Development of a multiplexing potency assay using upconverting nanoparticles-based luminescence resonance energy transfer
Journal of Immunological Methods, ISSN: 0022-1759, Vol: 510, Page: 113364
2022
- 1Citations
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations1
- Citation Indexes1
Article Description
A homogeneous particle-based immunoassay using upconverting nanoparticles (UCNPs) has been developed for multiplexing potency analysis of two different therapeutic monoclonal antibodies (mAbs) in a fixed-combination formulation.The UCNP, considered as the best donor lumiphore for luminescence resonance energy transfer (LRET), offers long lasting excitation state and increased signal-to-noise (S/N) ratio due to low autofluorescence effect and light scattering from near infrared (NIR) excitation. In this study, the dose-response curves for each therapeutic mAb were generated using two distinct UCNPs. This proof-of-concept LRET-based immunoassay demonstrated a novel approach for increasing testing throughput and analyzing the potency of mixed therapeutic mAbs in co-formulated products.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S002217592200151X; http://dx.doi.org/10.1016/j.jim.2022.113364; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85139346575&origin=inward; http://www.ncbi.nlm.nih.gov/pubmed/36179896; https://linkinghub.elsevier.com/retrieve/pii/S002217592200151X; https://dx.doi.org/10.1016/j.jim.2022.113364
Elsevier BV
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