SOURCE-LINKED INTELLIGENCE

Development of Suprasensors and Assays for Molecular Diagnostics

CORDIS · observation · Publication date unknown

fundamental shortcomings. Out of this deep routed analysis, I developed the proposed ambitious strategy that marries principles of molecular recognition with materials science and chemistry-informed deep learning. These SupraSensors will advance the field through the following elements: i) high-energy water release from microporous materials ensures high binding affinity; ii) strategically placed peptide-based recognition elements provide selectivity while offering synthetic tunability; iii) information-rich signal output from SupraSensor libraries enables metabolite distinction in biofluids; iv) novel signal amplification concepts increase sensitivity. SupraSensor discovery will be fast and generalizable to many metabolite classes. SupraSense has the potential to unleash supreme opportunities for multiparameter diagnostics, which will be essential for patient subgrouping based on metabolic phenotypes. The new concepts developed herein have the prospect to revolutionize early detection of emerging cardiovascular events, inflammations, sepsis, and other metabolic or aging-associated

Read original source ↗ Open in workspace

recordType

award

status

SIGNED

region

EU

value

1994069

unit

EUR