Veeren Chauhan1, 2, Mohamed Elsutohy1, James Jacobs2, Neil Roddis2 and Jonathan Aylott1*

 

1 School of Pharmacy, University of Nottingham, Nottingham. NG7 2RD, United Kingdom
2
TBG Solutions, Barlborough, Chesterfield, Derbyshire, S43 4UL, United Kingdom

 

There is an immediate unmet need for a diagnostic technology that assists GPs and healthcare professionals when making point of care clinical prescribing decisions for respiratory tract infections (RTIs).

Currently there is no easy to use low-cost desktop product that is able to stratify patients presenting with the symptoms of a RTI from viral or bacterial aetiology during the timeframe of typical GP-Patient consultation. As a result, antibiotics are overprescribed and have contributed to the rise of antimicrobial resistance, which is associated with both long-term medical and economic uncertainty. Existing solutions fall outside of the limited GP-Patient consultation timeframe (PCR, microscopy), require specialist skills to operate them (PCR, microscopy and ELISA) and are expensive (PCR, microscopy).

We have developed a rapid, accurate and economical point-of-care viral diagnostic that is highly sensitive towards a bespoke common cold viral nucleotide sequence, so that individuals presenting with the symptoms of an RTI can be classified into those patients who have/ do not have the common cold. Clinical throat swabs samples are transferred to a lateral flow test strip, where aptamer-gold nanoparticle based sensing elements in combination with electronic components, such as optical sensors, easy to read displays, and custom designed embedded software interpret the results on behalf of the healthcare professional to indicate whether the patient is positive or negative for the common cold. Patients that exhibit a positive result for the presence of the rhinovirus are advised of therapy that will effectively manage their symptoms and to return if their condition exacerbate. Whereas, patients that are negative for rhinoviruses will be prescribed an appropriate antibiotic/course of therapy to treat their non-rhinoviral RTI.

We envisage our technology will pave the way forward and complement existing strategies at overcoming antimicrobial resistance.

Figure 1: Schematic diagram of signal transduction mechanism of biosensor to simple user interface

Biographic Details

Name: Veeren Chauhan

Title: Dr

Affiliation, Country: University of Nottingham, UK

Phone: +44115 84 67048 Fax: +44115 951 5102 Email: veeren.chauhan@nottingham.ac.uk  

Research Interests: Nanoscience, Analytical Chemistry, Pharmaceutics