Novel Micro-LC-MS/MS Method for the Quantification of Tenofovir and Its Active Metabolite Tenofovir-Diphosphate in Biological Matrices for Therapeutic Drug Monitoring.

Abstract

Background/Objectives: Sustained drug exposure is a key factor in the treatment of patients infected with human immunodeficiency virus (HIV) or hepatitis B virus (HBV) in order to achieve the intended virological response. Although influenced also by other parameters, adherence to the treatment scheme is the most important for adequate drug exposure. This can be assessed by therapeutic drug monitoring (TDM). Tenofovir (TFV) is a nucleotide analogue used in the treatment of both HIV and HBV. Although various analytical methods for the quantification of tenofovir prodrugs have been published, there is limited literature on methods for simultaneous TFV and its active metabolite, tenofovir diphosphate (TFVDP) direct determination. Methods: In this study, we describe a novel micro-liquid-chromatography-mass spectrometry (micro-LC-MS/MS) method for TDM of TFV and TFVDP in biological matrices (whole blood, plasma). The challenging separation of the high-polarity analytes was resolved on an amino stationary phase, eluted in HILIC (hydrophilic interaction liquid chromatography) mode. The sample preparation included a clean-up step with hexane for the removal of lipophilic compounds and then protein precipitation with organic solvent. Results: The achieved low limits of quantification in blood were 0.25 ng/mL for TFV, and 0.5 ng/mL for TFVDP. Linearity, accuracy (91.63-109.18%), precision (2.48-14.08), and stability were validated for whole blood matrix, meeting the guidelines performance criteria. Samples collected from treated patients were analyzed, with results being in accordance with the reported pharmacokinetics. Conclusions: The new method is adequate for analyzing samples in a clinical set-up. The measurement of both TFV and TFVDP improves clinical decision by an in-depth evaluation of long-term adherence, and together with viral load and resistance data helps guiding the treatment towards the intended virological suppression.