The acceptability and feasibility of large-scale testing with lateral flow tests (LFTs) for clinical and public health purposes has been demonstrated during the COVID-19 pandemic. LFTs can detect analytes in a variety of samples, providing a rapid read-out, which allows selftesting and decentralized diagnosis. In this Review, we examine the changing LFT landscape with a focus on lessons learned from COVID-19. We discuss the implications of LFTs for decentralized testing of infectious diseases, including diseases of epidemic potential, the 'silent pandemic' of antimicrobial resistance, and other acute and chronic infections. Bioengineering approaches will play a key part in increasing the sensitivity and specificity of LFTs, improving sample preparation, incorporating nucleic acid amplification and detection, and enabling multiplexing, digital connection and green manufacturing, with the aim of creating the next generation of high-accuracy, easy-to-use, affordable and digitally connected LFTs. We conclude with recommendations, including the building of a global network of LFT research and development hubs to facilitate and strengthen future diagnostic resilience. Sections• Bioengineering approaches, such as the use of nano-and quantum materials, nucleic-acid-based LFTs, CRISPR and machine learning, will improve the sensitivity, specificity, multiplexing and connectivity features of LFTs.• We recommend investing in an international LFT research and development hub network to spearhead the development of a pipeline of innovative bioengineering approaches to design next-generation LFTs.

Paper-based lateral flow assays (LFAs) are among the most widely used biosensing platforms for point-of-care testing (POCT). However, the conventional colloidal gold label of LFAs show low sensitivity and limited quantitative capacity. Alternatively, the use of enzyme/chemical reaction-based signal amplification with structural modifications has enhanced analytical capacity but requires multiple user interventions as a trade-off, increasing complexity, test imprecision, and time. These platforms are also difficult to manufacture, limiting their practical applications. In this study, within the current LFA production framework, we developed a highly sensitive, automated, universal, and manufacturable LFA biosensing platform by (i) incorporating gold nanoparticles into a polymer-networked peroxidase with an antibody as a new scheme for enhanced enzyme conjugation and (ii) integrating a mass-producible and time-programmable amplification part based on a water-swellable polymer for automating the sequential reactions in the immunoassay and signal amplification, without compromising performance, simplicity, and production feasibility. We applied this platform to evaluate cardiac troponin I (cTnI), a gold-standard biomarker for myocardial infarction diagnosis. Quantitative analysis of cTnI in clinical setting remains limited to the laboratory-based high-end and costly standard equipment. Coupled with an enzymecatalyzed chemiluminescence method, this platform enables automated, cost-effective (0.66 USD per test), and highperformance testing of human cTnI in serum samples within 20 min with a detection range of 6 orders of magnitude, detection limit of 0.84 pg mL −1 (595-fold higher than conventional cTnI-LFA), and a coefficient of variation of 2.9−8.5%, which are comparable to the standard equipment and acceptable for clinical use. Moreover, cTnI analysis results using clinical serum/ plasma samples revealed a strong correlation (R 2 = 0.991) with contemporary standard equipment, demonstrating the practical application of this platform for high-performance POCT.

As a global shift continues to occur in high burden diseases toward developing countries, the importance of medical diagnostics based on point-of-care testing (POCT) is rapidly increasing. However, most diagnostic tests that meet clinical standards rely on high-end analyzers in central hospitals. Here, we report the development of a simple, low-cost, mass-producible, highly sensitive/quantitative, automated, and robust paper/soluble polymer hybrid-based lateral flow biosensing platform, paired with a smartphone-based reader, for high-performance POCT. The testing architecture incorporates a polymeric barrier that programs/automates sequential reactions via a polymer dissolving mechanism. The smartphone-based reader with simple opto-mechanical parts offers a stable framework for accurate quantification. Analytical performance of this platform was evaluated by testing human cardiac troponin I (cTnI), a preferred biomarker for the diagnosis of myocardial infarction, in serum/plasma samples. Coupled with catalytic/colorimetric gold-ion amplification, this platform produced results within 20 min with a detection limit of 0.92 pg mL–1 and a coefficient of variation <10%, which is equivalent to the performance of a high-sensitivity standard analyzer, and operated within acceptable levels stipulated by clinical guidelines. Moreover, cTnI clinical sample tests indicate a high correlation (r = 0.981) with the contemporary analyzers, demonstrating the clinical utility of this platform in high-performance POCT.

No abstract

Diabetes mellitus is one of the most common chronic diseases worldwide. Generally, the levels of fasting or postprandial blood glucose and other biomarkers, such as glycated albumin, glycated hemoglobin, and 1,5-anhydroglucitol, are used to diagnose or monitor diabetes progression. In the present study, we developed a sensor to simultaneously detect the glucose levels and glycation ratios of human serum albumin using a lateral flow assay. Based on the specific enzymatic reactions and immunoassays, a spiked glucose solution, total human serum albumin, and glycated albumin were measured simultaneously. To test the performance of the developed sensor, clinical serum samples from healthy subjects and patients with diabetes were analyzed. The glucose level and glycation ratios of the clinical samples were determined with reasonable correlation. The R-squared values of glucose level and glycation ratio measurements were 0.932 and 0.930, respectively. The average detection recoveries of the sensor were 85.80% for glucose and 98.32% for the glycation ratio. The glucose level and glycation ratio in our results were crosschecked with reference diagnostic values of diabetes. Based on the outcomes of the present study, we propose that this novel platform can be utilized for the simultaneous detection of glucose and glycation ratios to diagnose and monitor diabetes mellitus.