Point-of-care tests (POCT) are a class of diagnostics capable of conducting medical tests within the immediate patient vicinity. Among such tests, lateral flow assays (LFAs) have long represented an archetypical, low-cost and rapid POCT, meeting many of the REASSURED criteria for diagnostics. The user-friendly and equipment-free virtues of these tests enable LFAs to be conducted in a variety of decentralised settings, such as clinics, pharmacies and homes. The impact of LFAs is perhaps most evident in resourcelimited countries as a means of offering accessible and delocalised tests, where access to quality healthcare can be limited. The utility of LFAs was recently highlighted during the COVID-19 pandemic where tests were adopted on an unprecedented scale in efforts to monitor and control the spread of SARS-CoV-2 worldwide. The performance of a LFA is often criticised as lacking in sensitivity and thus strategies to improve this are desirable. Realising high sensitivity in LFAs is frequently underpinned by a need for excellent recognition components for biomarker detection. In a typical test, the timeframe in which analyte flows past the test line is relatively short, presenting a small opportunity for antibodies to bind target epitopes. In sandwich LFA formats, antibodies decorating the test line and nanoparticle labels must bind the analyte with fast association kinetics and high affinity to ensure maximal analyte detection and LFA sensitivity. Achieving this often necessitates screening monoclonal antibodies, which are generally expensive and time consuming to produce, despite no guarantee of identifying candidates with high affinity and specificity towards biomarker targets. To this end, the ability to enhance the sensitivity of these tests -especially where low-affinity or poorly performing antibody reagents fall short of clinical or early-detection criteria -in a costeffective way whilst maintaining maximal user-friendliness remains crucial.