Enhanced electromembrane extraction of acidic drugs using a chitosan-agarose hybrid gel membrane
In this study, a novel chitosan-agarose gel membrane was developed and applied in the gel electromembrane extraction (G-EME) technique to extract and preconcentrate two model acidic drugs, naproxen and ibuprofen, from urine samples. Chitosan, acting as a positively charged agent and viscosifier, sig...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-08-01
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| Series: | Advances in Sample Preparation |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S277258202500049X |
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| Summary: | In this study, a novel chitosan-agarose gel membrane was developed and applied in the gel electromembrane extraction (G-EME) technique to extract and preconcentrate two model acidic drugs, naproxen and ibuprofen, from urine samples. Chitosan, acting as a positively charged agent and viscosifier, significantly improved extraction efficiency by reducing electric current and minimizing the electroendosmosis (EEO) effect. The parameters affecting the extraction recoveries were optimized and evaluated using both one-variable-at-a-time and Box–Behnken design approaches alongside response surface methodology. To maximize drugs recovery from a 7.0 mL urine sample, the following parameters were optimized: a membrane composed of 3.0 % (w/v) agarose and 1.0 % (w/v) chitosan, pH of the gel membrane: 5.5, extraction voltage: 32.5 V, pH of the donor phase: 8.0, pH of the acceptor phase: 11.0, extraction time: 21 min, volume of acceptor phase: 200 µL, gel membrane thickness: ∼ 4 mm and donor phase stirring speed: 500 rpm. Under optimal conditions, the extraction recoveries were 60.4 % for naproxen and 81.9 % for ibuprofen. Limits of detection for naproxen and ibuprofen were 3.0 and 4.5 ng/mL, respectively. This method was successfully applied to quantify acidic drugs in real urine samples, achieving relative recoveries in the range of 91.2–94.9 %, demonstrating excellent reliability for biological matrices. |
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| ISSN: | 2772-5820 |