Assessment of capillary volumetric blood microsampling for the analysis of central nervous system drugs and metabolites.
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Abstract | :
Therapeutic drug monitoring (TDM) is an important tool for correlating the administered drug dose to drug and metabolite concentrations in the body and to therapeutic and adverse effects. In the case of treatment with drugs active on the central nervous system (CNS), frequent TDM becomes really useful, especially for patient compliance checking and for therapy optimisation. The selective serotonin reuptake inhibitors (SSRIs) fluoxetine and sertraline, chosen as target compounds for this study, are two antidepressants mainly used for major depression, but also for obsessive-compulsive disorder associated with neurodegenerative diseases and for eating disorders. Microsampling approaches can be used to make TDM patient-friendly, by means of minimally invasive fingerpricking instead of classic invasive venipuncture. In this study, an innovative volumetric microsampling approach based on the use of hemaPEN technology is proposed to simultaneously obtain four identical dried whole blood microsamples by means of a single capillary sampling. The developed strategy shows significant advantages in terms of blood collection and storage, fast and feasible extraction procedure and sensitive LC-MS/MS analysis, also providing satisfactory validation results (extraction yield >81%, RSD <12.0%, and <6.3% loss in analyte stability after 3 months). The proposed methodology has proven to be sound and reliable for application to the TDM of psychiatric patients treated with antidepressant drugs such as fluoxetine and sertraline. The original capillary volumetric microsampling procedure using hemaPEN has been demonstrated to be suitable for the accurate sampling of capillary whole blood, in order to be successfully exploited in self- and home-sampling procedures in future and to pave the way for precision medicine approaches for the treatment of CNS disorders. |
Year of Publication | :
2020
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Journal | :
The Analyst
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Volume | :
145
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Issue | :
17
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Number of Pages | :
5744-5753
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Date Published | :
2020
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ISSN Number | :
0003-2654
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URL | :
https://doi.org/10.1039/d0an01039a
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DOI | :
10.1039/d0an01039a
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Short Title | :
Analyst
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