環境に優しいナノスケール認識：医薬品および血清サンプル中のアバカビルを選択的に測定するためのMIPベースの電気化学センサー

An advantageous electrochemical sensor was designed and fabricated for the sensitive and selective analysis of abacavir, an antiviral agent, by integrating the molecularly imprinted polymer (MIP) strategy and nanomaterial-based performance enhancement. The molecular imprinting was achieved on the glassy carbon electrode (GCE) surface through photopolymerization, using acrylamide (ACR) as the functional monomer and abacavir (ABC) as the template drug, and the system was computationally designed. Amine-functionalized multi-walled carbon nanotubes (MWCNT-NH₂) were incorporated into the polymeric network as a supporter to improve binding efficiency, active surface area, and porosity. The successfully formed MIP and specific recognition capability were verified through electrochemical and microscopic characterizations using cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), scanning electron microscopy (SEM), and Fourier transform infrared spectroscopy (FTIR) methods. A systematic optimization procedure was followed to design an efficient MIP sensor. As a result, the ACR-ABC/MWCNT-NH₂@MIP/GCE sensor exhibited a linear response in the range of 0.2 and 1 pM for standard solution and serum sample (corresponding correlation coefficient value of 0.999), with the corresponding limit of detection (LOD) values of 26.5 fM and 8.04 fM. In both solutions, good RSD% values (1.23% and 1.48%) were obtained, confirming the sensor's repeatability performance. Detailed selectivity tests validated the sensor's high affinity to ABC in the presence of structurally and pharmaceutically related drugs (lamivudine, zidovudine, tenofovir, etc.). The relative imprinting factor (IF') values were found to be higher than 2 for each compound. The ACR-ABC/MWCNT-NH₂@MIP/GCE sensor's sensitive and selective determination performance was further validated in serum and tablet samples, providing reliable recovery results (98.99-102.01%). Additionally, the Analytical GREEnness Metric Approach (AGREE), the Analytical Greenness Metric for Sample Preparation (AGREEprep), the Blue Applicability Grade Index (BAGI), and the Analytical Greenness Assessment Tool for Molecularly Imprinted Polymer Synthesis (AGREEMIP) tools were utilized to assess sensor's green profile. The ACR-ABC/MWCNT-NH₂@MIP/GCE sensor demonstrated its potential to provide a selective, reliable, low-cost, and efficient analytical tool for ABC analysis.