Green Electrochemical Sensing: Novel Ion-Selective Electrode Method for Precise Determination of Dimenhydrinate and its Metabolite along with Cinnarizine in Pharmaceutical and Plasma Samples

Shereen Hassan Boltia, E. M. Morgan, Reem H. Obaydo, Y. Fayez, M. Abdelkawy, H. Lotfy
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Abstract

Green and sustainable scientific research is crucial for health and environmental improvement. Electrochemical analysis simplifies complex processes, saving time and cost. Ion selective electrode method, a key in green analytical chemistry, was utilized. A highly selective solid contact sensor was developed for two applications, detecting cinnarizine (CIN) and dimenhydrinate (DMH) in pharmaceuticals, and identifying CIN and diphenhydramine (DIP) in human plasma. Careful selection of ionophores ensured accurate detection. Multi-wall carbon-nanotubes (MWCNTs) facilitate rapid and precise measurement. The concentration range for CIN, DMH, and DIP was 1 × 10−6 M to 1 × 10−2 M, with mean recovery% of 100.07 ± 0.80, 100.12 ± 0.76, and 100.07 ± 0.53, respectively. Validation parameters exhibited accuracy and precision, with accuracy results of 100.87 ± 0.89, 99.96 ± 0.42, and 99.82 ± 0.31, and LODs of 0.5 x 10-6, 1.0 x 10-7, and 0.2 x 10-6 for CIN, DMH, and DIP, respectively. The study highlighted benefits like speed, economy, and sustainability, emphasizing the electrode's reusability. SWOT analysis and environmental assessments further underscored its advantages, promising applications in pharmaceutical analysis and quality control.
绿色电化学传感:新型离子选择性电极法精确测定药物和血浆样品中的二苯海拉明及其代谢物和辛那利嗪
绿色和可持续的科学研究对于改善健康和环境至关重要。电化学分析简化了复杂的过程,节省了时间和成本。离子选择电极法是绿色分析化学的关键。研究人员开发了一种高选择性固体接触传感器,用于检测药品中的西那利嗪(CIN)和二苯海拉明(DMH),以及鉴定人体血浆中的西那利嗪和苯海拉明(DIP)。精心选择的离子发生器确保了检测的准确性。多壁碳纳米管(MWCNT)有助于快速精确地测量。CIN、DMH 和 DIP 的浓度范围为 1 × 10-6 M 至 1 × 10-2 M,平均回收率分别为 100.07 ± 0.80、100.12 ± 0.76 和 100.07 ± 0.53。验证参数显示了准确度和精密度,CIN、DMH 和 DIP 的准确度分别为 100.87 ± 0.89、99.96 ± 0.42 和 99.82 ± 0.31,LOD 分别为 0.5 x 10-6、1.0 x 10-7 和 0.2 x 10-6。该研究强调了电极的速度、经济性和可持续性等优点,并强调了电极的可重复使用性。SWOT 分析和环境评估进一步突出了其优势,有望应用于药物分析和质量控制。
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