Development of ink-printed RPL technology by Marie Skłodowska-Curie Career FIT Fellow at the University of Limerick

Limerick, Ireland – February 2020. As Industry mentor, GlycoSeLect’s CEO, Robert Dunne, attended the annual review meeting of the Career-FIT project JETLECT – Ink-Jet Printed Recombinant Prokaryotic Lectins for POC Biomedical Diagnostics and High Throughput Biomedical Screening – at the University of Limerick.

Mr Dunne mentors Dr Semen Vasilev, a Marie Skłodowska-Curie fellow, whose research project aims to use GlycoSeLect’s Recombinant Prokaryotic Lectins (RPLs) as diagnostic sensors for disease detection and high throughput screening of biopharmaceuticals.

For this purpose, Dr Vasilev will develop methodologies for ink-jet printing RPLs in a high-density format, generating bio-sensing platforms and, ultimately, building RPL-based arrays for biopharmaceutical screening applications.

“I was delighted to see the progress in the project made by the Dr Semen Vasilev with his academic mentor Dr Emmet O’Reilly. I am looking forward to the publication of 3 research papers and the use of our RPL lectins following the proof of concept work to date”, said GlycoSeLect’s CEO, Robert Dunne.

 

Career-FIT has received funding from the European Union’s Horizon2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 713654.

About GlycoSelect Ltd

GlycoSeLect Ltd develops innovative technologies for the analysis, characterisation and purification of biopharmaceuticals. These next-generation products are highly specific for glycan structures improving product development and improving the cost-efficiency of their manufacturing. GlycoSeLect specialises in the development of proteins based on recombinant prokaryotic lectins RPLs. Our RPL products advance efficient detection, analysis and selective isolation of glycosylated pharmaceutical products. GlycoSeLect’s family of RPLs products are associated with market-leading properties, including high affinity for glycan targets, high sensitivity of detection, high stability and robustness in process development.

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