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Continuous and automated slug flow nanoextraction for rapid partition coefficient measurement.
- Source :
-
The Analyst [Analyst] 2021 Sep 13; Vol. 146 (18), pp. 5722-5731. Date of Electronic Publication: 2021 Sep 13. - Publication Year :
- 2021
-
Abstract
- Octanol-water partition coefficients (log K <subscript>ow</subscript> ) are widely used in pharmaceutical and environmental chemistry to assess the lipophilicity of compounds. Traditionally log K <subscript>ow</subscript> is determined using a shake-flask method that uses milliliters of sample and solvent and requires hours for preparation, extraction, and analysis. Here, we report an automated system for rapid log K <subscript>ow</subscript> determination for an array of compounds using slug flow nanoextraction (SFNE) enabled by a microfluidic chip. In the method, an autosampler is used to introduce 1 μL of sample into a microfluidic device that segments the injected volume into a series of 4 nL slugs that are each paired to an adjacent octanol slug. Each octanol-water phase pair is compartmentalized by an immiscible fluorous carrier fluid. During flow, rapid extraction occurs at each octanol-water interface. The resulting linear array of slugs flows into an online UV absorbance detector that is used to determine concentrations in the phases, allowing the log K <subscript>ow</subscript> to be measured. The microfluidic device allows toggling between two-phase "aqueous plug" generation (aqueous sample separated by fluorous carrier fluid) and three-phase "phase pair" generation. In this way, online calibration for detection in the aqueous phase can be achieved. The method is applied to determining log K <subscript>ow</subscript> for a panel of seven pharmaceutical compounds, including complete calibration curves, at three different pHs in under 2 h using 5 μL of extraction standard and 2.9 μL of octanol per extraction standard analyzed.
- Subjects :
- Calibration
Octanols
Solvents
Water
Subjects
Details
- Language :
- English
- ISSN :
- 1364-5528
- Volume :
- 146
- Issue :
- 18
- Database :
- MEDLINE
- Journal :
- The Analyst
- Publication Type :
- Academic Journal
- Accession number :
- 34515695
- Full Text :
- https://doi.org/10.1039/d1an01156a