Multivariate optimization of mebeverine analysis using molecularly imprinted polymer electrochemical sensor based on silver nanoparticles

Optimisation of electrochemical sensors based on molecularly imprinted polymers: from OFAT to machine learning

Molecularly imprinted polymers (MIPs) rely on synthetic engineered materials able to selectively bind and intimately recognise a target molecule through its size and functionalities. The way in which MIPs interact with their targets, and the magnitude of this interaction, is closely linked to the chemical properties derived during the polymerisation stages, which tailor them to their specific target. Hence, MIPs are in-deep studied in terms of their sensitivity and cross-reactivity, further being used for monitoring purposes of analytes in complex analytical samples. As MIPs are involved in sensor development within different approaches, a systematic optimisation and rational data-driven sensing is fundamental to obtaining a best-performant MIP sensor. In addition, the closer integration of MIPs in sensor development requires that the inner properties of the materials in terms of sensitivity and selectivity are maintained in the presence of competitive molecules, which focus is currently opened. Identifying computational models capable of predicting and reporting the best-performant configuration of electrochemical sensors based on MIPs is of immense importance. The application of chemometrics using design of experiments (DoE) is nowadays increasingly adopted during optimisation problems, which largely reduce the number of experimental trials. These approaches, together with the emergent machine learning (ML) tool in sensor data processing, represent the future trend in design and management of point-of-care configurations based on MIP sensing. This review provides an overview on the recent application of chemometrics tools in optimisation problems during development and analytical assessment of electrochemical sensors based on MIP receptors. A comprehensive discussion is first presented to cover the recent advancements on response surface methodologies (RSM) in optimisation studies of MIPs design. Therefore, the recent advent of machine learning in sensor data processing will be focused on MIPs development and analytical detection in sensors.

Prospective of Agro-Waste Husks for Biogenic Synthesis of Polymeric-Based CeO2/NiO Nanocomposite Sensor for Determination of Mebeverine Hydrochloride

BACKGROUND

The remarkable properties of nickel oxide (NiO) and cerium oxide (CeO₂) nanostructures have attracted considerable interest in these nanocomposites as potential electroactive materials for sensor construction.

METHODS

The mebeverine hydrochloride (MBHCl) content of commercial formulations was determined in this study using a unique factionalized CeO₂/NiO-nanocomposite-coated membrane sensor.

RESULTS

Mebeverine-phosphotungstate (MB-PT) was prepared by adding phosphotungstic acid to mebeverine hydrochloride and mixing with a polymeric matrix (polyvinyl chloride, PVC) and plasticizing agent o-nitrophenyl octyl ether. The new suggested sensor showed an excellent linear detection range of the selected analyte at 1.0 × 10^-8-1.0 × 10^-2 mol L^-1 with regression equation E_mV = (-29.429 ± 0.2) log [MB] + 347.86. However, the unfunctionalized sensor MB-PT displayed less linearity at 1.0 × 10^-5-1.0 × 10^-2 mol L^-1 drug solution with regression equation E_mV = (-26.603 ± 0.5) log [MB] + 256.81. By considering a number of factors, the applicability and validity of the suggested potentiometric system were improved following the rules of analytical methodological requirements.

CONCLUSION

The created potentiometric technique worked well for determining MB in bulk substance and in medical commercial samples.

Potentiometric determination of mebeverine hydrochloride antispasmodic drug based on molecular docking with different ionophores host-guest inclusion as a theoretical study

The scientific community has continued to pay particular attention to potentiometric sensors based on ion-selective membrane sensors as an energy-efficient, easy-to-use method suitable for microfabrication. To this end, potentiometric ion-selective sensors were used as an alternative green analytical instrument. Three distinct sensors relying on various ionophores were built and assessed. A cationic exchanger, tetra phenyl borate, was used in the polyvinyl chloride polymeric plasticized matrix using di octyl phthalate, where α, β, and γ cyclodextrins were utilized as ionophores. A comparative potentiometric analysis was carried out using three ion-selective sensor designs: α, β, and γ cyclodextrins sensors. β-Cyclodextrin significantly reduced the detection limit and improved the discriminative performance of mebeverine hydrochloride (MBV) in the pharmaceutical dosage form over α- and γ-cyclodextrins in the presence of other interfering chemicals. Additionally, a significant connection was made between the practical perspective and a theoretical investigation based on computational research. Nernstian potentiometric results for the optimum sensor were obtained for MBV in the range of concentrations 1.0 × 10^-2 to 1.0 × 10^-6 M, its slope was -58.70 ± 0.12 mV per decade with lower detection limits 4.50 × 10^-7 M. This computational molecular docking investigation clarified that the binding sites and modes were in good agreement with the experiment results. This investigation was applied to expect the interaction between MBV and the proposed sensors to ensure which ionophores were the best for MBV.

SENSOR FOR PREDNISOLONE DETECTION IN SPORTS DOPING

ABSTRACT Introduction: Prednisolone causes pro-inflammatory impulses to be inhibited and anti-inflammatory signals to be promoted. As a result, it alters how the body's immune system reacts to certain diseases. The World Anti-Doping Agency, however, has banned SNP and other glucocorticosteroids. An electrochemical sensor can be developed using a gold nanocomposite, polypyrrole nanoparticles and synthesized carbon nanotubes (Au-PPy NPs@CNTs). Objective: Develop an electrochemical sensor to detect prednisolone. Method: Au-PPy NPs@CNTs nanocomposite was chemically synthesized with a modified glassy carbon electrode (GCE) surface. Results: According to SEM data, the nanocomposite was composed of amorphous Au NPs, and PPy NPs deposited in tubes strongly entangled in a CNTs network. The wide linear range and low detection limit of the Au-PPy NPs@CNTs/GCE as prednisolone sensors were attributed to the combined catalytic performance of the Au and PPy NPs@CNTs nanostructures. Conclusion: The results of prednisolone detection in each specimen using the amperometric method indicated good accuracy. The accuracy and precision of Au-PPy NPs@CNTs/GCE for prednisolone detection were explored in blood samples from 5 young athletes aged 20-24 years who used prednisolone tablets (RSD less than 4.25%). In addition to monitoring prednisolone concentrations in athletes’ serum, Au-PPy NPs@CNTs/GCE can be used as a reliable prednisolone sensor. Level of evidence II; Therapeutic studies - investigating treatment outcomes.

Turbidimetric Determination of Mebeverine Hydrochloride in Pharmaceutical Formulations Using Two Consecutive Detection Zones under Continuous Flow Conditions

A simple, low cost and rapid flow injection turbidimetric method was developed and validated for mebeverine hydrochloride (MBH) determination in pharmaceutical preparations. The developed method is based on forming of a white, turbid ion-pair product as a result of a reaction between the MBH and sodium persulfate in a closed flow injection system where the sodium persulfate is used as precipitation reagent. The turbidity of the formed complex was measured at the detection angle of 180° (attenuated detection) using NAG dual&Solo (0-180°) detector which contained dual detections zones (i.e., measuring cells 1 & 2). The increase in the turbidity of the complex was directly proportional to the increase of the MBH concentration in the range of 2.0-10 µmol/L with a limit of detection 0.35 µmol/L, 0.9981 (R2), and 2.0-12 µmol/L with a limit of detection 0.4 µmol/L and 0.9973 (R2) for measuring cells 1 and 2, respectively. The intra-day precision for three serial estimations of 5.0 and 9.0 µmol/L of MBH exhibited an RSD % of 0.23 % and 0.77 % and 0.68 % and 0.13 %, for cell 1 & 2, respectively. While the inter-day precision for three serials of three days exhibited an RSD % of 0.03 % and 0.77 % and 0.11 % and 0.07 %, for measuring cells 1 & 2, respectively. The accuracy of the developed method has expressed as an error % (E%) and a Rec % (recovery percentage), which was between 100.35 to 101.15 and 99.70 to 101.56 for cell 1 and cell 2, respectively. The present flow injection method has shown no interference effect from the common excipients and permits quantitively determination of 60 samples per hour. The developed method was successfully applied for the quantitative determination of MBH in different tablets containing 135 mg with excellent recovery percentage.

Recent Advances of Nanomaterials-Based Molecularly Imprinted Electrochemical Sensors

Molecularly imprinted polymer (MIP) is illustrated as an analogue of a natural biological antibody-antigen system. MIP is an appropriate substrate for electrochemical sensors owing to its binding sites, which match the functional groups and spatial structure of the target analytes. However, the irregular shapes and slow electron transfer rate of MIP limit the sensitivity and conductivity of electrochemical sensors. Nanomaterials, famous for their prominent electron transfer capacity and specific surface area, are increasingly employed in modifications of MIP sensors. Staying ahead of traditional electrochemical sensors, nanomaterials-based MIP sensors represent excellent sensing and recognition capability. This review intends to illustrate their advances over the past five years. Current limitations and development prospects are also discussed.

Design and fabrication of electrochemical sensor based on molecularly imprinted polymer loaded onto silver nanoparticles for the detection of 17-β-Estradiol

In this research report, we prepared an electrochemical sensor based on the molecularly imprinted poly(p-aminophenol) supported by silver nanoparticles capped with 2-mercaptobenzoxazole (AgNP) for the selective and sensitive detection of endocrine disrupting 17β-estradiol (E2). The electropolymerization of the functional monomer prepared the proposed MIP composite-based sensor in the presence of E2 as a template. The recognition materials were characterized using Fourier transform infrared, cyclic voltammetry (CV), square wave voltammetry (SWV), scanning electron microscopy, energy-dispersive X-ray spectroscopy and x-ray powder diffraction techniques. The electrochemical measurements were performed by employing both CV and SWV methods. We did the optimization of critical parameters affecting the sensor performances through the experimental design and verification. The developed sensor showed a linear range from 10 pM to 100 nM with the calculated quantification and detection limits of 1.86 pM and 6.19 pM, respectively. The incorporation of AgNP with high electrical conductivity into the MIP matrix enhanced the sensor's performance. Furthermore, the sensor was applied to determine E2 in real water samples without any sample preconcentration steps to achieve the percent recovery of 91.87-98.36% and acceptable reusability and storage stability performances. This article is protected by copyright. All rights reserved.

Recent Developments in Voltammetric Analysis of Pharmaceuticals Using Disposable Pencil Graphite Electrodes

The even growing production of both well-known and new derivatives with pharmaceutical action involves the need for developing facile and reliable methods for the analysis of these compounds. Among the widely used instrumental techniques, the electrochemical ones are probably the simplest and the most rapid, also having good performance characteristics. However, the key tool in electroanalysis is the working electrode. Due to the inherent electrochemical and economic advantages of the pencil graphite electrode (PGE), the interest in its applicability in the analysis of different analytes has continuously increased in recent years. Thus, this paper aims to review the scientific reports published in the last 10 years on the use of the disposable eco- and user-friendly PGEs in the electroanalysis of compounds of pharmaceutical importance in different matrices. The PGE characteristics and designs (bare or modified with various types of materials), along with their applications and performance parameters (e.g., linear range, limit of detection, and reproducibility), will be discussed, and their advantages and limitations will be critically emphasized.

Molecularly Imprinted Polymers (MIPs) in Sensors for Environmental and Biomedical Applications: A Review

Molecular imprinted polymers are custom made materials with specific recognition sites for a target molecule. Their specificity and the variety of materials and physical shapes in which they can be fabricated make them ideal components for sensing platforms. Despite their excellent properties, MIP-based sensors have rarely left the academic laboratory environment. This work presents a comprehensive review of recent reports in the environmental and biomedical fields, with a focus on electrochemical and optical signaling mechanisms. The discussion aims to identify knowledge gaps that hinder the translation of MIP-based technology from research laboratories to commercialization.

The Use of Computational Methods for the Development of Molecularly Imprinted Polymers

Recent years have witnessed a dramatic increase in the use of theoretical and computational approaches in the study and development of molecular imprinting systems. These tools are being used to either improve understanding of the mechanisms underlying the function of molecular imprinting systems or for the design of new systems. Here, we present an overview of the literature describing the application of theoretical and computational techniques to the different stages of the molecular imprinting process (pre-polymerization mixture, polymerization process and ligand-molecularly imprinted polymer rebinding), along with an analysis of trends within and the current status of this aspect of the molecular imprinting field.

Electropolymerised Polypyrroles as Active Layers for Molecularly Imprinted Sensors: Fabrication and Applications

Conjugated polymers are widely used in the development of sensors, but even though they are sensitive and robust, they typically show limited selectivity, being cross-sensitive to many substances. In turn, molecular imprinting is a method involving modification of the microstructure of the surface to incorporate cavities, whose shape matches that of the “template”—the analyte to be detected, resulting in high selectivity. The primary goal of this review is to report on and briefly explain the most relevant recent developments related to sensors utilising molecularly imprinted polypyrrole layers and their applications, particularly regarding the detection of bioactive substances. The key approaches to depositing such layers and the most relevant types of analytes are highlighted, and the various trends in the development of this type of sensors are explored.

Non-enzymatic lactose molecularly imprinted sensor based on disposable graphite paper electrode

Lactose (LAC) is a disaccharide - major sugar, present in milk and dairy products. LAC content is an important indicator of milk quality and abnormalities in food industries, as well as in human and animal health. The present study reports the development of an innovative imprinted voltammetric sensor for sensitive detection of LAC. The sensor was constructed using electropolymerized pyrrole (Py) molecularly imprinted polymer (MIP) on graphite paper electrode (PE). The MIP film was constructed through the electrosynthesis of polypyrrole (PPy) in the presence of LAC (template molecule) on PE (PPy/PE). To optimize the detection conditions, several factors affecting the PPy/PE sensor performance were assessed by multivariate methods (Plackett-Burman design and central composite design). Under optimized conditions, the proposed analytical method was applied for LAC detection in whole and LAC-free milks, where it demonstrated high sensitivity and selectivity, with two dynamic linear ranges of concentration (1.0-10 nmol L^-1 and 25-125 nmol L^-1) and a detection limit of 0.88 nmol L^-1. The MIP sensor showed selective molecular recognition for LAC in the presence of structurally related molecules. The proposed PPy/PE sensor exhibited good stability, as well as excellent reproducibility and repeatability. Based on the results obtained, the PPy/PE is found to be highly promising for sensitive detection of LAC.