Dataset Information

Real-time, smartphone-based processing of lateral flow assays for early failure detection and rapid testing workflows.

ABSTRACT: Despite their simplicity, lateral flow immunoassays (LFIAs) remain a crucial weapon in the diagnostic arsenal, particularly at the point-of-need. However, methods for analysing LFIAs still rely heavily on sub-optimal human readout and rudimentary end-point analysis. This negatively impacts both testing accuracy and testing times, ultimately lowering diagnostic throughput. Herein, we present an automated computational imaging method for processing and analysing multiple LFIAs in real-time and in parallel. This method relies on the automated detection of signal intensity at the test line, control line, and background, and employs statistical comparison of these values to predictively categorise tests as "positive", "negative", or "failed". We show that such a computational methodology can be transferred to a smartphone and detail how real-time analysis of LFIAs can be leveraged to decrease the time-to-result and increase testing throughput. We compare our method to naked-eye readout and demonstrate a shorter time-to-result across a range of target antigen concentrations and fewer false negatives compared to human subjects at low antigen concentrations.

SUBMITTER: Colombo M

PROVIDER: S-EPMC9850356 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

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Real-time, smartphone-based processing of lateral flow assays for early failure detection and rapid testing workflows.

Colombo Monika M Bezinge Léonard L Rocha Tapia Andres A Shih Chih-Jen CJ de Mello Andrew J AJ Richards Daniel A DA

Sensors & diagnostics 20221201 1

Despite their simplicity, lateral flow immunoassays (LFIAs) remain a crucial weapon in the diagnostic arsenal, particularly at the point-of-need. However, methods for analysing LFIAs still rely heavily on sub-optimal human readout and rudimentary end-point analysis. This negatively impacts both testing accuracy and testing times, ultimately lowering diagnostic throughput. Herein, we present an automated computational imaging method for processing and analysing multiple LFIAs in real-time and in ...[more]

PMID: 36741250

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Project description:ObjectiveThere is a lack of evidence addressing several important human factors questions pertaining to the quality of supportive information provided by commercial manufacturers that can affect the adoption and use of lateral flow serology assays in practice. We aimed to: (1) identify and assess the quality of information that commercial manufacturers provided for their point-of-care tests (POCTs) and (2) examine the implications of these findings on real-world settings.DesignWe used a content analysis methodology in two stages to systematically, code and analyse textual data from documents of commercial manufacturers. A deductive approach was applied using a coding guide based on the validated Point-of-Care Key Evidence Tool (POCKET) multidimensional checklist. An inductive approach was used to identify new patterns or themes generated from our textual analysis.SettingPublicly available supportive information documents by commercial manufacturers for lateral flow serology, were identified and gathered from online searches.ParticipantsSupportive information documents retrieved from online searches over 3 months (March 2020 to June 2020).ResultsA total of 79 POCTs were identified that met the study inclusion criteria. Using the POCKET coding guide, we found that the quality of information varied significantly between the manufacturers and was often lacking in detail. Our inductive approach further examined these topics and found that several statements were vague and that significant variations in the level of details existed between manufacturers.ConclusionsThis study revealed significant concerns surrounding the supportive information reported by manufacturers for lateral flow serology assays. Information transparency was poor and human factor issues were not properly addressed to mitigate the risk of improper device use, although it should be noted that the results of our study are limited by the data that manufactures were prepared to disclose. Overall, commercial manufacturers should improve the quality and value of information presented in their supporting documentation.

Project description:BackgroundAccurate diagnosis followed by timely treatment is an effective strategy for the prevention of complications together with reducing schistosomiasis transmission. Recombinase Polymerase Amplification (RPA) is a simple, rapid, sensitive, and specific isothermal method with low resource needs. This research aimed at the development and optimisation of a real-time (RT) and a lateral flow (LF) RPA assay for the detection of Schistosoma mansoni.MethodologyRecombinase Polymerase Amplification reactions were performed at full- (as recommended) and half-volumes (to reduce costs), with RT or LF detection systems targeting the S. mansoni mitochondrial minisatellite region. The specificity was assessed using gDNA from other Schistosoma species, helminths co-endemic with S. mansoni, human stool, and urine, and Biomphalaria snail hosts. The analytical sensitivity was evaluated using serial dilutions of gDNA, synthetic copies of the target, and single eggs. The ability of both assays to detect the S. mansoni DNA in human urine and stool samples was also tested. The long-term stability of the RT-RPA reagents was evaluated by storing the reaction components in different temperature conditions for up to 3 weeks.ResultsThe RT- and the LF-RPA (SmMIT- and SmMIT-LF-RPA, respectively) presented similar results when used full- and half-volumes, thus the latter was followed in all experiments. The SmMIT-RPA was 100% specific to S. mansoni, able to detect a single egg, with a limit of detection (LOD) of down to 1 fg of gDNA and one synthetic copy of the target. The assay was able to detect S. mansoni DNA from stool containing 1 egg/g and in spiked urine at a concentration of 10 fg/μl. SmMIT-RPA reagents were stable for up to 3 weeks when kept at 19°C, and 2 weeks when stored at 27°C. The SmMIT-LF-RPA cross-reacted with Clinostomidae, presented the LOD of 10 fg and one synthetic copy of the target, being able to detect a single egg and 1 egg/g in a stool sample. The LOD in spiked urine samples was 10 pg/μl.ConclusionThe half-volume SmMIT-RPA is a promising method to be used in the field. It is specific, sensitive, robust, and tolerant to inhibitors, with a long-term stability of the reaction components and the real-time visualisation of results.

Dataset Information

Real-time, smartphone-based processing of lateral flow assays for early failure detection and rapid testing workflows.

Publications

Real-time, smartphone-based processing of lateral flow assays for early failure detection and rapid testing workflows.

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