Competitive Adsorption of Anti-Parkinson Drugs on Different Amberlite Resins from Water: Quantitative Analysis by Ultra Performance Liquid Chromatography (UPLC)

Abstract

Anti-Parkinson drugs, levodopa and entacapone, are potential pollutants of concern that need to be removed from water. These drug compounds generally occur in the aqueous medium in the form of multicomponent mixtures. This work focuses on the competitive adsorption effects of multiple anti-Parkinson drugs in single and binary systems. Four effective Amberlite IRA resins (IRA-67, IRA-96, IRA-400, and IRA-958) have been utilized as adsorbents. The quantitative analysis of anti-Parkinson drugs was performed by a rapid and sensitive ultra performance liquid chromatography (UPLC) method. The structure and surface chemistry of Amberlite resins were characterized by Fourier transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD), and scanning electron microscopy (SEM). The results of single and binary drug systems showed that the affinity sequence of Amberlite IRA resins toward the anti-Parkinson drugs changed as entacapone > levodopa. In most examined conditions, in the case of binary system, entacapone enhanced the levodopa adsorption. Conversely, levodopa suppressed the adsorption of entacapone in the binary system. The highest total adsorption capacity values were found as 35.59 mg.g(-1) and 73.01 mg.g(-1) for single levodopa and entacapone systems, respectively, and 83.44 mg.g(-1) for binary (levodopa + entacapone) system. Amberlite IRA-67 showed high performance in the adsorption of entacapone in aqueous solutions, presenting a higher adsorption capacity with 73.01 mg.g(-1) in single system and 48.33 mg.g(-1) in binary system. The experimental data were modeled using single-component adsorption isotherm models (Langmuir, Freundlich, and Temkin) and multi-component adsorption isotherm models (non-modified Langmuir, modified Langmuir, and extended Freundlich). The single adsorption of two drugs obeyed well the Langmuir isotherm model (R-2 >= 0.9). The binary drug adsorption data exhibited a good fit to the single-component and multi-component adsorption isotherm models studied.