A significant amount of noteworthy articles reviewing different label-free biosensors are being published in the last years. Most of the times, the comparison among the different biosensors is limited by the procedure used of calculating the limit of detection and the measurement uncertainty. This article clarifies and establishes a simple procedure to determine the calibration function and the uncertainty of the concentration measured at any point of the measuring interval of a generic label-free biosensor. The value of the limit of detection arises naturally from this model as the limit at which uncertainty tends when the concentration tends to zero. The need to provide additional information, such as the measurement interval and its linearity, among others, on the analytical systems and biosensor in addition to the detection limit is pointed out. Finally, the model is applied to curves that are typically obtained in immunoassays and a discussion is made on the application validity of the model and its limitations.

The standard rapid approach for the diagnosis of coronavirus disease 2019 (COVID-19) is the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA. The detection of specific anti-SARS-CoV-2 immunoglobulins is crucial for screening people who have been exposed to the virus, whether or not they presented symptoms. Recent publications report different methods for the detection of specific IgGs, IgMs, and IgAs against SARS-CoV-2; these methods mainly detect immunoglobulins in the serum using conventional techniques such as rapid lateral flow tests or enzyme-linked immunosorbent assay (ELISA). In this article, we report the production of recombinant SARS-CoV-2 spike protein and the development of a rapid, reliable, cost-effective test, capable of detecting immunoglobulins in serum and saliva samples. This method is based on interferometric optical detection. The results obtained using this method and those obtained using ELISA were compared. Owing to its low cost and simplicity, this test can be used periodically for the early detection, surveillance, detection of immunity, and control of the spread of COVID-19.

This work describes a procedure to obtain the limit of detection (LoD) of a biosensor device from a set of measurements that we call immunoassays, which consists of testing the device's response to different concentrations of the molecule, which has to be detected throughout its working range. The procedure, based on the recommendations of international organizations, provides general expressions to estimate the uncertainty throughout its working range and the LoD. In the metrological model, the contributions to the uncertainty, due to the determination of the parameters of the calibration curve, the resolution, the lack of repeatability and others are taken into account. The model is applied to experimental data from the calibration of a biosensor. Using iterative weighted least squares techniques, a general logistic function (6-parameters) has been fitted and used as a calibration curve. The example studied shows that the lack of repeatability is not always the most important contribution to the LoD. The final expression of the LoD is equivalent to that of the expanded uncertainty (for a coverage probability of 99.9%) assigned to the concentration when c ∼ = 0. This result permits seeing the LoD as the smallest concentration c measured with the device, whereby uncertainty interval [c − U 99.9% (c) , c + U 99.9% (c)] does not include negative values.

In the present work, highly multiplexed diagnostic KITs based on an Interferometric Optical Detection Method (IODM) were developed to evaluate six Coronavirus Disease 2019 (COVID-19)-related biomarkers. These biomarkers of COVID-19 were evaluated in 74 serum samples from severe, moderate, and mild patients with positive polymerase chain reaction (PCR), collected at the end of March 2020 in the Hospital Clínico San Carlos, in Madrid (Spain). The developed multiplexed diagnostic KITs were biofunctionalized to simultaneously measure different types of specific biomarkers involved in COVID-19. Thus, the serum samples were investigated by measuring the total specific Immunoglobulins (sIgT), specific Immunoglobulins G (sIgG), specific Immunoglobulins M (sIgM), specific Immunoglobulins A (sIgA), all of them against SARS-CoV-2, together with two biomarkers involved in inflammatory disorders, Ferritin (FER) and C Reactive Protein (CRP). To assess the results, a Multiple Linear Regression Model (MLRM) was carried out to study the influence of IgGs, IgMs, IgAs, FER, and CRP against the total sIgTs in these serum samples with a goodness of fit of 73.01% (Adjusted R-Squared).