How accurate and precise are limited sampling strategies in estimating exposure to mycophenolic acid in people with autoimmune disease?

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 (AUC(12)) 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 AUC(12). A total of 13 studies were identified that assessed the correlation between single time points and MPA AUC(12) and/or examined the predictive performance of limited sampling strategies in estimating MPA AUC(12). 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 AUC(12) 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 AUC(12) 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 AUC(12) 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 AUC(12) 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

Sample collection, biobanking, and analysis

Pediatric pharmacokinetic studies require sampling of biofluids from neonates and children. Limitations on sampling frequency and sample volume complicate the design of these studies. In addition, strict guidelines, designed to guarantee patient safety, are in place. This chapter describes the practical implications of sample collection and their storage, with special focus on the selection of the appropriate type of biofluid and withdrawal technique. In addition, we describe appropriate measures for storage of these specimens, for example, in the context of biobanking, and the requirements on drug assay methods that they pose. Pharmacokinetic studies in children are possible, but they require careful selection of an appropriate sampling method, specimen volume, and assay method. The checklist provided could help prospective researchers with the design of an appropriate study protocol and infrastructur

Clinical pharmacokinetics and pharmacodynamics of mycophenolate in patients with autoimmune disease

Mycophenolic acid (MPA), the active drug moiety of mycophenolate, is a potent immunosuppressant agent, which is increasingly being used in the treatment of patients with various autoimmune diseases. An understanding of the pharmacokinetics and pharmacodynamics of mycophenolate in this population should assist the clinician with rational dosage decisions. This review aims to provide an overview of the published literature on the clinical pharmacokinetics of mycophenolate in autoimmune disease and a briefer summary of current pharmacodynamic knowledge, and to identify areas of potential future research in this field. A literature search was conducted using PubMed and EMBASE databases as well as bibliographies of relevant articles and 'on-line early' pages of key journals. Twenty-six pharmacokinetic/pharmacodynamic studies of mycophenolate in people with autoimmune disease were identified and appraised. Twenty-two of these studies used non-compartmental analysis techniques and four used population modelling methods to estimate mycophenolate pharmacokinetic parameters. Seven studies linked mycophenolate exposure to treatment outcomes. Only four studies measured free (unbound) as well as total mycophenolate exposure and only two studies characterised MPA disposition following entericcoated mycophenolate sodium (EC-MPS) administration. Across all studies MPA displayed erratic and complex pharmacokinetics with substantial between-subject variability. Based on total drug measurement, the dose-normalised MPA area under the plasma concentration-time curve (AUC) from 0 to 12 h post-dose (AUC(12)) varied at least five-to ten-fold between subjects. Typical values for apparent oral clearance (CL/F) of MPA during nonlinear mixed-effects modelling ranged from 8.3 to 25.3 L/h. Patient renal function, serum albumin levels, sex, ethnicity, food intake, concurrent administration of interacting drugs such as antacids, metal-containing medications and proton pump inhibitors and polymorphisms in genes encoding uridine diphosphate glucuronosyltransferase were identified in some studies as having a significant influence on the pharmacokinetics of mycophenolate. Typical MPA CL/F values in autoimmune disease patients were generally slightly lower than values published previously in population pharmacokinetic studies involving renal allograft recipients, possibly because of usage of ciclosporin, poorer renal function or lower serum albumin levels in the renal transplant cohort. In a single crossover study involving ten subjects only, significantly higher MPA AUC(12) and maximum MPA concentration (C-max) and lower MPA CL/F were reported following EC-MPS administration compared to mycophenolate mofetil administration. MPA exposure correlated well with treatment efficacy in patients with autoimmune disease (response to treatment, active disease and disease markers); however the relationship between MPA exposure and adverse events (infectious episodes, haematological toxicity and gastrointestinal symptoms) was unclear. Further investigation is required in autoimmune diseases such as chronic plaque psoriasis and rheumatoid arthritis and following EC-MPS administration. The extent of within-subject variability in the pharmacokinetics of mycophenolate is largely unknown and potential covariate influences need to be confirmed in studies with large subject numbers. A relationship between MPA and MPA metabolite exposure and toxicity needs to be established