Scientists from the University of California San Diego and Stanford University have created a new way to monitor heart cells’ electrical activity without physically entering the cells. This method uses artificial intelligence (AI) to analyze signals from the outside of the cells and reconstruct the inner signals accurately.
The research, published in Nature Communications, reveals how extracellular signals (outside the cell) can be used to understand intracellular signals (inside the cell). These signals show how the heart works, how cells communicate, and how they respond to drugs.
Traditionally, monitoring these signals required invasive methods, like inserting electrodes into the cells, which could damage them. However, the new approach avoids this by linking the external and internal signals using AI.
The team built an array of tiny electrodes, much smaller than a single heart cell, to collect data. They trained an AI model with thousands of signal pairs to predict the internal signals based on external recordings. Tests showed the model was very accurate.
This breakthrough can speed up and improve drug testing for heart safety. Researchers can now test drugs on human heart cells, reducing the need for animal testing and offering more precise results. It also paves the way for personalized medicine, where drugs can be tested on a patient’s specific cells to predict their response.
The researchers aim to extend this technology to study other cells, like neurons, to better understand various tissues and diseases.
Source: medicalxpress
