Martí-Franquès COFUND Fellowship Programme


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Engineering and Architecture

Supervisor name and surname:

Beatriz Prieto Simón

Supervisor email:

Supervisor short biography

PhD programme:

Technologies for Nanosystems, Bioengineering and Energy

Title of the research project:

Rapid and cost-effective diagnostic tools to fight viral outbreaks

Description of the research project:

We aim to generate and validate a suit of highly sensitive and versatile label-free electrochemical sensing platforms for the early diagnosis of viral outbreaks. Early diagnosis is critical to advance in the fight against viral outbreaks, such as the CoVid19. The developed tools will be harnessed to 1) guide clinical workflow for health system relief, 2) select appropriate treatment, 3) inform prognosis, 4) confirm low enough viral load to recommend patient discharge to free up intensive care units, and 5) prevent the spread of infections, mainly driven via asymptomatic patients.

Early diagnosis will be approached via two strategies:

1. Host response-based diagnostics
The acquisition of personalised information about the host immune response to infection is highly relevant. Infection evolution over time shows that the early detection of biomarkers key during the incubation period, can be harnessed to actuate before pathogen replication and symptoms arise. We aim to demonstrate the potential of host response-based diagnostic tools to face the challenges involved in detecting viral infections at their onset. Biosensing platforms based on multi-stacks of materials featuring aligned nanochannels will be crafted to enable sequential analysis of exosomes and exosomal content, as biomarkers of the host response to infection. Complementary biomarkers, including procalcitonin and specific cytokines, will also be incorporated as target analytes in these multiplexing platforms to prove quick discrimination among viral infections.

2. Fit-for-purpose diagnostics for sequential viral and RNA viral detection
Tools that can provide information about the class of virus and subsequently identify the specific virus are expected to be a game changer in the early diagnosis of viral outbreaks, such as the CoVid19, by detecting infected patients prior to symptoms manifest and enabling monitoring of their infection status. Biosensors based on multi-stacks of hybrid materials are key to achieve sequential detection of various biomarkers to identify the class of virus (e.g. human coronaviruses) and the specific virus (e.g. SARS-CoV-2) by harnessing the feasibility of each layer to play a different role (i.e. biorecognition, transduction). Furthermore, this type of sensing platforms has demonstrated ultrasensitivity, required to allow direct measurements on complex matrices (e.g. blood, serum, saliva) without sample pre-treatment, and its ability to provide label-free detection without the need of previous amplification steps.
Ethics: This project does not involve ethical aspects.

Workplace location: Campus Sescelades, Tarragona

Gross anual salary:

27103.20 €


Full time

Working hours:

37.5 hours a week

Expected start date:

15 March 2021

European union This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 945413