Simultaneous versus sequential optimal design for pharmacokinetic-pharmacodynamic models with FO and FOCE considerations

We consider nested multiple response models which are used extensively in the area of pharmacometrics. Given the conditional nature of such models, differences in predicted responses are a consequence of different assumptions about how the models interact. As such, sequential versus simultaneous and First Order (FO) versus First Order Conditional Estimation (FOCE) techniques have been explored in the literature where it was found that the sequential and FO approaches can produce biased results. It is therefore of interest to determine any design consequences between the various methods and approximations. As optimal design for nonlinear mixed effects models is dependent upon initial parameter estimates and an approximation to the expected Fisher information matrix, it is necessary to incorporate any influence of nonlinearity (or parameter-effects curvature) into our exploration. Hence, sequential versus simultaneous design with FO and FOCE considerations are compared under low, typical and high degrees of nonlinearity. Additionally, predicted standard errors of parameters are also compared to empirical estimates formed via a simulation/estimation study in NONMEM. Initially, design theory for nested multiple response models is developed and approaches mentioned above are investigated by considering a pharmacokinetic–pharmacodynamic model found in the literature. We consider design for situations where all responses are continuous and extend this methodology to the case where a response may be a discrete random variable. In particular, for a binary response pharmacodynamic model, it is conjectured that such responses will offer little information about all parameters and hence a sequential optimization, in the form of product design optimality, may yield near optimal designs.     

Erratum: Optimal Design of a Population Pharmacodynamic Experiment for Ivabradine

Pharmaceutical Research -     

Evaluation of Approaches to Deal with Low-Frequency Nuisance Covariates in Population Pharmacokinetic Analyses

Clinical studies include occurrences of rare variables, like genotypes, which due to their frequency and strength render their effects difficult to estimate from a dataset. Variables that influence the estimated value of a model-based parameter are termed covariates. It is often difficult to determine if such an effect is significant, since type I error can be inflated when the covariate is rare. Their presence may have either an insubstantial effect on the parameters of interest, hence are ignorable, or conversely they may be influential and therefore non-ignorable. In the case that these covariate effects cannot be estimated due to power and are non-ignorable, then these are considered nuisance, in that they have to be considered but due to type 1 error are of limited interest. This study assesses methods of handling nuisance covariate effects. The specific objectives include (1) calibrating the frequency of a covariate that is associated with type 1 error inflation, (2) calibrating its strength that renders it non-ignorable and (3) evaluating methods for handling these non-ignorable covariates in a nonlinear mixed effects model setting. Type 1 error was determined for the Wald test. Methods considered for handling the nuisance covariate effects were case deletion, Box-Cox transformation and inclusion of a specific fixed effects parameter. Non-ignorable nuisance covariates were found to be effectively handled through addition of a fixed effect parameter.KEY WORDS: Box-Cox transformation, case deletion and pharmacometrics, fixed effect parameter, nuisance covariate     

The pharmacokinetics of sertraline in overdose and the effect of activated charcoal

Aims

To investigate the pharmacokinetics (PK) of sertraline in overdose and the effect of single dose activated charcoal (SDAC).

Methods

Patients presenting to a toxicology unit with sertraline overdoses had demographic and clinical information recorded, and serial serum collected for measurement of sertraline concentrations. Monolix® version 4.2 was used to develop a population PK model of sertraline overdose and the effect of SDAC. Uncertainty in dose time was accounted for by shifting dose time using lag time with between subject variability (BSV). BSV on relative fraction absorbed was used to model uncertainty in dose.

Results

There were 77 timed sertraline concentrations measured in 28 patients with sertraline overdoses with a median dose of 1550 mg (250–5000 mg). SDAC was given to seven patients between 1.5 and 4 h post-overdose. A one compartment model with lag time of 1 h and first order input and elimination adequately described the data. Including BSV on both lag time and relative fraction absorbed improved the model. The population PK parameter estimates for absorption rate constant, volume of distribution and clearance were 0.895 h⁻¹, 5340 l and 130 l h⁻¹, respectively. The calculated half-life of sertraline following overdose was 28 h (IQR 19.4−30.6h). When given up to 4 h post-overdose, SDAC significantly increased the clearance of sertraline by a factor of 1.9, decreased the area under the curve and decreased the maximum plasma concentration (C_max).

Conclusions

Sertraline had linear kinetics in overdose with parameter values similar to those in therapeutic use. SDAC is effective in increasing clearance when given 1.5 to 4 h post-overdose.     

Population pharmacokinetics of mycophenolic acid during the first week after renal transplantation

Objective To investigate the population pharmacokinetics of mycophenolic acid (MPA) in adult kidney transplant recipients during the crucial first week after transplantation.Methods Data were collected from 117 patients. MPA plasma concentrations were determined at t=0, 1, 2, 3 and 4 h after mycophenolate mofetil dosing on days 3, 5 and 7. Population analysis was performed using NONMEM. Covariates screened were sex, age, body weight, serum creatinine, creatinine clearance, serum albumin, days of therapy, diabetes mellitus, organ source (live or cadaveric) and co-therapy (tacrolimus or cyclosporine). Final model validity was evaluated using 200 bootstrapped samples from the original data. Bias and precision were determined through comparison of observed and predicted concentrations.Results Individual concentration–time profiles showed evidence of an absorption lag time and enterohepatic recirculation of MPA in some patients on some occasions. The best base model had bi-exponential elimination with a typical population (SE%) apparent clearance (CL/F) of 29 l/h (5%) and apparent volume of the central compartment of 65 l (7%). CL/F decreased significantly with increasing serum albumin (1.42 l/h reduction in total plasma CL/F with each 1 g/l increase in albumin) and was 27% greater in patients receiving cyclosporine than in those receiving tacrolimus. Evaluation of the final model showed close agreement between pairs of bootstrapped and final model parameter estimates (all differences <7%). Predictions were non-biased (0.11 mg/l) but imprecise (2.8 mg/l).Conclusion Population pharmacokinetic parameters for MPA were determined. These can be used to achieve specific target MPA concentrations or areas under the concentration–time curve.     

Free mycophenolic acid should be monitored in renal transplant recipients with hypoalbuminemia

The current approach for therapeutic drug monitoring in renal transplant recipients receiving mycophenolate mofetil (MMF) is measurement of total mycophenolic acid (MPA) concentration. Because MPA is highly bound, during hypoalbuminemia the total concentration no longer reflects the free (pharmacologically active) concentration. The authors investigated what degree of hypoalbuminemia causes a significant change in protein binding and thus percentage free MPA. Forty-two renal transplant recipients were recruited for the study. Free and total concentrations of MPA (predose, and 1, 3, and 6 hours post-MMF dose samples) and plasma albumin concentrations were determined on day 5 posttransplantation. Six-hour area under the concentration-time curve (AUC(0-6)) values were calculated for free and total MPA, and percentage free MPA was determined for each patient. The authors found a significant relationship between low albumin concentrations and increased percentage free MPA (Spearman correlation = -0.54, P < 0.0001). Receiver operating characteristic (ROC) curve analysis was performed on the albumin versus percentage free MPA data. The cutoff value of albumin determined from the ROC analysis that differentiated normal from elevated percentage free MPA (defined as > or = 3%) in this patient population was 31 g/L. At this cutoff value albumin was found to be a good predictor of altered free MPA percentage, with a sensitivity and specificity of 0.75 and 0.80, respectively, and an area under the ROC curve of 0.79. To rationalize MMF dosing regimens in hypoalbuminemic patients (plasma albumin < or = 31 g/L), clinicians should consider monitoring the free MPA concentration.     

The effect of body weight on dalteparin pharmacokinetics A preliminary study

Aim: To investigate whether there were significant differences in the volume of distribution (V) and clearance (CL) of dalteparin in obese versus normal-weight patients, and thereby determine whether dosing of dalteparin should be based on total body weight, lean body weight or an adjusted body weight in obese patients. Methods: Patients (ten obese and ten normal weight) treated with dalteparin were matched for age, gender, lean body weight and creatinine CL. Two steady-state plasma dalteparin concentrations were taken from each patient and assayed in duplicate. The pharmacokinetic values of V and CL were estimated, for each patient, using the Bayesian maximum a posteriori method with the program ABBOTTBASE. Results: The mean V in obese patients was approximately 60% larger than in normal-weight patients, but this was not statistically significant (P=0.11; two-tailed). The mean value of V (8.4 l) in the normal-weight patients was similar to that reported in the literature. The mean difference in values of CL (18% larger in obese patients) was not clinically or statistically significant. A poor correlation was seen between V and lean body weight (r ²=0.05). There was a moderate correlation between V and total body weight (r ²=0.52) and between V and adjusted body weight (r ²=0.55); adjusted body weight=[lean body weight + 0.4(total body weight – lean body weight)]. Total body weight and adjusted body weight provided a better correlation with CL (r ²=0.39, 0.32, respectively) than did lean body weight (r ²=0.01). Conclusion: These results suggest that doses of dalteparin in obese patients should be based on total body weight or an adjusted body weight, but not lean body weight. This study highlights some potential differences in the pharmacokinetics of dalteparin in individuals who are obese, and further work is necessary to quantify these differences in more detail. Received: 30 July 1999 / Accepted in revised form: 16 March 2000     

A model for venom-induced consumptive coagulopathy in snake bite

Many snake venoms contain procoagulant toxins that activate the coagulation cascade and cause venom-induced consumptive coagulopathy (VICC). We developed a semi-mechanistic model of the clotting cascade in order to explore the effects of the procoagulant toxin from taipan venom on this system as well as the effects of antivenom. Simulations of the time course in the change of clotting factors were compared to data collected from taipan envenomed patients. The model accurately predicted the observed concentration of clotting factors over time following taipan envenomation. Investigations from the model indicated that the upper limit of the half-life of the procoagulant toxin was 1h. Simulations from the model also suggest that antivenom for Australasian elapids has negligible effect on reducing the recovery time of the coagulation profile unless administered almost immediately after envenomation. The model has generality to be expanded to describe the effects of other venoms and drugs on the clotting cascade.