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Updated: Jan 25, 2026

Quantification of the Immunosuppressant Tacrolimus on Dried Blood Spots Using LC-MS/MS
Published on: November 8, 2015
Development and validation of an LC-MS/MS method for the analysis of ivermectin in plasma, whole blood, and dried
Urs Duthaler1, Claudia Suenderhauf1, Stefan Gaugler2
1Division of Clinical Pharmacology & Toxicology, Department of Biomedicine, University and University Hospital Basel, Switzerland.
Abstract:
Ivermectin is deployed in mass drug administration (MDA) campaigns to control parasitic diseases in the tropics, with billions of treatments having been administered in the last three decades. Simple blood sampling tools, like the dried blood spots (DBS) technique, are needed to monitor treatments in such challenging settings. Thus, we developed a fully automated method for the analysis of ivermectin in DBS microsamples, including a bioanalytical and clinical validation. Automated extraction was carried out using a DBS-MS 500 autosampler which was coupled to a LC-MS/MS system. DBS were extracted with 20 μL solvent and eluted on a C8 analytical column. Analysis was performed by multiple reaction monitoring in the positive mode. Automated DBS extraction resulted in consistent recoveries (62.8 ± 4.3%) and matrix effects (68.0 ± 8.1%) between different donors and concentration levels. Intra- and inter-day accuracy and precision deviations were ≤15%, while samples with hematocrits from 20 to 60% could be quantified reliably. The achieved sensitivity of 1 ng/mL in DBS samples is sufficient to analyze ivermectin at the dose given (single oral administration of 12 mg) over a period of at least 72 h post treatment. Importantly, DBS samples are stable after one-month storage at room temperature (accuracy: 88.8-96.2%), thus samples collected in the field must not be shipped on dry ice. Ivermectin concentrations in venous and capillary blood agreed strongly, with a mean difference of -4.8%. Moreover, the drying process of DBS did not alter the analysis and importantly plasma concentrations can be estimated from DBS data using the hematocrit and red blood cell partitioning as correction factor. Our method enables uncomplicated sample collection and shipment as well as automated analysis of large amounts of samples, which is key to surveying MDA campaigns in remote settings.
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