Development of a Nanobody-Based Screen-Printed Sensor for Cell Therapy Process Automation

Development of low cost screen-printed piezoresistive strain sensor for facial expressions recognition systems

The development of screen-printed electrochemical sensors represents a rapidly expanding research field with great potential for applications in the rapid and sensitive determination of drugs in complex matrices. This work presents a review of the state-of-the-art examples of this technology, focusing on its application in real matrices such as water, pharmaceutical formulations, and biological fluids. We discuss the main materials used in developing conductive inks, highlighting their properties and influence on sensor performance. The characterization of materials and sensors is crucial to ensure the reproducibility and reliability of results. Additionally, we address the challenges associated with the application of these sensors in complex matrices, such as interferences from other components and the need for sample pretreatment. Finally, we present future perspectives for developing screen-printed electrochemical sensors, with an emphasis on new technologies and materials that can improve the sensitivity, selectivity, and stability of these devices.

Broadly speaking, sensors are devices that detect and respond to changes in surroundings. Inputs can come from a variety of sources such as light, heat, motion, pressure, moisture, and similar physical parameter, and the outputs of sensors can be in any other form and mostly electrical pulses. If the sensors are connected to a network, they can share data with other connected devices or they can provide the requisite information to process control and automation systems. To a significant extent, cement manufacturing has been in the forefront of sensors application. For years the cement industry has been using sensors for detecting and controlling temperature, flow, level, speed, gas emissions, bulk solids composition, conveyor belt drift, operational hazards, etc. With increasing scale of production, more operational complexity, and higher levels of automation and control, the traditional sensors are being replaced with smart sensors, which are microprocessor driven and include features such as communication capability and on-board diagnostic function. The smart sensors provide information to a monitoring system for enhanced operational efficiency and a dedicated condition monitoring system prevents hardware problems before they occur. Despite such advancements in sensor technology, it is still not adequate for intelligent cement manufacturing, as there are several critical parameters in cement process that cannot be directly measured. This has led to the development of soft sensors, which try to quantify difficult-to-measure parameters from the knowledge of easy-to-measure online process variables. Substantial progress is seen in the development of soft sensors for intelligent cement manufacturing, particularly in the environment of artificial intelligence. The chapter attempts to trace the application trends of sensors technology to making the cement production sustainable and intelligent.

Enzyme-based sensors frequently produce unsatisfactory results such as poor reproducibility and insufficient long-term stability due to the natural instability of enzymes, stringent experimental conditions, and complicated immobilization procedures. Thus, an electrochemical non enzymatic sensor was fabricated by deposition of the multi-walled carbon nanotube (MWCNT) with zinc oxide nanoparticles (ZnO NP) and also molecular imprinted polymer (MIP) on a screen-printed carbon electrode (SPCE). Then, the modified electrode (SPCE/MWCNT/ZnO/MIP) was formed on the surface area of the SPCE. This study wanted to demonstrate the glucose detection between molecular imprinted polymer (MIP) which contained glucose as template, o-phenylenediamine (oPD) and potassium persulfate as initiators in 0.1 M PBS at pH 7 and non-imprinted polymer (NIP) without addition of the template. The characterization and evaluation of various factor such as sensitivity, selectivity and limit of detection (LOD) were investigated through cyclic voltammetry (CV) and scanning electron microscopy (SEM) was used to look up onto the surface area of the modified electrode. The SPCE/MWCNT/ZnO/MIP electrode sensor showed a linear glucose concentration range from 0, 0.5, 1, 2 to 5 mM (R2 = 0.9709). The sensitivity of the sensor was 0.3386 μA mM-1 cm-2 with low detection limit of 1.81 mM. The sensor showed good stability and reproducibility along with excellent anti-interference properties to ascorbic acid, lactic acid, tartaric acid, and acetic acid. Finally, the applicability of the as-prepared SPCE/MWCNT/ZnO/MIP electrode sensor was successfully studied for detection of glucose. The results obtained for our sensor confirm that it is a promising non-enzymatic glucose sensor to be used for practical purpose.

Today, air pollution has become a major society issue. With the increased development of motorized vehicles, polluting and even toxic gases are being released in increasing quantities into the atmosphere with all known consequences [1] [2]. With the apparition of the concerns about impacts of human activity into the global warming, European legislations have started to impose more and more drastic emission limits through the euro norms (euro 6B currently). The norms concern both particles and polluting gases emitted from motorized vehicles. In a close future, industries, and particularly those having combustion furnaces will also be impacted by the norm. Therefore, controlling emitted gases and particles has become a major issue for car manufacturers and the development of new sensors responding to the requirements of the harsh environments present in exhausts has emerged. In response to those requirements, electrochemical sensors based on solid-state ceramic electrolyte are well-adapted [3] [4]. However, like for gas sensors based on other transducing techniques, a lack of selectivity compels the sensors’ developers to find different methods to extract the analyte’s nature and concentration information. According to the sensing principle, the gas analytes will be discriminated according to different of their properties. For example, in the case of microbalances, the sensor’s response will rely only to the mass deposited. In this case, it seems difficult to discriminate the gas nature since the mass is not specific to one specie in particular. The output sensor’s signal will give concentration information but no information linked to analyte’s nature. Besides, in the case of electrochemical sensors (like for MOX sensors), the sensor’s response will both give information on the analyte’s concentration and on its redox behavior. Different models describing electrochemical sensors already exist in the literature for null current potentiometry based measurement (thermodynamic equilibrium). In this case, models used to describe the operation of the sensor are often based on the mixed potential theory [5]. However, only few of them describe the sensor’s kinetics behavior when used in electrolysis mode (imposed current potentiometry). In this work, two analytical models describing the response of an electrochemical sensor used in his electrolysis mode are proposed and compared. Those model results from the association of the Butler-Volmer equations and an equivalent electrical circuit describing the parallel reactions that can occur at the triple phase interfaces of the electrodes. The first model considers that both oxidizing gases and reducing gases react at the gold cathode whereas the second one considers that only oxidizing gases react at the gold cathode, the reducing gases just adsorbing on the cathode which induce slowing down of the reaction kinetics of other O2 oxidizing gas.Besides, to test those models, different experimental curves, obtained thanks to our gas test bench and our “homemade” screen-printed electrochemical sensors, were used. Apart from O2, which is always present in the dilution air or in the “base gas”, the sensors were exposed to four different polluting analytes: NO2, NO, NH3, CO. To perform curve fitting, MATLAB algorithms were developed. 3 methods were chosen perform curve fitting and parameters extraction: the Least Squares method, the Newton-Gauss method and the Levenberg-Marquardt method. For each one, an iterative algorithm was developed to extract the vector values containing the fitting parameters. First results indicate good fitting performance for both oxidizing and reducing gases in the case of model 2 whereas for the first model, relevant fitting results could only be obtained for oxidizing gases.

The advancement of machine learning and artificial intelligence has created potential for the automation of the time-consuming process of analyzing, evaluating, and interpreting large quantities of imagery. In order for the large-scale deployment of artificial intelligence in image analysis to be made possible, a new image rating system akin to the more traditional National Interpretability Rating Scale (NIIRS) must be created, so as to aid in the defining of system requirements in the development of new sensors. Through prototyping models using the open-source object detection library Detectron2 alongside proxy imagery from the Overhead Imagery Research Data Set (OIRDS), current limitations faced by machine learning algorithms in the context of target identification in aerial imagery are brought to light, including how they may affect a new image-rating scale, and insights into how such limitations could be overcome.

In recent years, interest in screen-printed electrodes (SPEs) has grown due to their wide range of applications. Diclofenac (DCF), a widely used non-steroidal anti-inflammatory drug, is a subject of interest in pharmaceutical research as well as environmental research, primarily due to its environmental contamination and therapeutic applications. This study describes the development and characterization of an innovative screen-printed sensor based on graphene oxide (GO) and phenanthroline (PHEN) for the rapid and highly sensitive determination of diclofenac. The modified sensor was characterized by Fourier Transform Infrared (FT-IR) spectroscopy and scanning electron microscopy (SEM). The electrochemical behavior of the screen-printed electrodes was assessed through cyclic voltammetry (CV) in phosphate buffer solution (PBS) and potassium ferrocyanide/potassium ferricyanide solution. The cyclic voltammograms of the electrodes modified with GO and PHEN revealed peaks in PBS related to redox processes of PHEN immobilized in the carbonaceous matrix. Additionally, the active surface area of the electrodes was found to be larger for the modified carbon screen-printed electrode with GO and PHEN, which also showed improved sensitivity to the detection of DCF. The limit of detection (1.53 nM) and the sensitivity of the novel sensor were promising, and these performance characteristics enabled the sensitive detection of DCF in different pharmaceutical products. The selectivity was confirmed to be appropriate based on recovery studies conducted with the pharmaceutical products, which produced values close to 100%.

The irrigation management based on the monitoring of the soil water content allows for the minimization of the amount of water applied, making its use more efficient. Taking into account these aspects, in this work, a sensor for measuring the soil water content was developed to allow real time automation of irrigation systems. This way, problems affecting crop yielding such as irregularities in the time to turn on or turn off the pump, and excess or deficit of water can be solved. To develop the sensors were used stainless steel rods, resin, and insulating varnish. The sensors measuring circuit was based on a microcontroller, which gives its output signal in the digital format. The sensors were calibrated using soil of the type “Quartzarenic Neosoil”. A third order polynomial model was fitted to the experimental data between the values of water content corresponding to the field capacity and the wilting point to correlate the soil water content obtained by the oven standard method with those measured by the electronic circuit, with a coefficient of determination of 93.17%, and an accuracy in the measures of ±0.010 kg kg-1. Based on the results, it was concluded that the sensor and its implemented measuring circuit can be used in the automation process of irrigation systems.

LB28 - Process automation helps standardize and de-risk thawing of cellular therapy products

Manufacturing of cellular products for therapeutic purposes like stem cell or cancer therapy requires equipment with specific characteristics not always addressed by conventional technologies. A new integrated cell processing device is presented that can handle all current technical requirements for manufacturing cellular products by automation of the complete process in a GMP‐compliant single‐use tubing set. Its capabilities are exemplified in the presented study by successful processing of adult stem cells, natural killer cells, and several cell lines. Multiple cell processing workflows can be automated in a functionally closed environment: from cell separation through cell culture to formulation of the final product.

Biopharma Is Going Digital … Bit by Bit

Stem cells are a population of precursor cells that are capable of developing into many different cell types in the body. They are unspecialized cells that can give rise to specialized cells and capable of dividing and renewing themselves for long periods. Based on the potency, stem cells can be totipotent, pluripotent, multipotent, oligopotent, unipotent and based on source it can be divided as embryonic, fetal, adult, amniotic fluid, cord blood, and induced pluripotent stem cells. Stem cell microenvironment (niche) providing support and stimuli to control stem cell properties. The application of stem cells in human medicine is well established and it is commonly used for chronic and accidental injuries and in veterinary medicine they rapidly become a visible tool for regenerative therapy of chronic, debilitating and various unresponsive clinical diseases and disorders. Unquestionably, the development of bioprocess technologies for the transfer of the current laboratory-based practice of stem cell tissue culture to the clinic as therapeutics necessitates the application of engineering principles and practices to achieve control, reproducibility, automation, validation and safety of the process and the product. A stem cell therapy is a treatment that uses stem cells, or cells that come from stem cells, to replace or to repair a patient’s cells or tissues that are damaged. Stem cells undoubtedly offer tremendous potential to treat many human and animal diseases and to repair tissue damage resulting from injury. Although stem cell holds pivotal promise in treatments of many incurable diseases, it has many critical limitations. Key words: Application, biology, bioprocess, limitation, niche, stem cells.