitude Components of Electrocardiosignals

This manual has been published within the framework of the BME-ENA project under the responsibility of National Technical University of Ukraine. The BME-ENA “Biomedical Engineering Education Tempus Initiative in Eastern Neighbouring Area”, Project Number: 543904-TEMPUS-1-2013-1-GR-TEMPUS-JPCR is a Joint Project within the TEMPUS IV program. This project has been funded with support from the European Commission.Навчальний посібник присвячено розробці методів та засобів для неінвазивного виявлення та дослідження тонких проявів електричної активності серця. Особлива увага приділяється вдосконаленню інформаційного та алгоритмічного забезпечення систем електрокардіографії високого розрізнення для ранньої діагностики електричної нестабільності міокарда, а також для оцінки функціонального стану плоду під час вагітності. Теоретичні основи супроводжуються прикладами реалізації алгоритмів за допомогою системи MATLAB. Навчальний посібник призначений для студентів, аспірантів, а також фахівців у галузі біомедичної електроніки та медичних працівників.The teaching book is devoted to development and research of methods and tools for non-invasive detection of subtle manifistations of heart electrical activity. Particular attention is paid to the improvement of information and algorithmic support of high resolution electrocardiography for early diagnosis of myocardial electrical instability, as well as for the evaluation of the functional state of the fetus during pregnancy examination. The theoretical basis accompanied by the examples of implementation of the discussed algorithms with the help of MATLAB. The teaching book is intended for students, graduate students, as well as specialists in the field of biomedical electronics and medical professionals

Characterization of t wave amplitude, duration and morphology changes during hemodialysis: Relationship with serum electrolyte levels and heart rate

Objective: Chronic kidney disease affects more than 10% of the world population. Changes in serum ion concentrations increase the risk for ventricular arrhythmias and sudden cardiac death, particularly in end stage renal disease (ESRD) patients. We characterized how T wave amplitude, duration and morphology descriptors change with variations in serum levels of potassium and calcium and in heart rate, both in ESRD patients and in simulated ventricular fibers. Methods: Electrocardiogram (ECG) recordings from twenty ESRD patients undergoing hemodialysis (HD) and pseudo-ECGs (pECGs) calculated from twenty-two simulated ventricular fibers at varying transmural heterogeneity levels were processed to quantify T wave width (Tw), T wave slope-to-amplitude ratio (TS/A) and four indices of T wave morphological variability based on time warping (dw, dNLw, da and dNLa). Serum potassium and calcium levels and heart rate were measured along HD. Results: dNL with serum potassium, dw with calcium and da with heart rate, after correction for covariates. Median values of partial correlation coefficients were 0.75,−0.74 and −0.90, respectively. For all analyzed T wave descriptors, high inter-patient variability was observed in the pattern of such relationships. This variability, accentuated during the first HD time points, was reproduced in the simulations and shown to be influenced by differences in transmural heterogeneity. Conclusion: Changes in serum potassium and calcium levels and in heart rate strongly affect T wave descriptors, particularly those quantifying morphological variability. Significance: ECG markers have the potential to be used for monitoring serum ion concentrations in ESRD patients

Estimation of Serum Potassium and Calcium Concentrations from Electrocardiographic Depolarization and Repolarization Waveforms

Chronic kidney disease (CKD), a condition defined by a gradual decline in kidney function over time, has become a global health concern affecting between 11 and 13% of the world population [1]. As renal function declines, CKD patients gradually lose their ability to maintain normal values of potassium concentration ([K+]) in their blood. Elevated serum [K+], known as hyperkalemia, increases the risk for life-threatening arrhythmias and sudden cardiac death [2].An increase in serum [K+] outside the physiological range is commonly silent and is only detected when hyperkalemia is already very severe or when a blood test is performed. Maintenance and monitoring of [K+] in the blood is an important component in the treatment of CKD patients because therapies for hyperkalemia management in CKD patients are designed to prevent arrhythmias and to immediately lower serum [K+] to safe ranges. However, this is currently only possible by taking a blood sample and is associated with a long analysis time. Therefore it is useful to have a simple, noninvasive method to estimate serum [K+], particularly using the electrocardiogram (ECG). Indeed, variations in serum electrolyte levels have been shown to alter the electrical behavior of the heart and to induce changes in the ECG [3¿6]. However, large inter-individual variability existsin the relationship between ion concentrations and ECG features. Previous attempts to estimate serum [K+] from the ECG have therefore shown limitations [7¿9], such as not being applicable to some common types of ECG waveforms or relying on specific ECG characteristics that may present large variations not necessarily associated with hyperkalemia.The aim of this thesis is to develop novel estimates of serum [K+] that are robust enough to detect hypokalemia (reduced [K+]) or hyperkalemia in a timely manner to provide life-saving treatment. Additionally, the effect of changes in other electrolyte levels, like calcium concentration ([Ca2+]), and in heart rate are investigated. These aims are achieved by combining novel ECG signal processing techniques with in silico modeling and simulation of cardiac electrophysiology.The specific objectives are:1. Characterization of hypokalemia or hyperkalemia and hypocalcemia (reduced [Ca2+]) or hypercalcemia (elevated [Ca2+])-induced changes in ventricular repolarization from ECGs (T wave) of CKD patients. This is addressed in chapter 3 and chapter 4. In these chapters, we describe how T waves are extracted from ECGs and how we characterize changes in T waves at varying potassium, calcium and heart rate using analyses based on time warping and Lyapunov exponents. Next, univariable and multivariable regression models including markers of T wave nonlinear dynamics in combination with warping-based markers of T wave morphology are built and their performance for [K+] estimation is assessed.2. Characterization of hypo- or hyperkalemia and hypo- or hypercalcemia-induced changes in ventricular depolarization from the QRS complex of CKD patients. This is reported in chapter 5. In this chapter, we present how QRS complexes from ECGs of CKD patients are processed and how we measure changes at varying [K+], [Ca2+] and heart rate. Univariate and multivariate regression analyses including novel QRS morphological markers in combination with T wave morphological markers are performed to assess the contribution of depolarization and repolarization features for electrolyte monitoring in CKD patients.3. Identification of potential sources underlying inter-individual variability in ECG markers in response to changes in [K+] and [Ca2+]. In silico investigations of cardiac electrophysiology are conducted and ECG features are computed. Simulation results are compared with patient data. This is explained in chapter 3 using one-dimensional (1D) fibers and in chapter 6 using three-dimensional (3D) human heart-torso models. Chapter 6 includes the development of a population of realistic computational models of human ventricular electrophysiology, based on human anatomy and electrophysiology, to better understand how changes in individual characteristics influence the ECG (QRS and T wave) markers that we introduced in previous chapters. ECG waveforms are characterized by their amplitude, duration and morphology. Simulations are performed with the most realistic available techniques to model the electrophysiology of the heart and the resulting ECG. We establish mechanisms that contribute to inter-individual differences in the characterized ECG features.In conclusion, we identify several markers of ECG morphology, including depolarization and repolarization features, that are highly correlated with serum electrolyte (potassium and calcium) concentrations. ECG morphological variability markers vary significantly with [K+] and [Ca2+] in both simulated and measured ECGs, with a wide range of patterns observed for such relationships. The proportions of endocardial, midmyocardial and epicardial cells have a large impact on ECG markers, particularly for serum electrolyte concentrations out of their physiological levels. This suggests that transmural heterogeneities can modulate ECG responses to changes in electrolyte concentrations in CKD patients. Agreement between actual potassium and calcium levels and their estimates derived from the ECG is promising, with lower average errors than previously proposed markers in the literature. These findings can have major relevance for noninvasive monitoring of serum electrolyte levels and prediction of arrhythmic events in these patients.<br /

Effects of Serum Calcium Changes on the Cardiac Action Potential and the ECG in a Computational Model

Patients suffering from end stage of chronic kid ney disease (CKD) often undergo haemodialysis to normaliz the electrolyte concentrations. Moreover, cardiovascula disease (CVD) is the main cause of death in CKD patients To study the connection between CKD and CVD, we investi gated the effects of an electrolyte variation on cardiac signal (action potential and ECG) using a computational model. In first step, simulations with the Himeno et al. ventricular cel model were performed on cellular level with different extra cellular sodium ([Na+]o), calcium ([Ca2+]o) and potassium ([K+]o) concentrations as occurs in CKD patients. [Ca2+]o an [K+]o changes caused variations in different features describ ing the morphology of the AP. Changes due to a [Na+]o varia tion were not as prominent. Simulations with [Ca2+]o varia tions were also carried out on ventricular ECG level and 12-lead ECG was computed. Thus, a multiscale simulato from ion channel to ECG reproducing the calcium-dependen inactivation of ICaL was achieved. The results on cellular an ventricular level agree with results from literature. Moreover we suggest novel features representing electrolyte change that have not been described in literature. These results coul be helpful for further studies aiming at the estimation of ioni concentrations based on ECG recordings

Doctor of Philosophy

dissertationDespite a century of research and practice, the clinical accuracy of the electrocardiogram (ECG) to detect and localize myocardial ischemia remains less than satisfactory. Myocardial ischemia occurs when the heart does not receive adequate oxygen-rich blood to keep up with its metabolic requirements, and severe ischemia can lead to myocardial infarction and life-threatening arrhythmias. Early and accurate detection is an essential component of managing this condition. Ischemia is known to be a dynamic condition that reflects a changing imbalance between blood supply and metabolic demand so that it is natural that examination under physical stress conditions or exercise testing (ET) is in widespread clinical use. However, ET is characterized by poor sensitivity (68%) and specificity (77%), limiting its diagnostic usefulness and providing the motivation to address some gaps in our understanding of myocardial ischemia and its ECG signature. This dissertation is composed of three studies. The aim of the first study was to evaluate the conventionally held mechanisms for nontransmural ischemia using intramural electrodes to measure three-dimensional potential distributions in the ventricles of animals exposed to acute ischemia. We demonstrated that contrary to accepted dogma, the electrocar- diographic response of acute myocardial ischemia originated throughout the ventricular wall, i.e., in the subendocardium, midmyocardium, or the subepicardium, under various conditions. Our goal in the second study was to evaluate whether acute myocardial ischemia follows a similar pattern of spatial and temporal evolution as seen in myocardial infarction. Our findings show that the spatial and temporal evolution of acute ischemia is characterized by multiple distinct regions that expand in all three directions, with maximal expansion in the circumferential direction, especially in the early stages of ischemic development. Furthermore, with increased stress, these regions continue to expand and eventually merge into one another, and in the extreme become transmural. The progression of myocardial infarction, by contrast, was very quickly transmural in extent and formed a cohesive block of affected tissues. The aim of the third study was to evaluate the sensitivity of epicardial electrical markers of acute ischemia relative to direct evidence of ischemia derived from intramural electro- grams. The key finding from this study is that the epicardial T-wave is a more sensitive index of acute ischemia than epicardial ST segment changes, especially in the early stages of acute ischemia development

Influence of ECG Lead reduction techniques for extracellular potassium and calcium concentration estimation

Chronic kidney disease (CKD) affects 13% of the worldwide population and end stage patients often receive haemodialysis treatment to control the electrolyte concentrations. The cardiovascular death rate increases by 10% - 30% in dialysis patients than in general population. To analyse possible links between electrolyte concentration variation and cardiovascular diseases, a continuous noninvasive monitoring tool enabling the estimation of potassium and calcium concentration from features of the ECG is desired. Although the ECG was shown capable of being used for this purpose, the method still needs improvement. In this study, we examine the influence of lead reduction techniques on the estimation results of serum calcium and potassium concentrations. We used simulated 12 lead ECG signals obtained using an adapted Himeno et al. model. Aiming at a precise estimation of the electrolyte concentrations, we compared the estimation based on standard ECG leads with the estimation using linearly transformed fusion signals. The transformed signals were extracted from two lead reduction techniques: principle component analysis PCA) and maximum amplitude transformation (MaxAmp). Five features describing the electrolyte changes were calculated from the signals. To reconstruct the ionic concentrations, we applied a first and a third order polynomial regression connecting the calculated features and concentration values. Furthermore, we added 30 dB white Gaussian noise to the ECGs to imitate clinically measured signals. For the noise-free case, the smallest estimation error was achieved with a specific single lead from the standard 12 lead ECG. For example, for a first order polynomial regression, the error was 0.0003±0.0767 mmol/l (mean±standard deviation) for potassium and -0.0036±0.1710 mmol/l for calcium (Wilson lead V1). For the noisy case, the PCA signal showed the best estimation performance with an error of -0.003±0.2005 mmol/l for potassium and -0.0002±0.2040 mmol/l for calcium (both first order fit). Our results show that PCA as ECG lead reduction technique is more robust against noise than MaxAmp and standard ECG leads for ionic concentration reconstruction

Modeling Human Atrial Patho-Electrophysiology from Ion Channels to ECG - Substrates, Pharmacology, Vulnerability, and P-Waves

Half of the patients suffering from atrial fibrillation (AF) cannot be treated adequately, today. This thesis presents multi-scale computational methods to advance our understanding of patho-mechanisms, to improve the diagnosis of patients harboring an arrhythmogenic substrate, and to tailor therapy. The modeling pipeline ranges from ion channels on the subcellular level up to the ECG on the body surface. The tailored therapeutic approaches carry the potential to reduce the burden of AF

Prediction of the effects of drugs on cardiac activity using computer simulations

[ES] Las enfermedades cardiovasculares siguen siendo la principal causa de muerte en Europa. Las arritmias cardíacas son una causa importante de muerte súbita, pero sus mecanismos son complejos. Esto denota la importancia de su estudio y prevención. La investigación sobre electrofisiología cardíaca ha demostrado que las anomalías eléctricas causadas por mutaciones que afectan a canales cardíacos pueden desencadenar arritmias. Sorprendentemente, se ha descubierto una gran variedad de fármacos proarrítmicos, incluidos aquellos que usamos para prevenirlas. Las indicaciones de uso de fármacos actuales intentaron solucionar este problema diseñando una prueba para identificar aquellos fármacos que podían ser peligrosos basado en el bloqueo de un solo canal iónico. El estudio de las interacciones fármaco-canal ha revelado la existencia no sólo de compuestos que bloquean múltiples canales, sino también una gran complejidad en esas interacciones. Esto podría explicar por qué algunos medicamentos pueden mostrar efectos muy diferentes en la misma enfermedad. Existen dos desafíos importantes con respecto a los efectos de los fármacos en la electrofisiología cardíaca. Por un lado, las empresas y entidades reguladoras están buscando una herramienta de alto rendimiento que mejore la detección del potencial proarrítmico durante el desarrollo de fármacos. Por otro lado, los pacientes con anomalías eléctricas a menudo requieren tratamientos personalizados más seguros. Las simulaciones computacionales contienen un poder sin precedentes para abordar fenómenos biofísicos complejos. Deberían ser de utilidad a la hora de determinar las características que definen tanto los efectos beneficiosos como no deseados de los fármacos mediante la reproducción de datos experimentales y clínicos. En esta tesis doctoral, se han utilizado modelos computacionales y simulaciones para dar respuesta a estos dos desafíos. El estudio de los efectos de los fármacos sobre la actividad cardíaca se dividió en el estudio de su seguridad y de su eficacia, respectivamente. Para dar respuesta al primer desafío, se adoptó un enfoque más amplio y se generó un nuevo biomarcador fácil de usar para la clasificación del potencial proarrítmico de los fármacos utilizando modelos del potencial de acción de células y tejidos cardíacos humanos. Se integró el bloqueo de múltiples canales a través de IC50 y el uso de concentraciones terapéuticas con el fin de mejorar el poder predictivo. Luego, se entrenó el biomarcador cuantificando el potencial proarrítmico de 84 fármacos. Los resultados obtenidos sugieren que el biomarcador podría usarse para probar el potencial proarrítmico de nuevos fármacos. Respecto al segundo desafío, se adoptó un enfoque más específico y se buscó mejorar la terapia de pacientes con anomalías eléctricas cardíacas. Por lo tanto, se creó un modelo detallado de la mutación V411M del canal de sodio, causante del síndrome de QT largo, reproduciendo datos clínicos y experimentales. Se evaluaron los posibles efectos beneficiosos de ranolazina, a la par que se aportó información sobre los mecanismos que impulsan la efectividad de la flecainida. Los resultados obtenidos sugieren que, si bien ambos fármacos mostraron diferentes mecanismos de bloqueo de los canales de sodio, un tratamiento con ranolazina podría ser beneficioso en estos pacientes.[CA] Les malalties cardiovasculars continuen sent la principal causa de mort a Europa. Les arrítmies cardíaques són una causa important de mort sobtada, però els seus mecanismes són complexos. Això denota la importància del seu estudi i prevenció. La investigació sobre electrofisiologia cardíaca ha demostrat que les anomalies elèctriques que afecten a canals cardiacs poden desencadenar arrítmies. Sorprenentment, s'ha descobert una gran varietat de fàrmacs proarrítmics, inclosos aquells que utilitzem per a previndre-les. Les indicacions d'ús de fàrmacs actuals van intentar solucionar aquest problema dissenyant una prova per a identificar aquells fàrmacs que podien ser perillosos basada en el bloqueig d'un sol canal iònic. L'estudi de les interaccions fàrmac-canal ha revelat l'existència no sols de compostos que bloquegen múltiples canals, sinó també una gran complexitat en aquestes interaccions. Això podria explicar per què alguns medicaments poden mostrar efectes molt diferents en la mateixa malaltia. Existeixen dos desafiaments importants respecte als efectes dels fàrmacs en la electrofisiologia cardíaca. D'una banda, les empreses i entitats reguladores estan buscant una eina d'alt rendiment que millore la detecció del potencial proarrítmic durant el desenvolupament de fàrmacs. D'altra banda, els pacients amb anomalies elèctriques sovint requereixen tractaments personalitzats més segurs. Les simulacions computacionals contenen un poder sense precedents per a abordar fenòmens biofísics complexos. Haurien de ser d'utilitat a l'hora de determinar les característiques que defineixen tant els efectes beneficiosos com no desitjats dels fàrmacs mitjançant la reproducció de dades experimentals i clíniques. En aquesta tesi doctoral, s'han utilitzat models computacionals i simulacions per a donar resposta a aquests dos desafiaments. L'estudi dels efectes dels fàrmacs sobre l'activitat cardíaca es va dividir en l'estudi de la seva seguretat i la seva eficacia. Per a donar resposta al primer desafiament, es va adoptar un enfocament més ampli i es va generar un nou biomarcador fàcil d'usar per a la classificació del potencial proarrítmic dels fàrmacs utilitzant models del potencial d'acció de cèl·lules i teixits cardíacs humans. Es va integrar el bloqueig de múltiples canals a través d'IC50 i l'ús de concentracions terapèutiques amb la finalitat de millorar el poder predictiu. Després, es va entrenar el biomarcador quantificant el potencial proarrítmic de 84 fàrmacs. Els resultats obtinguts suggereixen que el biomarcador podria usar-se per a provar el potencial proarrítmic de nous fàrmacs. Respecte al segon desafiament, es va adoptar un enfocament més específic i es va buscar millorar la teràpia de pacients amb anomalies elèctriques cardíaques. Per tant, es va crear un model detallat de la mutació V411M del canal de sodi, causant de la síndrome de QT llarg, reproduint dades clíniques i experimentals. Es van avaluar els possibles efectes beneficiosos de ranolazina, a l'una que es va aportar informació sobre els mecanismes que impulsen l'efectivitat de la flecainida. Els resultats obtinguts suggereixen que, si bé tots dos fàrmacs van mostrar diferents mecanismes de bloqueig dels canals de sodi, un tractament amb ranolazina podria ser beneficiós en aquests pacients.[EN] Cardiovascular disease remains the main cause of death in Europe. Cardiac arrhythmias are an important cause of sudden death, but their mechanisms are complex. This denotes the importance of their study and prevention. Research on cardiac electrophysiology has shown that electrical abnormalities caused by mutations in cardiac channels can trigger arrhythmias. Surprisingly, a wide variety of drugs have also shown proarrhythmic potential, including those that we use to prevent arrhythmia. Current guidelines designed a test to identify dangerous drugs by assessing their blocking power on a single ion channel to address this situation. Study of drug-channel interactions has revealed not only compounds that block multiple channels but also a great complexity in those interactions. This could explain why similar drugs can show vastly different effects in some diseases. There are two important challenges regarding the effects of drugs on cardiac electrophysiology. On the one hand, companies and regulators are in search of a high throughput tool that improves proarrhythmic potential detection during drug development. On the other hand, patients with electrical abnormalities often require safer personalized treatments owing to their condition. Computer simulations provide an unprecedented power to tackle complex biophysical phenomena. They should prove useful determining the characteristics that define the drugs' beneficial and unwanted effects by reproducing experimental and clinical observations. In this PhD thesis, we used computational models and simulations to address the two abovementioned challenges. We split the study of drug effects on the cardiac activity into the study of their safety and efficacy, respectively. For the former, we took a wider approach and generated a new easy-to-use biomarker for proarrhythmic potential classification using cardiac cell and tissue human action potential models. We integrated multiple channel block through IC50s and therapeutic concentrations to improve its predictive power. Then, we quantified the proarrhythmic potential of 84 drugs to train the biomarker. Our results suggest that it could be used to test the proarrhythmic potential of new drugs. For the second challenge, we took a more specific approach and sought to improve the therapy of patients with cardiac electrical abnormalities. Therefore, we created a detailed model for the long QT syndrome-causing V411M mutation of the sodium channel reproducing clinical and experimental data. We tested the potential benefits of ranolazine, while giving insights into the mechanisms that drive flecainide's effectiveness. Our results suggest that while both drugs showed different mechanisms of sodium channel block, ranolazine could prove beneficial in these patients.This PhD thesis was developed within the following projects: Ministerio de Economía y Competitividad and Fondo Europeo de Desarrollo Regional (FEDER) DPI2015-69125-R (MINECO/FEDER, UE): Simulación computacional para la predicción personalizada de los efectos de los fármacos sobre la actividad cardiaca. Dirección General de Política Científica de la Generalitat Valenciana (PROMETEU2016/088): “Modelos computacionales personalizados multiescala para la optimización del diagnóstico y tratamiento de arritmias cardiacas (personalised digital heart). Vicerrectorado de Investigación, Innovación y Transferencia de la Universitat Politècnica de València, Ayuda a Primeros Proyectos de Investigación (PAID-06-18), and by Memorial Nacho Barberá. Instituto de Salud Carlos III (La Fe Biobank PT17/0015/0043).Cano García, J. (2021). Prediction of the effects of drugs on cardiac activity using computer simulations [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/164094TESI