MSE Research Project Database

Electrocardiographic markers associated with fatal heart diseases and cardiac safety


Project Leader: Ahsan Khandoker
Staff: Marimuthu Palaniswami
Student: Hasan Imam
Collaborators: Jean-Philippe Couderc (University of Rochester)
Primary Contact: Ahsan Khandoker (ahsank@unimelb.edu.au)
Keywords: biosignals; cardiovascular disease; electrocardiogram ECG; heart
Disciplines: Biomedical Engineering
Domains: Convergence of engineering and IT with the life sciences
Research Centre: ARC Research Network on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)

Cardiac safety remains a major public health concern. Sudden cardiac death (SCD) is responsible for half of all heart disease deaths and is the largest cause of natural death in the world. Despite the effort implemented to reduce this number by early advanced care, there is a clear need for the improvement of risk stratification techniques to optimise the use of prophylactic therapies, such as implantable defibrillators and drug therapies. Meanwhile cardiac safety is also one of the most challenging hurdles in the development of new molecular entities. It has been estimated that as many as 86% of all drugs tested in pharmaceutical development show specific inhibitory activity of potassium ion kinetics, which in some cases can lead to torsades de pointes and potentially to SCD. According to the US Food and Drug Administration (FDA), the main reason for the inability to effectively screen out potentially harmful drugs is the lack of better markers to improve predictability and efficacy of new compounds. For example, drug-induced QT prolongation is used as a surrogate marker of drug cardiotoxicity, yet the scientific community has strongly questioned its validity and there is a consensus on the need for novel technologies that would improve the current safety guidelines. The aim of this project to develop novel markers of the surface electrocardiograms (ECGs) as a noninvasive approach to assess drug cardiotoxicity, to predict arrhythmic events, and to risk stratify cardiac and non-cardiac patients. Electrocardiogram data from healthy individuals exposed to cardiac and non-cardiac drugs, patients with congenital long QT syndrome, post-myocardial patients and patients with coronary artery disease will be analysed in this project.