posted on 2020-04-30, 16:35authored byXianglin Ji, Peilin Fang, Bingzhe Xu, Kai Xie, Haibing Yue, Xuan Luo, Zixun Wang, Xi Zhao, Peng Shi
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.