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Despite the potentialities of electrochemical sensors, these devices still encounter challenges in devising high-throughput and accurate drug susceptibility testing. The lack of platforms for providing these analyses over the preclinical trials of drug candidates remains a significant barrier to developing medicines. In this way, ultradense electrochemical chips are combined with machine learning (ML) to enable high-throughput, user-friendly, and accurate determination of the viability of 2D tumor cells (breast and colorectal) aiming at drug susceptibility assays. The effect of doxorubicin (anticancer drug model) was assessed through cell detachment electrochemical assays by interrogating Ru(NH 3 ) 6 with square wave voltammetry (SWV). This positive probe is presumed to imply sensitive monitoring of the on-sensor cellular death because of its electrostatic preconcentration in the so-called nanogap zone between the electrode surface and adherent cells. High-throughput assays were obtained by merging fast individual SWV measurements (9 s) with the ability of chips to yield analyses of Ru(NH 3+ with square wave voltammetry (SWV). This positive probe is presumed to imply sensitive monitoring of the on-sensor cellular death because of its electrostatic preconcentration in the so-called nanogap zone between the electrode surface and adherent cells. High-throughput assays were obtained by merging fast individual SWV measurements (9 s) with the ability of chips to yield analyses of Ru(NH 3 in series. The approach's applicability was demonstrated across two analysis formats, drop-casting and microfluidic assays. One should also mention that fitting a multivariate descriptor from selected input data via ML proved to be essential to providing accurate determinations (98 to 104%) of cell viability and half-maximal lethal concentration of the drug. The achieved results underscore the potential of the method in steering electrochemical sensors toward enabling high-throughput drug screening in practical applications.6 3+ in series. The approach's applicability was demonstrated across two analysis formats, drop-casting and microfluidic assays. One should also mention that fitting a multivariate descriptor from selected input data via ML proved to be essential to providing accurate determinations (98 to 104%) of cell viability and half-maximal lethal concentration of the drug. The achieved results underscore the potential of the method in steering electrochemical sensors toward enabling high-throughput drug screening in practical applications.

Flow assurance is a long-term challenge for oil and gas exploration as it plays a key role in designing safe and efficient operation techniques to ensure the uninterrupted transport of reservoir fluids. In this regard, the sensitive monitoring of the scale formation process is important by providing an accurate assessment of the minimum inhibitor concentration (MIC) of antiscale products. The optimum dosage of antiscale inputs is of pivotal relevance as their application at concentrations both lower and higher than MIC can imply pipeline blockages, critically hindering the entire supply chain of oil-related inputs and products to society. Using a simple and low-cost impedimetric platform, we here address the monitoring of the scale formation on stainless-steel capillaries from its early stages under real topside (ambient pressure and 60 °C) and subsea (1000 psi and 80 °C) sceneries of the oil industry. The method could continuously gauge the scale formation with a sensitivity higher than the conventional approach, i.e., the tube blocking test (TBT), which proved to be mandatory for avoiding misleading inferences on the MIC. In fact, whereas our sensor could entail accurate MICs, as confirmed by scanning electron microscopy, TBT suffered from negative deviations, with the predicted MICs being lower than the real values. Importantly, the impedance measurements were performed through a hand-held, user-friendly workstation. In this way, our method is envisioned to deliver an attractive and readily deployable platform to combat the scale formation issues because it can continuously monitor the salt precipitation from its early stages and yield the accurate determination of MIC., Competing Interests: The authors declare the following competing financial interest(s): W.J.P., V.M.S.F., L.C.S.V., J. M. S., B.C.C., A.L.G. and R.S.L. are listed as inventors on a patent filing application describing this technology., (© 2024 The Authors. Published by American Chemical Society.)