Measurement of free drug and clinical end-point by high-performance liquid chromatography-mass spectrometry: Applications and implications for pharmacokinetic and pharmacodynamic studies

Free drug measurement and pharmacodymanic markers provide the opportunity for a better understanding of drug efficacy and toxicity. High-performance liquid chromatography (HPLC)-mass spectrometry (MS) is a powerful analytical technique that could facilitate the measurement of free drug and these markers. Currently, there are very few published methods for the determination of free drug concentrations by HPLC-MS. The development of atmospheric pressure ionisation sources, together with on-line microdialysis or on-line equilibrium dialysis and column switching techniques have reduced sample run times and increased assay efficiency. The availability of such methods will aid in drug development and the clinical use of certain drugs, including anti-convulsants, anti-arrhythmics, immunosuppressants, local anaesthetics, anti-fungals and protease inhibitors. The history of free drug measurement and an overview of the current HPLC-MS applications for these drugs are discussed. Immunosuppressant drugs are used as an example for the application of HPLC-MS in the measurement of drug pharmacodynamics. Potential biomarkers of immunosuppression that could be measured by HPLC-MS include purine nucleoside/nucleotides, drug-protein complexes and phosphorylated peptides. At the proteomic level, two-dimensional gel electrophoresis combined with matrix-assisted laser desorption/ionisation time-of-flight (TOF) MS is a powerful tool for identifying proteins involved in the response to inflammatory mediators. (C) 2003 Elsevier Science B.V. All rights reserved.

Population pharmacokinetic analysis of mycophenolic acid in renal transplant recipients following oral administration of mycophenolate mofetil

Aim To develop a population pharmacokinetic model for mycophenolic acid in adult kidney transplant recipients, quantifying average population pharmacokinetic parameter values, and between- and within-subject variability and to evaluate the influence of covariates on the pharmacokinetic variability. Methods Pharmacokinetic data for mycophenolic acid and covariate information were previously available from 22 patients who underwent kidney transplantation at the Princess Alexandra Hospital. All patients received mycophenolate mofetil 1 g orally twice daily. A total of 557 concentration-time points were available. Data were analysed using the first-order method in NONMEM (version 5 level 1.1) using the G77 FORTRAN compiler. Results The best base model was a two-compartment model with a lag time (apparent oral clearance was 271 h(-1), and apparent volume of the central compartment 981). There was visual evidence of complex absorption and time-dependent clearance processes, but they could not be successfully modelled in this study. Weight was investigated as a covariate, but no significant relationship was determined. Conclusions The complexity in determining the pharmacokinetics of mycophenolic acid is currently underestimated. More complex pharmacokinetic models, though not supported by the limited data collected for this study, may prove useful in the future. The large between-subject and between-occasion variability and the possibility of nonlinear processes associated with the pharmacokinetics of mycophenolic acid raise questions about the value of the use of therapeutic monitoring and limited sampling strategies.

Prospective evaluation of a D-optimal designed population pharmacokinetic study

Recently, methods for computing D-optimal designs for population pharmacokinetic studies have become available. However there are few publications that have prospectively evaluated the benefits of D-optimality in population or single-subject settings. This study compared a population optimal design with an empirical design for estimating the base pharmacokinetic model for enoxaparin in a stratified randomized setting. The population pharmacokinetic D-optimal design for enoxaparin was estimated using the PFIM function (MATLAB version 6.0.0.88). The optimal design was based on a one-compartment model with lognormal between subject variability and proportional residual variability and consisted of a single design with three sampling windows (0-30 min, 1.5-5 hr and 11 - 12 hr post-dose) for all patients. The empirical design consisted of three sample time windows per patient from a total of nine windows that collectively represented the entire dose interval. Each patient was assigned to have one blood sample taken from three different windows. Windows for blood sampling times were also provided for the optimal design. Ninety six patients were recruited into the study who were currently receiving enoxaparin therapy. Patients were randomly assigned to either the optimal or empirical sampling design, stratified for body mass index. The exact times of blood samples and doses were recorded. Analysis was undertaken using NONMEM (version 5). The empirical design supported a one compartment linear model with additive residual error, while the optimal design supported a two compartment linear model with additive residual error as did the model derived from the full data set. A posterior predictive check was performed where the models arising from the empirical and optimal designs were used to predict into the full data set. This revealed the optimal'' design derived model was superior to the empirical design model in terms of precision and was similar to the model developed from the full dataset. This study suggests optimal design techniques may be useful, even when the optimized design was based on a model that was misspecified in terms of the structural and statistical models and when the implementation of the optimal designed study deviated from the nominal design.

What is the best size descriptor to use for pharmacokinetic studies in the obese?

The prevalence of obesity in the western world is dramatically rising, with many of these individuals requiring therapeutic intervention for a variety of disease states. Despite the growing prevalence of obesity there is a paucity of information describing how doses should be adjusted, or indeed whether they need to be adjusted, in the clinical setting. This review is aimed at identifying which descriptors of body size provide the most information about the relationship between dose and concentration in the obese. The size descriptors, weight, lean body weight, ideal body weight, body surface area, body mass index, fat-free mass, percent ideal body weight, adjusted body weight and predicted normal body weight were considered as potential size descriptors. We conducted an extensive review of the literature to identify studies that have assessed the quantitative relationship between the parameters clearance (CL) and volume of distribution (V) and these descriptors of body size. Surprisingly few studies have addressed the relationship between obesity and CL or V in a quantitative manner. Despite the lack of studies there were consistent findings: (i) most studies found total body weight to be the best descriptor of V. A further analysis of the studies that have addressed V found that total body weight or another descriptor that incorporated fat mass was the preferred descriptor for drugs that have high lipophilicity; (ii) in contrast, CL was best described by lean body mass and no apparent relationship between lipophilicity or clearance mechanism and preference for body size descriptor was found. In conclusion, no single descriptor described the influence of body size on both CL and V equally well. For drugs that are dosed chronically, and therefore CL is of primary concern, dosing for obese patients should not be based on their total weight. If a weight-based dose individualization is required then we would suggest that chronic drug dosing in the obese subject should be based on lean body weight, at least until a more robust size descriptor becomes available.

Quantitative justification for target concentration intervention - parameter variability and predictive performance using population pharmacokinetic models for aminoglycosides

Aims [1] To quantify the random and predictable components of variability for aminoglycoside clearance and volume of distribution [2] To investigate models for predicting aminoglycoside clearance in patients with low serum creatinine concentrations [3] To evaluate the predictive performance of initial dosing strategies for achieving an aminoglycoside target concentration. Methods Aminoglycoside demographic, dosing and concentration data were collected from 697 adult patients (>=20 years old) as part of standard clinical care using a target concentration intervention approach for dose individualization. It was assumed that aminoglycoside clearance had a renal and a nonrenal component, with the renal component being linearly related to predicted creatinine clearance. Results A two compartment pharmacokinetic model best described the aminoglycoside data. The addition of weight, age, sex and serum creatinine as covariates reduced the random component of between subject variability (BSVR) in clearance (CL) from 94% to 36% of population parameter variability (PPV). The final pharmacokinetic parameter estimates for the model with the best predictive performance were: CL, 4.7 l h(-1) 70 kg(-1); intercompartmental clearance (CLic), 1 l h(-1) 70 kg(-1); volume of central compartment (V-1), 19.5 l 70 kg(-1); volume of peripheral compartment (V-2) 11.2 l 70 kg(-1). Conclusions Using a fixed dose of aminoglycoside will achieve 35% of typical patients within 80-125% of a required dose. Covariate guided predictions increase this up to 61%. However, because we have shown that random within subject variability (WSVR) in clearance is less than safe and effective variability (SEV), target concentration intervention can potentially achieve safe and effective doses in 90% of patients.

Pharmacokinetic considerations relating to tacrolimus dosing in the elderly

Relaxation of the upper age limits for solid organ transplantation coupled with improvements in post-transplant survival have resulted in greater numbers of elderly patients receiving immunosuppressant drugs such as tacrolimus. Tacrolimus is a potent agent with a narrow therapeutic window and large inter- and intraindividual pharmacokinetic variability. Numerous physiological changes occur with aging that could potentially affect the pharmacokinetics of tacrolimus and, hence, patient dosage requirements. Tacrolimus is primarily metabolised by cytochrome P450 (CYP) 3A enzymes in the gut wall and liver. It is also a substrate for P-glycoprotein, which counter-transports diffused tacrolimus out of intestinal cells and back into the gut lumen. Age-associated alterations in CYP3A and P-glycoprotein expression and/or activity, along with liver mass and body composition changes, would be expected to affect the pharmacokinetics of tacrolimus in the elderly. However, interindividual variation in these processes may mask any changes caused by aging. More investigation is needed into the impact aging has on CYP and P-glycoprotein activity and expression. No single-dose, intense blood-sampling study has specifically compared the pharmacokinetics of tacrolimus across different patient age groups. However, five population pharmacokinetic studies, one in kidney, one in bone marrow and three in liver transplant recipients, have investigated age as a co-variate. None found a significant influence for age on tacrolimus bioavailability, volume of distribution or clearance. The number of elderly patients included in each study, however, was not documented and may have been only small. It is likely that inter- and intraindividual pharmacokinetic variability associated with tacrolimus increase in elderly populations. In addition to pharmacokinetic differences, donor organ viability, multiple co-morbidity, polypharmacy and immunological changes need to be considered when using tacrolimus in the elderly. Aging is associated with decreased immunoresponsiveness, a slower body repair process and increased drug adverse effects. Elderly liver and kidney transplant recipients are more likely to develop new-onset diabetes mellitus than younger patients. Elderly transplant recipients exhibit higher mortality from infectious and cardiovascular causes than younger patients but may be less likely to develop acute rejection. Elderly kidney recipients have a higher potential for chronic allograft nephropathy, and a single rejection episode can be more devastating. There is a paucity of information on optimal tacrolimus dosage and target trough concentration in the elderly. The therapeutic window for tacrolimus concentrations may be narrower. Further integrated pharmacokinetic-pharmaco-dynamic studies of tacrolimus are required. It would appear reasonable, based on current knowledge, to commence tacrolimus at similar doses as those used in younger patients. Maintenance dose requirements over the longer term may be lower in the elderly, but the increased variability in kinetics and the variety of factors that impact on dosage suggest that patient care needs to be based around more frequent monitoring in this age group.

Some considerations on the design of population pharmacokinetic studies

The goal of this manuscript is to introduce a framework for consideration of designs for population pharmacokinetic orpharmacokinetic-pharmacodynamic studies. A standard one compartment pharmacokinetic model with first-order input and elimination is considered. A series of theoretical designs are considered that explore the influence of optimizing the allocation of sampling times, allocating patients to elementary designs, consideration of sparse sampling and unbalanced designs and also the influence of single vs. multiple dose designs. It was found that what appears to be relatively sparse sampling (less blood samples per patient than the number of fixed effects parameters to estimate) can also be highly informative. Overall, it is evident that exploring the population design space can yield many parsimonious designs that are efficient for parameter estimation and that may not otherwise have been considered without the aid of optimal design theory.

Estimation of pharmacokinetic parameters from non-compartmental variables using Microsoft Excel((R))

This study was conducted to develop a method, termed 'back analysis (BA)', for converting non-compartmental variables to compartment model dependent pharmacokinetic parameters for both one- and two-compartment models. A Microsoft Excel((R)) spreadsheet was implemented with the use of Solver((R)) and visual basic functions. The performance of the BA method in estimating pharmacokinetic parameter values was evaluated by comparing the parameter values obtained to a standard modelling software program, NONMEM, using simulated data. The results show that the BA method was reasonably precise and provided low bias in estimating fixed and random effect parameters for both one- and two-compartment models. The pharmacokinetic parameters estimated from the BA method were similar to those of NONMEM estimation.

Analysis of population pharmacokinetic data using NONMEM and WinBUGS

The aim of this report is to describe the use of WinBUGS for two datasets that arise from typical population pharmacokinetic studies. The first dataset relates to gentamicin concentration-time data that arose as part of routine clinical care of 55 neonates. The second dataset incorporated data from 96 patients receiving enoxaparin. Both datasets were originally analyzed by using NONMEM. In the first instance, although NONMEM provided reasonable estimates of the fixed effects parameters it was unable to provide satisfactory estimates of the between-subject variance. In the second instance, the use of NONMEM resulted in the development of a successful model, albeit with limited available information on the between-subject variability of the pharmacokinetic parameters. WinBUGS was used to develop a model for both of these datasets. Model comparison for the enoxaparin dataset was performed by using the posterior distribution of the log-likelihood and a posterior predictive check. The use of WinBUGS supported the same structural models tried in NONMEM. For the gentamicin dataset a one-compartment model with intravenous infusion was developed, and the population parameters including the full between-subject variance-covariance matrix were available. Analysis of the enoxaparin dataset supported a two compartment model as superior to the one-compartment model, based on the posterior predictive check. Again, the full between-subject variance-covariance matrix parameters were available. Fully Bayesian approaches using MCMC methods, via WinBUGS, can offer added value for analysis of population pharmacokinetic data.

Pharmacokinetic-pharmacodynamic modelling of QT interval prolongation following citalopram overdoses

Aims To develop a pharmacokinetic-pharmacodynamic model describing the time-course of QT interval prolongation after citalopram overdose and to evaluate the effect of charcoal on the relative risk of developing abnormal QT and heart-rate combinations. Methods Plasma concentrations and electrocardiograph (ECG) data from 52 patients after 62 citalopram overdose events were analysed in WinBUGS using a Bayesian approach. The reported doses ranged from 20 to 1700 mg and on 17 of the events a single dose of activated charcoal was administered. The developed pharmacokinetic-pharmacodynamic model was used for predicting the probability of having abnormal combinations of QT-RR, which was assumed to be related to an increased risk for torsade de pointes (TdP). Results The absolute QT interval was related to the observed heart rate with an estimated individual heart-rate correction factor [alpha = 0.36, between-subject coefficient of variation (CV) = 29%]. The heart-rate corrected QT interval was linearly dependent on the predicted citalopram concentration (slope = 40 ms l mg(-1), between-subject CV = 70%) in a hypothetical effect-compartment (half-life of effect-delay = 1.4 h). The heart-rate corrected QT was predicted to be higher in women than in men and to increase with age. Administration of activated charcoal resulted in a pronounced reduction of the QT prolongation and was shown to reduce the risk of having abnormal combinations of QT-RR by approximately 60% for citalopram doses above 600 mg. Conclusion Citalopram caused a delayed lengthening of the QT interval. Administration of activated charcoal was shown to reduce the risk that the QT interval exceeds a previously defined threshold and therefore is expected to reduce the risk of TdP.

Relationships of tacrolimus pharmacokinetic measures and adverse outcomes in stable adult liver transplant recipients

Alternative measures to trough concentrations [non-trough concentrations and limited area under the concentration-time curve (AUC)] have been shown to better predict tacrolimus AUC. The aim of this study was to determine if these are also better predictors of adverse outcomes in long term liver transplant recipients. The associations between tacrolimus trough concentrations (C-0), non-trough concentrations (C-1, C-2, C-4, C-6/8), and AUC(0-12) and the occurrence of hypertension, hyperkalaemia, hyperglycaemia and nephrotoxicity were assessed in 34 clinically stable liver transplant patients. The most common adverse outcome was hypertension, prevalence of 36%. Hyperkalaemia and hyperglycaemia had a prevalence of 21% and 13%, respectively. A sequential population pharmacokinetic/pharmacodynamic approach was implemented. No significant association between predicted C-0, C-1, C-2, C-4, C-6/8 or AUC(0-12) and adverse effects could be found. Tacrolimus concentrations and AUC measures were in the same range in patients with and without adverse effects. Measures reported to provide benefit, preventing graft rejection and minimizing acute adverse effects in the early post-transplant period, were not able to predict adverse effects in stable adult liver recipients whose trough concentrations were maintained in the notional target range.

Synthesis, biological activity, and preliminary pharmacokinetic evaluation of analogues of a phosphosulfomannan angiogenesis inhibitor (PI-88)

The phosphosulfomannan 1 (PI-88) is a mixture of highly sulfated oligosaccharides that is currently undergoing clinical evaluation in cancer patients. As well as it's anticancer properties, 1 displays a number of other interesting biological activities. A series of analogues of 1 were synthesized with a single carbon (pentasaccharide) backbone to facilitate structural characterization and interpretation of biological results. In a fashion similar to 1, all compounds were able to inhibit heparanase and to bind tightly to the proangiogenic growth factors FGF-1, FGF-2, and VEGF. The compounds also inhibited the infection of cells and cell-to-cell spread of herpes simplex virus (HSV-1). Preliminary pharmacokinetic data indicated that the compounds displayed different pharmacokinetic behavior compared with 1. Of particular note was the n-octyl derivative, which was cleared 3 times less rapidly than 1 and may provide increased systemic exposure.