Automated high throughput analysis of antiretroviral drugs in dried blood spots.

Duthaler, U; Berger, B; Erb, S; Battegay, M; Letang, E; Gaugler, S; Krähenbühl, S; Haschke, Manuel Martin (2017). Automated high throughput analysis of antiretroviral drugs in dried blood spots. Journal of mass spectrometry, 52(8), pp. 534-542. Wiley 10.1002/jms.3952

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For therapeutic drug monitoring in remote settings, dried blood spots (DBS) are particularly advantageous, as blood sample collection and handling is uncomplicated. The aim of this study was to develop and validate an automated extraction method for the analysis of nevirapine, efavirenz and lopinavir in DBS samples. Automated extraction was performed with methanol : water (70 : 30 v/v), using a DBS-MS 500 autosampler coupled to a liquid chromatography tandem mass spectrometry system. The autosampler used digital images of each DBS to position the extraction head, sprayed 10 μl of internal standard onto each DBS and extracted a 4-mm disc (Ø) from the centre of each spot by unilateral flow using 25-μl extraction solvent. The analytes were baseline separated on a pentafluorophenyl column and analysed by using electrospray ionization with multiple reaction monitoring in positive polarity mode for nevirapine and lopinavir and in negative mode for efavirenz. The method was linear between 10 and 10 000 ng/ml for all analytes. Automated sample extraction resulted in consistent recoveries (nevirapine: 70 ± 6%, efavirenz: 63 ± 11% and lopinavir: 60 ± 10%) and matrix effects between different donors and concentration levels. Intra-day and inter-day accuracy and precision deviations were ≤15%. Manual and automated extractions of DBS samples collected within the framework of an adherence assessment study in rural Tanzania showed good agreements with deviations of less than 10%. Our study highlights that therapeutic drug monitoring samples obtained in the resource-constrained setting of rural Africa can be reliably determined by automated extraction of DBS. Overall, automatization improved method sensitivity and facilitates analysis of large sample numbers. Copyright © 2017 John Wiley & Sons, Ltd.

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