Multimodal integrated sensor platform for rapid biomarker detection

Al-Rawhani, M. A. et al. (2019) Multimodal integrated sensor platform for rapid biomarker detection. IEEE Transactions on Biomedical Engineering, (doi:10.1109/TBME.2019.2919192) (PMID:31226063) (Early Online Publication)

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Abstract

Precision metabolomics and quantification for cost-effective, rapid diagnosis of disease are key goals in personalized medicine and point-of-care testing. Presently, patients are subjected to multiple test procedures requiring large laboratory equipment. Microelectronics has already made modern computing and communications possible by integration of complex functions within a single chip. As More than Moore technology increases in importance, integrated circuits for densely patterned sensor chips have grown in significance. Here, we present a versatile single CMOS chip forming a platform to address personalized needs through on-chip multimodal optical and electrochemical detection that will reduce the number of tests that patients must take. The chip integrates interleaved sensing subsystems for quadruple-mode colorimetric, chemiluminescent, surface plasmon resonance and hydrogen ion measurements. These subsystems include a photodiode array and a single photon avalanche diode array, with some elements functionalized to introduce a surface plasmon resonance mode. The chip also includes an array of ion sensitive field effect transistors. The sensor arrays are distributed uniformly over an active area on the chip surface in a scalable and modular design. Bio-functionalization of the physical sensors yields a highly selective simultaneous multiple-assay platform in a disposable format. We demonstrate its versatile capabilities through quantified bioassays performed on-chip for glucose, cholesterol, urea and urate, each within their naturally occurring physiological range.

Item Type:Articles
Status:Early Online Publication
Refereed:Yes
Glasgow Author(s) Enlighten ID:Mitra, Dr Srinjoy and Cochran, Professor Sandy and Al-Rawhani, Dr Mohammed and Accarino, Claudio and Giagkoulovits, Mr Christos and Velugotla, Dr Srinivas and Grant, Dr James and Cumming, Professor David and Hu, Dr Chunxiao and Annese, Valerio and Beeley, Mr James and Barrett, Professor Michael and Cheah, Dr Boon Chong
Authors: Al-Rawhani, M. A., Hu, C., Giagkoulovits, C., Annese, V. F., Cheah, B. C., Beeley, J., Velugotla, S., Accarino, C., Grant, J. P., Mitra, S., Barrett, M. P., Cochran, S., and Cumming, D. R.S.
College/School:College of Medical Veterinary and Life Sciences > Institute of Infection Immunity and Inflammation
College of Science and Engineering > School of Engineering
College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
College of Science and Engineering > School of Engineering > Systems Power and Energy
Journal Name:IEEE Transactions on Biomedical Engineering
Publisher:IEEE
ISSN:0018-9294
ISSN (Online):1558-2531
Published Online:19 June 2019
Copyright Holders:Copyright © 2019 IEEE
First Published:First published in IEEE Transactions on Biomedical Engineering 2019
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher
Data DOI:10.5525/gla.researchdata.825

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
605821The Multi-Corder: Poly-Sensor TechnologyDavid CummingEngineering and Physical Sciences Research Council (EPSRC)EP/K021966/1ENG - ENGINEERING ELECTRONICS & NANO ENG