An irregular heartbeat – known as an arrhythmia – interferes with normal electrical pulses in the heart, which can lead to cardiac arrest, according to scientists.
But, arrhythmias are so rare, that it’s difficult to estimate when they will occur.
It had already been revealed that some cells next to the heart can spontaneously burst calcium, leading to a premature heartbeat, and subsequently deadly arrhythmias.
But, researchers claim to have created a new computer model that estimates the probably of rare arrhythmias.
Predicting when these abnormal heartbeats may occur opens the door to new drug therapies for the most at-risk patients, the scientists revealed.
Study co-author, Raimond Winslow, said: “This study represents an important step forward in understanding how to pinpoint the molecular processes that are the primary regulators of the probability of occurrence of rare arrhythmic events.
“As such, our approach offers a powerful new computational tool for identifying the optimal drug targets for pharmacotherapy directed at preventing arrhythmias.”
The researchers’ model runs hundreds of simulations in the heart, to forecast the probability of arrhythmia.
Sanofi Director and Head of Systems Pharmacology, Karim Azer – who wasn’t involved in the study – said the model was critical to improving our understanding of organ behaviour in complex diseases, like heart failure.
“The models provide predictions that can be tested in the laboratory or the clinic,” said Azer.
“The pharmaceutical industry is increasingly using mathematical and computational modelling approaches for enabling key drug discovery and development decisions regarding drug and patient characteristics.”
More than two million people a year in the UK experience arrhythmias, or heart rhythm problems, according to the NHS.
Symptoms of the condition include palpitations, feeling dizzy, fainting, and being short of breath.
An electrocardiogram (ECG) is used to diagnose arrhythmias, by monitoring electrical pulses in the heart.
Medication is available to help prevent the condition.