Preparation of molecularly imprinted solid-phase microextraction fiber for the selective removal and extraction of the antiviral drug abacavir in environmental and biological matrices

• Preparation of a novel SPME MIP fiber with remarkable recognition properties.
• Selective removal and extraction of abacavir from environmental & biological media.
• Detailed adsorbent characterization and adsorption studies.
• Successful application of synthesized MIPs as SPME sorbents.
• Estimation of expanded uncertainty following a bottom-up approach.

In the present study, a molecularly imprinted solid-phase microextraction fiber (MIP-SPMEf) was synthesized and applied for the selective removal and extraction of the antiviral drug, abacavir (ABA). Morphology and structure characterization of fibers were performed by scanning electron microscopy and Fourier transform infrared spectra, respectively. The effects on the adsorption behavior of the process parameters were studied and the equilibrium data were fitted by the Langmuir, Freundlich and Langmuir-Freundlich models. The maximum adsorption capability (Qmax) was determined by Langmuir- Freundlich model and was 149 mg/g for MIP-SPMEf. In the next step, SPME methodology followed by liquid desorption and liquid chromatography with mass spectrometry (LC/MS) has been developed and evaluated for the determination of the target compound in environmental and biological matrices (surface waters, wastewaters and urine). Parameters that could influence SPME efficiency were investigated. Then, optimization of stirring speed, extraction time and salt content was carried out by using a central composite design (CCD) and response surface methodology (RSM). A quadratic model between dependent and independent variables was built. Under the optimum conditions (extraction time 40 min, stirring rate 650 rpm and salt content 0.3% NaCl w/v) the validated method presented a high sensitivity and selectivity with LODs and LOQs in the range of 10.1–13.6 and 33.3–43.9 ng/L, respectively. The developed method was successfully applied to the analysis of ABA in real samples. The percentage extraction efficiency ranged from 88 to 99% revealing good accuracy and absence of matrix effects.

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