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SLAS Technol. 2018 Apr;23(2):188-197. doi: 10.1177/2472630317750378. Epub 2018 Jan 18.

Automation on an Open-Access Platform of Alzheimer's Disease Biomarker Immunoassays.

Author information

1 Laboratory for Molecular Neurobiomarker Research, Department of Neurosciences, KU Leuven, Leuven, Belgium.
2 Department of Chronic Disease, Metabolism and Ageing, KU Leuven, Leuven, Belgium.
3 ADx NeuroSciences, Gent, Belgium.
4 Laboratory Medicine, University Hospitals Leuven, Leuven, Belgium.
5 Euroimmun AG, Lübeck, Germany.
6 Department of Neurology, University Hospitals Leuven, Leuven, Belgium.
7 Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium.
8 Alzheimer Research Centre KU Leuven, Leuven Institute of Neuroscience and Disease, Leuven, Belgium.
9 Department of Clinical and Experimental Medicine, KU Leuven, Leuven, Belgium.


The lack of (inter-)laboratory standardization has hampered the application of universal cutoff values for Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers and their transfer to general clinical practice. The automation of the AD biomarker immunoassays is suggested to generate more robust results than using manual testing. Open-access platforms will facilitate the integration of automation for novel biomarkers, allowing the introduction of the protein profiling concept. A feasibility study was performed on an automated open-access platform of the commercial immunoassays for the 42-amino-acid isoform of amyloid-β (Aβ1-42), Aβ1-40, and total tau in CSF. Automated Aβ1-42, Aβ1-40, and tau immunoassays were performed within predefined acceptance criteria for bias and imprecision. Similar accuracy was obtained for ready-to-use calibrators as for reconstituted lyophilized kit calibrators. When compared with the addition of a standard curve in each test run, the use of a master calibrator curve, determined before and applied to each batch analysis as the standard curve, yielded an acceptable overall bias of -2.6% and -0.9% for Aβ1-42 and Aβ1-40, respectively, with an imprecision profile of 6.2% and 8.4%, respectively. Our findings show that transfer of commercial manual immunoassays to fully automated open-access platforms is feasible, as it performs according to universal acceptance criteria.


Alzheimer’s disease; automation; biomarkers; cerebrospinal fluid; open-access platform

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