Despite the remarkable development related to Point-of-Care devices based on optical technology, their difficulties when used outside of research laboratories are notable. In this sense, it would be interesting to ask ourselves what the degree of transferability of the research work to the market is, for example, by analysing the relation between the scientific work developed and the registered one, through patent. In this work, we provide an overview of the state-of-the-art in the sector of optical Point-of-Care devices, not only in the research area but also regarding their transfer to market. To this end, we explored a methodology for searching articles and patents to obtain an indicator that relates to both. This figure of merit to estimate this transfer is based on classifying the relevant research articles in the area and the patents that have been generated from these ones. To delimit the scope of this study, we researched the results of a large enough number of publications in the period from 2015 to 2020, by using keywords “biosensor”, “optic”, and “device” to obtain the most representative articles from Web of Science and Scopus. Then, we classified them according to a particular classification of the optical PoC devices. Once we had this sampling frame, we defined a patent search strategy to cross-link the article with a registered patent (by surfing Google Patents) and classified them accordingly to the categories described. Finally, we proposed a relative figure called Index of Technology Transference (IoTT), which estimates to what extent our findings in science materialized in published articles are protected by patent.

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 . This result permits seeing the LoD as the smallest concentration measured with the device, whereby uncertainty interval does not include negative values.

This paper proposes a novel readout methodology for improving the performance of Refractive Index (RI) based photonic transducers. Specifically, the authors focus on an optical transducer reported recently in the literature, the so-called Resonant Nano-Pillars (RNPs) transducer. The readout signal for this transducer is usually obtained based on the Wavelength Shift of the Resonant Mode (WSRM), which identifies a single point from the signal, such as the minimum of a resonant mode, whose wavelength shift or intensity value has a correlation with the RI of the media, and, therefore, with the monitored chemical component. This work proposes a novel spectral analysis through Principal Component Analysis (PCA), later inferring the property of interest by regression techniques. To evaluate the performance of the proposal, the authors mimic an agro-food experiment emulating a fermentation process as a proof of concept by measuring the ethanol concentration over time in two liquids: Deionized Water (DIW) and White Wine (WW). The authors compare both methods by inferring the ethanol concentration in the two experiments. As a result, the authors demonstrated experimentally that the proposal significantly outperformed the WSRM method, reporting an improvement of the Limit of Detection (LoD) of up to 140 times. Moreover, this PCA method can be also applied to many other biochemical sensing systems and transducers.

A controlled, 3D selective inductively coupled plasma reactive ion etching process (ICP-RIE) was employed to fabricate high aspect ratio tiered resonant nanopillars (TR-NPs) made of two Bragg reflectors consisting of a stack of Si₃N₄/SiO₂ alternate layers, a resonant SiO₂ central cavity, and nickel caps. The 3D etching process led to a vertical full etching, and also to a horizontal highly selective etching that preserves SiO₂ layers while the Si₃N₄ layers are slowly etched. Resulting TR-NPs periodic arrays were tested as optical sensors and highlighted a 28% increment in bulk sensitivity (379 nm RIU⁻¹) comparing with conventional Si₃N₄/SiO₂ resonant NPs without metal caps (296 nm RIU⁻¹) considering the resonance feature located in the 580-630 nm wavelength range.

In this work, it is reported for the first time the use of a network of periodic optical resonant nanopillars for sensing vapors of volatile organic components. In particular, this work evaluates the presence of methanol, ethanol, isopropanol, acetic acid, propionic acid, and toluene vapors at different working distances between the transducer and the surface of the sample in the liquid state, obtaining the sensing curve response of each one of them. In addition, it studies the thin film of liquid condensed onto the nanopillar surface, estimating their corresponding thickness value by means of numerical photonic simulations and their correlation with the corresponding vapor pressure of different specimens.