Optimal Blood Sampling Time Windows for Parameter Estimation Using a Population Approach: Design of a Phase II Clinical Trial

Optimal sparse sampling for estimating ganciclovir/valganciclovir AUC in solid organ transplant patients using NONMEN

BACKGROUND

Ganciclovir and valganciclovir (GCV/VGCV) are used for the treatment and prophylaxis of cytomegalovirus in solid organ transplant (SOT) patients. An area under the time-concentration curve of 40-50 μg × h/mL is related to efficacy. Therapeutic drug monitoring could prevent suboptimal drug exposure and adverse events, but obtaining full concentration profiles is not feasible. Sampling optimization by developing a reliable and clinically applicable limited sampling strategy (LSS) may simplify dose adjustment.

METHODS

An LSS was developed using an original pharmacokinetic (PK) data set of 40 full profiles from 20 adult SOT patients. The LSS was developed based on population and Bayesian prediction approaches. Population PK parameters from a previous model were used for simulation or as priors (NONMEM version 7.2). Median percentage of prediction error and median of absolute percentage prediction error were calculated for plasma clearance (CL) and central compartment distribution volume (V(2)). Bias and precisions were compared using 1-way analysis of variance (SPSSv19.0).

RESULTS

Sampling windows were designed according to the PK profile previously observed with the entire set of data. The 4 windows selected were distributed from 0.5 to 1.5 hours, 2 to 3 hours, 4 to 5 hours, and 6 to 8 hours. Predose and concentrations beyond 8 hours were not considered in any case because simulated negative concentrations occurred in both cases. Predicted exposure using 3 sampling times (0.5-1.5, 4-5, and 6-8 hours) showed the best predictive performance, by either the population or Bayesian approaches. Bias and imprecision for CL and V(2) were 0 and 0.60%, and -0.78% and 0.78%, respectively.

CONCLUSIONS

GCV/VCG area under the time-concentration curve in SOT patients could be predicted with acceptable accuracy for clinical management and dose individualization using LSS. The estimator of GCV/VGC, using 3 concentrations measured at 0.5-1.5, 4-5, and 6-8 hours after drug intake, could be used for dose adjustment.

A simultaneous d-optimal designed study for population pharmacokinetic analyses of mycophenolic Acid and tacrolimus early after renal transplantation

Mycophenolic acid (MPA) and tacrolimus (TAC) are immunosuppressive agents used in combination with corticosteroids for the prevention of acute rejection after solid organ transplantation. Their pharmacokinetics (PK) show considerable unexplained intraindividual and interindividual variability, particularly in the early period after transplantation. The main objective of the present work was to design a study based on D-optimality to describe the PK of the 2 drugs with good precision and accuracy and to explain their variability by means of patients' demographics, biochemical test results, and physiological characteristics. Pharmacokinetic profiles of MPA and TAC were obtained from 65 stable adult renal allograft recipients on a single occasion (ie, day 15 after transplantation). A sampling schedule was estimated based on the D-optimality criterion with the POPED software, using parameter values from previously published studies on MPA and TAC modeling early after transplantation. Subsequently, a population PK model describing MPA and TAC concentrations was developed using nonlinear mixed-effects modeling. Optimal blood-sampling times for determination of MPA and TAC concentrations were estimated to be at 0 (predose) and at 0.24, 0.64, 0.98, 1.37, 2.38, and 11 hours after oral intake of mycophenolate and TAC. The PK of MPA and TAC were best described by a 2-compartment model with first-order elimination. For MPA, the absorption was best described by a transit compartment model, whereas first-order absorption with a lag time best described TAC transfer from the gastrointestinal tract. Parameters were estimated with good precision and accuracy. While hematocrit levels and CYP3A5 genetic polymorphism significantly influenced TAC clearance, the pharmaceutical formulation and MRP2 genetic polymorphism were retained as significant covariates on MPA absorption and elimination, respectively. The prospective use of the simultaneous D-optimal design approach for MPA and TAC has allowed good estimation of MPA and TAC PK parameters in the early period after transplantation characterized by a very high unexplained variability. The influence of some relevant covariates could be shown.

Designing simple PK-PD studies in children

Conducting clinical pharmacology research studies in pediatric patients is challenging because of ethical and practical constraints but necessary to ensure that drugs are used safely and effectively in this population. Developments in laboratory analytical techniques, such as improved assay sensitivity and the use of alternative sample matrices, can reduce blood loss and offer less invasive blood sampling, causing less trauma to the patient and fewer ethical concerns. Recent advances in data analysis techniques, which aim to extract the maximum amount of useful information from small sample numbers, should be considered when planning a clinical trial and incorporated into the study design. Using 'population' methodology allows a more flexible sampling strategy that enables valuable data to be collected in the course of routine clinical practice, rather than in a rigid, and potentially artificial, setting. Integration of pharmacokinetics and pharmacodynamics and the application of physiological approaches and simulation techniques to the analysis and interpretation of drug concentration and effect data offer new opportunities that have particular relevance to pharmacological research in the field of pediatric anesthetics.

Application of optimal design methodologies in clinical pharmacology experiments

Pharmacokinetics and pharmacodynamics data are often analysed by mixed-effects modelling techniques (also known as population analysis), which has become a standard tool in the pharmaceutical industries for drug development. The last 10 years has witnessed considerable interest in the application of experimental design theories to population pharmacokinetic and pharmacodynamic experiments. Design of population pharmacokinetic experiments involves selection and a careful balance of a number of design factors. Optimal design theory uses prior information about the model and parameter estimates to optimize a function of the Fisher information matrix to obtain the best combination of the design factors. This paper provides a review of the different approaches that have been described in the literature for optimal design of population pharmacokinetic and pharmacodynamic experiments. It describes options that are available and highlights some of the issues that could be of concern as regards practical application. It also discusses areas of application of optimal design theories in clinical pharmacology experiments. It is expected that as the awareness about the benefits of this approach increases, more people will embrace it and ultimately will lead to more efficient population pharmacokinetic and pharmacodynamic experiments and can also help to reduce both cost and time during drug development.

A d-optimal designed population pharmacokinetic study of oral itraconazole in adult cystic fibrosis patients

AIM

The primary objective of the study was to estimate the population pharmacokinetic parameters for itraconazole and hydroxy-itraconazole, in particular, the relative oral bioavailability of the capsule compared with solution in adult cystic fibrosis patients, in order to develop new dosing guidelines. A secondary objective was to evaluate the performance of a population optimal design.

METHODS

The blood sampling times for the population study were optimized previously using POPT v.2.0. The design was based on the administration of solution and capsules to 30 patients in a cross-over study. Prior information suggested that itraconazole is generally well described by a two-compartment disposition model with either linear or saturable elimination. The pharmacokinetics of itraconazole and the metabolite were modelled simultaneously using NONMEM. Dosing schedules were simulated to assess their ability to achieve a trough target concentration of 0.5 mg ml(-1).

RESULTS

Out of 241 blood samples, 94% were taken within the defined optimal sampling windows. A two-compartment model with first order absorption and elimination best described itraconazole kinetics, with first order metabolism to the hydroxy-metabolite. For itraconazole the absorption rate constants (between-subject variability) for capsule and solution were 0.0315 h(-1) (91.9%) and 0.125 h(-1) (106.3%), respectively, and the relative bioavailability of the capsule was 0.82 (62.3%) (confidence interval 0.36, 1.97), compared with the solution. There was no evidence of nonlinearity. Simulations from the final model showed that a dosing schedule of 500 mg twice daily for both formulations provided the highest chance of target success.

CONCLUSION

The optimal design performed well and the pharmacokinetics of itraconazole and hydroxy-itraconazole were described adequately by the model. The relative bioavailability for itraconazole capsules was 82% compared with the solution.