Biohybrid Triboelectric Nanogenerator for Label-Free Pharmacological Fingerprinting in Cardiomyocytes

Abstract

The development of new drugs requires high-throughput and cost-effective pharmacological assessment in relevant biological models. Here, we introduce a novel pharmacological screening platform that combines a biohybrid triboelectric nanogenerator (TENG) and informatic analysis for self-powered, noninvasive, and label-free biosensing in cardiac cells. The cyclic mechanical activity of functional cardiomyocytes is dynamically captured by a specially designed biohybrid TENG device and is analyzed by a custom-made machine learning algorithm to reveal distinctive fingerprints in response to different pharmacological treatment. The core of the TENG device is a multilayer mesh substrate with microscale-gapped triboelectric layers, which are induced to generate electrical outputs by the characteristic motion of cardiomyocytes upon pharmaceutical treatment. Later bioinformatic extraction from the recorded TENG signal is sufficient to predict a drug's identity and efficacy, demonstrating the great potential of this platform as a biocompatible, low-cost, and highly sensitive drug screening system.