Pharmacometrics Markup Language (PharmML): Opening New Perspectives for Model Exchange in Drug Development.

The lack of a common exchange format for mathematical models in pharmacometrics has been a long-standing problem. Such a format has the potential to increase productivity and analysis quality, simplify the handling of complex workflows, ensure reproducibility of research, and facilitate the reuse of existing model resources. Pharmacometrics Markup Language (PharmML), currently under development by the Drug Disease Model Resources (DDMoRe) consortium, is intended to become an exchange standard in pharmacometrics by providing means to encode models, trial designs, and modeling steps.

Overview of model-building strategies in population PK/PD analyses: 2002-2004 literature survey.

AIMS: A descriptive survey of published population pharmacokinetic and/or pharmacodynamic (PK/PD) analyses from 2002 to 2004 was conducted and an evaluation made of how model building was performed and reported. METHODS: We selected 324 articles in Pubmed using defined keywords. A data abstraction form (DAF) was then built comprising two parts: general characteristics including article identification, context of the analysis, description of clinical studies from which the data arose, and model building, including description of the processes of modelling. The papers were examined by two readers, who extracted the relevant information and transmitted it directly to a MySQL database, from which descriptive statistical analysis was performed. RESULTS: Most published papers concerned patients with severe pathology and therapeutic classes suffering from narrow therapeutic index and/or high PK/PD variability. Most of the time, modelling was performed for descriptive purposes, with rich rather than sparse data and using NONMEM software. PK and PD models were rarely complex (one or two compartments for PK; E(max) for PD models). Covariate testing was frequently performed and essentially based on the likelihood ratio test. Based on a minimal list of items that should systematically be found in a population PK-PD analysis, it was found that only 39% and 8.5% of the PK and PD analyses, respectively, published from 2002 to 2004 provided sufficient detail to support the model-building methodology. CONCLUSIONS: This survey allowed an efficient description of recent published population analyses, but also revealed deficiencies in reporting information on model building.

Estimating heterogeneity in random effects models for longitudinal data.

In this paper, we are interested in estimating parameters entering nonlinear mixed effects models using a likelihood maximization approach. As the accuracy of the likelihood approximation is likely to govern the quality of the derived estimates of both the distribution of the random effects and the fixed parameters, we propose a methodological approach based on the adaptive Gauss Hermite quadrature to better approximate the likelihood function. This work presents improvements of this quadrature that render it accurate and computationally efficient in the problem of likelihood approximation with, an application to mixture models, models which allow the description of coexistence of several different homogeneous subpopulations specifying the distribution of random effects as a mixture of Gaussian distributions. These improvements are based on a new choice of the scaling matrix followed by its optimisation. An application to a phase III clinical trial of an anticoagulant molecule is proposed and estimation results are compared to those obtained with the most frequently used method in population pharmacokinetic analysis. Moreover, in order to evaluate the accuracy of the estimations, an analysis of simulated pharmacokinetic data derived from the model and the a priori values of population parameters of the previous study are presented.

Pharmacodynamics of follicle stimulating hormone (FSH) in postmenopausal women during pulsed estrogen therapy: Evidence that FSH release and synthesis are controlled by distinct pathways.

17 beta-Estradiol (E2) exerts negative feedback effects at the hypothalamo-pituitary level on serum FSH. This study investigated the effects of repeated daily administration of intranasal E2 (S21400) on the pharmacokinetics (PK) of E2 and estrone (E1) and the pharmacodynamics (PD) of FSH and assessed the PK/PD relationship between E2 and FSH using population model-dependent analysis. Postmenopausal volunteers (n = 24) received according to a balanced cross-over design, two 28-d treatments separated by a 2-month wash-out period: 300 microg E2, either alone or combined with oral dydrogesterone (20 mg/d) during the last 14 d of one of the treatments. Absorption of E2 was rapid, with maximal plasma concentrations at 10-30 min, returning to postmenopausal levels within 12 h. Over the 24-h period, FSH levels showed a U curve, with a minimum around 8 h after E2 administration. Moreover, over the treatment period, FSH basal values decreased by 17% between d 1 and 14 and an additional 5% between d 14 and 28. A PK/PD model described these short- and mid-term effects, possibly reflecting separate regulation mechanisms by E2 on FSH release and biosynthesis, respectively. The administration of progestin had no influence on E1, E2, and FSH model parameters. This study suggests that daily transient tissue exposure to E2 after pulsed estrogen therapy elicits short- and mid-term effects on the gonadotropin axis.

Population PKPD modelling of the long-term hypoglycaemic effect of gliclazide given as a once-a-day modified release (MR) formulation.

AIMS: To study the relationship between the pharmacokinetics (PK) of gliclazide and its long-term pharmacodynamic (PD) effect in a large population of Type 2 diabetic patients and to identify factors predicting intersubject variability. METHODS: A PKPD database of 634 Type 2 diabetic patients with a total of 5,258 fasting plasma glucose (FPG) samples was built up from the data collected during the clinical development of a modified release formulation of gliclazide (gliclazide MR). The PKPD analysis used a nonlinear mixed effect modelling approach. A mixture model was used to identify patients with a FPG response to treatment. In patients identified as responders, the decrease in FPG was related to gliclazide exposure (AUC) by an Emax relationship. An effect compartment was used to describe the link between PK and PD. A linear disease-progression model was used to assess the glycaemic deterioration observable over several months of treatment. Simulations were performed to evaluate the predictive performance of the PKPD model and to illustrate the time course of the antidiabetic effect of gliclazide MR. RESULTS: Disease state was found to be the main explanatory factor for intersubject variability in response to gliclazide. The percentage of responders to gliclazide, used as monotherapy, increased inversely to the number of classes of antidiabetic agents received prior to entry in the studies. In responders, the initial dose (30 mg) of the gliclazide MR dosing regimen induced half of the maximum hypoglycaemic effect. The equilibration half-life between the PK and PD steady states was 3 weeks (intersubject variability of 84%). The rate of disease progression was 0.84 mmol l(-1) year(-1) (intersubject variability 143%). The PKPD model adequately predicted the FPG profiles of 234 patients who received the current formulation of gliclazide. Simulation of a 1-year parallel dose ranging clinical trial illustrated the influence of dose, time and type of previous antidiabetic treatment on the percentage of patients with clinically significant improvement of blood glucose control. CONCLUSIONS: This population PKPD analysis has characterized the relationship between the exposure to gliclazide and its long-term hypoglycaemic effect, and has established that the intersubject variability in response is mostly related to disease state. These results underline the clinical interest of quickly increasing the dose of gliclazide MR according to the response to treatment in order to achieve effective blood glucose control.

A pharmacokinetic simulation model for ivabradine in healthy volunteers.

Ivabradine is a novel bradycardic agent that has been developed for the prevention of angina. Ivabradine has an active metabolite S-18982. The aim of this study is to develop a pharmacokinetic simulation model. Pharmacokinetic data from two studies were pooled and included data from a total of 66 healthy male volunteers. The data were collected following single dose intravenous and multiple dose oral administration of ivabradine. The multiple dose regimens were administered every 12 h and there were seven active dosing levels. The modelling was performed using the NONMEM software. The model was assessed in terms of its ability to describe the original data set used in its construction and also data arising from a different clinical pharmacology study involving 12 additional subjects. The pharmacokinetics of ivabradine and S-18982 were best described by two linked two compartment intravenous bolus and first-order input, with first-pass loss, and first-order output model. When the model was used for simulation it produced an adequate description of both the original data and data arising from a different clinical pharmacology study.

Use of nonlinear mixed effect modeling for the meta-analysis of preclinical pharmacokinetic data: application to S 20342 in the rat.

The standard two-stage analysis of separate preclinical pharmacokinetic (PK) and toxicokinetic (TK) studies may lead to good information on the bioavailability in the rat at a low (pharmacologic) dose but only an idea on the dose/exposure relationship, on gender, and on time effect. In view of these drawbacks, we decided therefore to explore the usefulness of the implementation of a meta-analysis in preclinical studies in a given species (the rat in this case) taking as an example S 20342, an investigational new drug with potential antipsychotic properties. A nonlinear mixed-effect PK model was built from all intravenous (IV) and oral (PO) data collected until the completion of the 4-week toxicity study. The database included data from 201 Wistar rats (161 males and 40 females). Forty animals received the drug IV and 161 PO. The treatment duration ranged from 1 day to 4 weeks. IV doses were 3, 5, and 20 mg/kg, and 11 different oral doses were tested in the range of 5 to 200 mg/kg. Three different salts were administered PO: hydrochloride, sulfate, and mesylate. The modeling was performed with NONMEM IV. The best pharmacokinetic model was a two-compartment model with simultaneous first-order and zero-order absorption. The combination of these two input functions allowed the model to fit the peak plasma concentrations observed in the first hour (first order), especially after oral administration of low doses, and to take into account the prolonged absorption phase when the dose increased (zero order). A significant gender effect was found on CL. In addition, significant positive correlations were found between weight and CL, weight and Vc, and dose and the dose fraction after a zero-order absorption. No covariate significantly influenced the other parameters. In conclusion, the meta-analysis of preclinical data allowed for an objective assessment of statistically significant effects throughout the model-building process, leading to a better knowledge (and thus a better understanding) of preclinical PK in the rat. Moreover, the model obtained could be used to interpret further preclinical specific studies involving a sparse sampling design (e.g., further TK studies and PK/PD studies). Although this meta-analysis is more complicated than the noncompartmental approach and requires a case-by-case effort, it could be very useful to integrate this approach in the preclinical development process.

Pharmacokinetic-pharmacodynamic modeling of the effects of ivabradine, a direct sinus node inhibitor, on heart rate in healthy volunteers.

OBJECTIVE: Ivabradine (S-16257) is a new bradycardic agent with a direct effect on the sinus node. Its N-dealkylated metabolite, S-18982, has shown a bradycardic activity in animals. The aim of this trial was to study the correlation between drug bradycardic activity and plasma levels of the parent compound and its metabolite in healthy volunteers. METHODS: Eighteen healthy volunteers participated in three successive study periods: an oral double-blind period with two parallel groups of doses (10 or 20 mg, single and repeated); a 10 mg intravenous bolus open period; and a final control period. The effects of ivabradine on heart rate were studied at rest and during bicycle exercise tests (at 85% of maximum workload) during 24-hour postdosing, and ivabradine and S-18982 plasma levels were determined simultaneously. RESULTS: The maximal reductions of exercise heart rate were 11% +/- 4% (10 mg) and 18% +/- 6% (20 mg) after single oral doses (p < 0.05) and 18% +/- 4% (10 mg) and 27% +/- 6% (20 mg) after repeated doses (p < 0.01). Maximum heart rate reduction after the intravenous bolus was 19% +/- 4%. After oral administrations an indirect relationship between the bradycardic effect and the plasma concentrations of the two compounds was found. A pharmacokinetic/pharmacodynamic population analysis done with the NONMEM computer program showed that S-18982 contributes in part to the overall activity of ivabradine: modeling suggested that the metabolite is responsible for the initial bradycardic effect, whereas the parent compound is responsible for the duration of action. CONCLUSION: This study shows that ivabradine exerts a dose-dependent bradycardic effect and that its N-dealkylated metabolite contributes to this bradycardic effect.

Application of population pharmacokinetics to the phase II development of an anti-Alzheimer's disease compound, S12024.

Steady-state concentrations of S12024, a novel compound for treatment of Alzheimer's disease, were studied to determine the pharmacokinetic parameters of S12024 in Phase IIa patients and to assess the effect of patient characteristics on those pharmacokinetics. A prospective sparse sampling strategy was used to obtain oral repeated data (n = 285) from 89 patients, which were analyzed using a one-compartment model and the NONMEM computer program. The model suggested that apparent clearance of S12024 was influenced by the study and by patient age. In the Spanish study, apparent clearance was increased by 68% and 26% for doses of 100 mg and 300 mg, respectively, and patient age decreased oral clearance by approximately 10% per decade in the patient age range (50 to 90 years). Data from only a few patients in the Spanish study were probably responsible for the observed study influence on apparent clearance of S12024, and no measured covariates could explain this effect. The model provided an excellent characterization of the observed data and it predicted correctly the plasma concentrations from an earlier Phase I trial and a subsequent Phase IIb study. The present model, built from Phase IIa data, provides a basis for examining the influence of patient covariates and the magnitude of their effects on the pharmacokinetics of S12024. The study effect is probably an artefact that will disappear by further expanding of the population model in the future.