Innovative sensors with selectivity enhancement by molecularly imprinted polymers for the concurrent quantification of donepezil and memantine

Abstract

Ion-selective sensors are widely employed in various pharmaceutical, environmental, and biological analytical applications due to their simplicity, cost-effectiveness, and rapid response times. They suffer from some challenges though. These challenges may arise from the selective sensing process that can be hindered by interference from ions with similar charges or suitable lipophilicity. Solid contact type due to water layer formation between the sensing surfaces may also appear as an obstacle. This work is dedicated to overcoming the selectivity issue using the molecularly imprinted polymer (MIP) approach to determine Donepezil (DON) and Memantine (MEM) in their combined pharmaceutical formulation. Precipitation polymerization approach was employed for the preparation of the MIP for each drug. The resulting MIPs were thoroughly examined using various characterization methods. The potential response of the proposed sensors was stabilized by applying graphene nanoplatelets as an ion-to-electron transducer layer. This layer prevented the formation of the water layer, improved the responses, and enhanced charge transfer. Two sensors featuring different cationic exchangers were designed for the selective determination of donepezil, for which one sensor was developed for memantine analysis by adding the corresponding MIPs to the membrane components. The achieved detection limits were 5.01 × 10^-8 M & 4.47 × 10^-7 M for DON and 2.24 × 10^-7 M for MEM, with slope values of 56.77 mV per decade, 56.91 mV per decade, and 55.87 mV per decade, respectively. Each sensor was successfully employed for the selective determination of its corresponding drug in the combined formulations and spiked human plasma samples without interference.

Fig. 1. (a) DON cationic exchangers (linearity ranges (1.0 × 10⁻⁵ to 1.0 × 10⁻² M) except for TPB (1.0 × 10⁻⁶ to 1.0 × 10⁻² M)), b) MEM cationic exchangers [linearity ranges (1.0 × 10⁻⁶ to 1.0 × 10⁻² M)].

Fig. 2. SEM surface images of: (a) DON-MIP, (b) MEM-MIP, (c) NIP.

Fig. 3. Potential profile in mV vs. log concentration of: (a) DON by TPB sensors: MIP/GR/GCE (1.0 × 10⁻⁷ to 1.0 × 10⁻² M), GR/GCE (1.0 × 10⁻⁶ to 1.0 × 10⁻² M) and unmodified GCE (1.0 × 10⁻⁶ to 1.0 × 10⁻² M), (b) DON by K-TCPB sensors: MIP/GR/GCE (1.0 × 10⁻⁶ to 1.0 × 10⁻² M), GR/GCE (1.0 × 10⁻⁶ to 1.0 × 10⁻² M) and unmodified GCE (1.0 × 10⁻⁵ to 1.0 × 10⁻² M), (c) MEM by K-TFMPB sensors: MIP/GR/GCE (1.0 × 10⁻⁶ to 1.0 × 10⁻² M), GR/GCE (1.0 × 10⁻⁶ to 1.0 × 10⁻² M) and unmodified GCE (1.0 × 10⁻⁶ to 1.0 × 10⁻² M), all along with their corresponding slopes.

Fig. 4. Water layer test of: (a) DON by TPB sensors, (b) DON by K-TCPB sensors, (c) MEM by K-TFMPB sensors, using GR-modified and unmodified sensors.

Fig. 5. Response of various sensors of: (A) DON-TPB as function of log concentration of (a) DON and (b) MEM, (B) DON-TCPB as function of log concentration of (c) DON and (d) MEM, (C) MEM-TFMPB as function of log concentration of (e) MEM and (f) DON, where values between parentheses represent the slope in (a, c and e) figures, and slope and (log K^pot_drug,I) in (b, d and f) figures.