Sample-to-Answer Robotic ELISA

Chuqing Zhou, Zecong Fang, Cunyi Zhao, Xiyan Mai, Shiva Emami, Ameer Y. Taha, Gang Sun, Tingrui Pan

Research output: Contribution to journalArticlepeer-review


Enzyme-linked immunosorbent assays (ELISA), as one of the most used immunoassays, have been conducted ubiquitously in hospitals, research laboratories, etc. However, the conventional ELISA procedure is usually laborious, occupies bulky instruments, consumes lengthy operation time, and relies considerably on the skills of technicians, and such limitations call for innovations to develop a fully automated ELISA platform. In this paper, we have presented a system incorporating a robotic-microfluidic interface (RoMI) and a modular hybrid microfluidic chip that embeds a highly sensitive nanofibrous membrane, referred to as the Robotic ELISA, to achieve human-free sample-to-answer ELISA tests in a fully programmable and automated manner. It carries out multiple bioanalytical procedures to replace the manual steps involved in classic ELISA operations, including the pneumatically driven high-precision pipetting, efficient mixing and enrichment enabled by back-and-forth flows, washing, and integrated machine vision for colorimetric readout. The Robotic ELISA platform has achieved a low limit of detection of 0.1 ng/mL in the detection of a low sample volume (15 μL) of chloramphenicol within 20 min without human intervention, which is significantly faster than that of the conventional ELISA procedure. Benefiting from its modular design and automated operations, the Robotic ELISA platform has great potential to be deployed for a broad range of detections in various resource-limited settings or high-risk environments, where human involvement needs to be minimized while the testing timeliness, consistency, and sensitivity are all desired.

Original languageEnglish (US)
Pages (from-to)11424-11432
Number of pages9
JournalAnalytical Chemistry
Issue number33
StatePublished - Aug 24 2021

ASJC Scopus subject areas

  • Analytical Chemistry


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