scholarly journals FLIM FRET Technology for Drug Discovery: Automated Multiwell‐Plate High‐Content Analysis, Multiplexed Readouts and Application in Situ

ChemPhysChem ◽  
2011 ◽  
Vol 12 (3) ◽  
pp. 609-626 ◽  
Author(s):  
Sunil Kumar ◽  
Dominic Alibhai ◽  
Anca Margineanu ◽  
Romain Laine ◽  
Gordon Kennedy ◽  
...  
2013 ◽  
Vol 7 (4) ◽  
pp. e2154 ◽  
Author(s):  
Nathalie Aulner ◽  
Anne Danckaert ◽  
Eline Rouault-Hardoin ◽  
Julie Desrivot ◽  
Olivier Helynck ◽  
...  

Nanomedicine ◽  
2019 ◽  
Vol 14 (19) ◽  
pp. 2535-2548 ◽  
Author(s):  
Zhigang Zhang ◽  
Tianying Zhang ◽  
Lu Cao ◽  
Xin Wang ◽  
Jiali Cao ◽  
...  

Aim: Traditional antigenicity assay requires antigen recovery from the particulate adjuvants prior to analysis. An in situ method was developed for interrogating vaccine antigens with monoclonal antibodies while being adsorbed on adjuvants. Materials & methods: The fluorescence imaging-based high content analysis was used to visualize the antigen distribution on adjuvant agglomerates and to analyze the antigenicity for adsorbed antigens. Results: Simultaneous visualization and quantitation were achieved for dual antigens in a bivalent human papillomavirus vaccine with uniquely labeled antibodies. Good agreement was observed between the in situ multiplexed assays with well-established sandwich enzyme-linked immunosorbent assays. Conclusion: The streamlined procedures and the amenability for multiplexing make the in situ antigenicity analysis a favorable choice for in vitro functional assessment of bionanoparticles as vaccine antigens.


2019 ◽  
Vol 24 (6) ◽  
pp. 615-627 ◽  
Author(s):  
Tijmen H. Booij ◽  
Leo S. Price ◽  
Erik H. J. Danen

The introduction of more relevant cell models in early preclinical drug discovery, combined with high-content imaging and automated analysis, is expected to increase the quality of compounds progressing to preclinical stages in the drug development pipeline. In this review we discuss the current switch to more relevant 3D cell culture models and associated challenges for high-throughput screening and high-content analysis. We propose that overcoming these challenges will enable front-loading the drug discovery pipeline with better biology, extracting the most from that biology, and, in general, improving translation between in vitro and in vivo models. This is expected to reduce the proportion of compounds that fail in vivo testing due to a lack of efficacy or to toxicity.


PLoS ONE ◽  
2014 ◽  
Vol 9 (7) ◽  
pp. e102678 ◽  
Author(s):  
Albert H. Gough ◽  
Ning Chen ◽  
Tong Ying Shun ◽  
Timothy R. Lezon ◽  
Robert C. Boltz ◽  
...  

2008 ◽  
Vol 11 (3) ◽  
pp. 216-230 ◽  
Author(s):  
Philip Denner ◽  
Janine Schmalowsky ◽  
Stefan Prechtl

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