(RxWiki News) Testing new drugs is no easy task. Animal testing may show successful results that aren't replicated in humans, and having drug trials in individuals could result in undesirable side effects.
Those might become the testing methods of the past with the development of an accurate computer model designed to test the effectiveness of drugs for heart arrhythmias before they are used in patients.
"Know the side effects before you begin a new drug."
Dr. Colleen Clancy, an associate professor of pharmacology at UC Davis and senior author of the study, said that drug development for abnormal heart rhythms has failed because it is difficult to anticipate how drugs will alter the heart's electrical behavior prior to clinical trials.
She said the new computer simulation can help solve the problem by making early predictions about the efforts of medications on heart rhythms.
The development of the new tool was spurred by the Cardiac Arrhythmia Suppression Trial (CAST) study in the 1980s, which was abruptly ended when scientists found that arrhythmia drug flecainide tripled the risk of sudden cardiac death.
In developing the computer model, researchers used lidocaine, an anti-arrhythmia medication considered safe with ample clinical data already available.
Dr. Clancy started with existing models that simulate the behavior of heart cells during both normal and abnormal heart rhythms . Mathematical formulas were then devised to describe the interactions of flecainide and lidocaine on cardiac electrical activity. The models were used to predict the drug effects on heart rhythms in a three dimensional virtual heart.
In order to confirm the results, researchers treated rabbit hearts with the two drugs and found that the simulation correctly predicted the heart rates and adverse effects.
Dr. Clancy noted that each year millions with cardiac arrhythmias wind up with implantable defibrillators that could reduce their quality of life after failing to respond well to medications.The model is currently limited to a few drugs and biological processes. However, it still could lead to quicker discoveries of new therapies for heart arrhythmias.
The new tool was described in journal Science Translational Medicine.
