Summary
This project aims to advance point-of-care diagnostics through the identification of novel biomarkers and the development of nanobodies targeting epitopes that are unique within them, to achieve the highest specify.
Relevant biomarkers will be identified by analysing ‘omics data, and a preliminary shortlist has already been compiled. Nanobodies targeting them will be obtained in the academic lab using a combination of pioneering in silico and in vitro approaches of antibody discover and optimisation.
Then, they will be deployed in state-of-the-art lateral-flow devices (the ""NeutroCheck"" platform) developed by the industrial partner, to enable the rapid and cost-effective detection of both cell- and non-cell-based biomarkers, thus facilitating timely clinical interventions.
Project aims
The primary focus will be on identifying and raising nanobodies for biomarkers within blood lymphocytes. These biomarkers will serve as crucial indicators for monitoring drug- or disease-related immunosuppression at the point of care, addressing a critical need in healthcare.
By integrating highly specific nanobodies with advanced detection technologies, NeutroCheck will enable quantitative, rapid, and reliable point-of-care diagnosis, improving patient outcomes and healthcare efficiency.
Furthermore, this research will provide a unique opportunity to explore and discover novel biomarkers associated with the response to anticancer immunotherapy, possibly leading to new insights for cancer treatment strategies.
This strongly multidisciplinary project bridges computational structural biology, biophysics, immunology, and diagnostics.
It offers an exceptional opportunity for a PhD candidate to make a significant impact on both healthcare and life-sciences industries. The proposed research will contribute to advancing precision medicine, improving patients’ healthcare journeys, and reducing healthcare costs.
Contact details
Pietro Sormanni - ps589@cam.ac.uk
Opportunities
This project is open to applicants who want to do a:
- PhD