Objective
This project aims to deliver a microfluidic platform capable of isolating bacteria and Extracellular Vesicles (EVs) at high throughput and high recovery rates from clinical samples, and perform the necessary downstream analysis for the diagnosis of diseases requiring earlier/urgent treatment. Currently, long incubation steps required for identification and susceptibility testing of pathogens make clinicians to prescribe broad-spectrum antibiotic treatments in sepsis cases upon hospital admission, and in nearly half of cases this treatment fails. On a different timescale, the lack of symptoms until late stages of some cancer types such as pancreatic cancer means a high mortality rate. Profiling molecules contained in EVs —most importantly DNA, RNA, proteins and lipids— promises a powerful diagnostic tool as biomarkers for cancer, but current EV isolation methods relying on ultracentrifugation are lengthy and can potentially damage the information enclosed. Microfluidics could provide a high yield, high throughput solution for isolation and enrichment of such particles. However, current approaches do not meet requirements of throughput and/or detection limit, and lack insightful physical understanding. I propose to use novel fluid dynamic and electrokinetic models for particle manipulation in microfluidics, with state-of-the-art fabrication methods to deliver a device capable of rapidly isolating and enriching samples containing (a) bacteria at low concentration (few hundreds per mL) to be integrated in a platform with the potential to identify and perform ASTs in possible bacterial infections in body fluids that avoid culture steps in current gold standards and potentially allow a ten-fold time reduction from sample to answer; (b) EVs to replace current ultracentrifugation methods. Thus, a future clinical implementation of the project outcomes will have large economic and societal impact.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencesphysical sciencesclassical mechanicsfluid mechanicsmicrofluidics
- social sciencessociologydemographymortality
- natural sciencesbiological sciencesmicrobiologybacteriology
- natural sciencesbiological sciencesbiochemistrybiomoleculeslipids
- medical and health sciencesclinical medicineoncology
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Keywords
Programme(s)
- HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA) Main Programme
Funding Scheme
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European FellowshipsCoordinator
41004 Sevilla
Spain