This paper describes a new validated high performance liquid chromatography (HPLC) method for the simultaneous determination of two anti-cancer drugs, Arabinoside-C (Ara-C) and doxorubicin hydrochloride (DOX). A simultaneous determination method saves cost and time as both drugs can be injected into a single HPLC system without the need to change or re-equilibrate with a new mobile phase. The objective of the study is to develop a simultaneous determination method of two anti-cancer drugs, Ara-C and DOX. The mobile phase consisted of a mixture (45:55) of acetonitrile:ammonium hydrogen phosphate aqueous solution (0.01 M) at pH 6.2 at a flow rate of 0.3 ml/min, with UV detection at 252 nm. Separation was achieved on a C-18 column (5 µm: 250 mm × 4.6 mm) maintained at 30°C in a column oven. The method was linear between 325 ng/ml and 10 µg/ml for Ara-C and 625 ng/ml and 20 µg/ml for DOX. The limit of detection (LOD) was 20 ng/ml for Ara-C and 60 ng/ml for DOX. The developed HPLC method achieved good precision and accuracy as well as limit of quantitations. The developed and validated method is suitable to be used for routine analysis of Ara-C and DOX.
Mycophenolic acid (MPA) is a potent immunosuppressant agent, which is increasingly being used in the treatment of patients with various autoimmune diseases. Dosing to achieve a specific target MPA area under the concentration-time curve from 0 to 12 h post-dose (AUC12) is likely to lead to better treatment outcomes in patients with autoimmune disease than a standard fixed-dose strategy. This review summarizes the available published data around concentration monitoring strategies for MPA in patients with autoimmune disease and examines the accuracy and precision of methods reported to date using limited concentration-time points to estimate MPA AUC12. A total of 13 studies were identified that assessed the correlation between single time points and MPA AUC12 and/or examined the predictive performance of limited sampling strategies in estimating MPA AUC12. The majority of studies investigated mycophenolate mofetil (MMF) rather than the enteric-coated mycophenolate sodium (EC-MPS) formulation of MPA. Correlations between MPA trough concentrations and MPA AUC12 estimated by full concentration-time profiling ranged from 0.13 to 0.94 across ten studies, with the highest associations (r (2) = 0.90-0.94) observed in lupus nephritis patients. Correlations were generally higher in autoimmune disease patients compared with renal allograft recipients and higher after MMF compared with EC-MPS intake. Four studies investigated use of a limited sampling strategy to predict MPA AUC12 determined by full concentration-time profiling. Three studies used a limited sampling strategy consisting of a maximum combination of three sampling time points with the latest sample drawn 3-6 h after MMF intake, whereas the remaining study tested all combinations of sampling times. MPA AUC12 was best predicted when three samples were taken at pre-dose and at 1 and 3 h post-dose with a mean bias and imprecision of 0.8 and 22.6 % for multiple linear regression analysis and of -5.5 and 23.0 % for maximum a posteriori (MAP) Bayesian analysis. Although mean bias was less when data were analysed using multiple linear regression, MAP Bayesian analysis is preferable because of its flexibility with respect to sample timing. Estimation of MPA AUC12 following EC-MPS administration using a limited sampling strategy with samples drawn within 3 h post-dose resulted in biased and imprecise results, likely due to a longer time to reach a peak MPA concentration (t max) with this formulation and more variable pharmacokinetic profiles. Inclusion of later sampling time points that capture enterohepatic recirculation and t max improved the predictive performance of strategies to predict EC-MPS exposure. Given the considerable pharmacokinetic variability associated with mycophenolate therapy, limited sampling strategies may potentially help in individualizing patient dosing. However, a compromise needs to be made between the predictive performance of the strategy and its clinical feasibility. An opportunity exists to combine research efforts globally to create an open-source database for MPA (AUC, concentrations and outcomes) that can be used and prospectively evaluated for AUC target-controlled dosing of MPA in autoimmune diseases.