Population pharmacokinetics. A regulatory perspective

Predictive performance for population models using stochastic differential equations applied on data from an oral glucose tolerance test

Several articles have investigated stochastic differential equations (SDEs) in PK/PD models, but few have quantitatively investigated the benefits to predictive performance of models based on real data. Estimation of first phase insulin secretion which reflects beta-cell function using models of the OGTT is a difficult problem in need of further investigation. The present work aimed at investigating the power of SDEs to predict the first phase insulin secretion (AIR (0-8)) in the IVGTT based on parameters obtained from the minimal model of the OGTT, published by Breda et al. (Diabetes 50(1):150-158, 2001). In total 174 subjects underwent both an OGTT and a tolbutamide modified IVGTT. Estimation of parameters in the oral minimal model (OMM) was performed using the FOCE-method in NONMEM VI on insulin and C-peptide measurements. The suggested SDE models were based on a continuous AR(1) process, i.e. the Ornstein-Uhlenbeck process, and the extended Kalman filter was implemented in order to estimate the parameters of the models. Inclusion of the Ornstein-Uhlenbeck (OU) process caused improved description of the variation in the data as measured by the autocorrelation function (ACF) of one-step prediction errors. A main result was that application of SDE models improved the correlation between the individual first phase indexes obtained from OGTT and AIR (0-8) (r = 0.36 to r = 0.49 and r = 0.32 to r = 0.47 with C-peptide and insulin measurements, respectively). In addition to the increased correlation also the properties of the indexes obtained using the SDE models more correctly assessed the properties of the first phase indexes obtained from the IVGTT. In general it is concluded that the presented SDE approach not only caused autocorrelation of errors to decrease but also improved estimation of clinical measures obtained from the glucose tolerance tests. Since, the estimation time of extended models was not heavily increased compared to basic models, the applied method is concluded to have high relevance not only in theory but also in practice.

Population pharmacokinetics of docetaxel in patients with hepatic dysfunction treated in an oncology practice

To investigate the relationship between the degree of liver dysfunction and the pharmacokinetics of docetaxel, a population pharmacokinetic model was developed in an oncology practice without excluding patients with moderate to severe liver dysfunction. Two hundred patients were treated with docetaxel as a single agent or in combination chemotherapy. The plasma concentration-time course data were analyzed using a three-compartment open model with zero-order administration and first-order elimination on the NONMEM program. Sixty-one had elevated transaminase levels, and alkaline phosphatase was elevated in 40. Body surface area, albumin, alpha1-acid glycoprotein, and liver function were found to be significant covariates for the systemic clearance of docetaxel. Compared to patients with normal or minimal impairment of liver function, patients with grade 2 and 3 elevations of transaminases at baseline in conjunction with elevation of alkaline phosphatase had 22 and 38% lower clearances, respectively. Goodness-of-fit plots indicated that the model was fitted well with the observed data, and the bootstrap method guaranteed robustness of the model. We developed a population pharmacokinetic model for docetaxel, which can be used in the setting of an oncology practice. Based on the model, dose reduction by approximately 20 and 40% should be considered for patients with grade 2 and 3 elevations of transaminases at baseline in conjunction with elevation of alkaline phosphatase, respectively.

Integrated pharmacokinetics and pharmacodynamics in drug development

Drug development is a complex, lengthy and expensive process. Pharmaceutical companies and regulatory authorities have recognised that the drug development process needs optimisation for efficiency in view of the return on investments. Pharmacokinetics and pharmacodynamics are the two main principles determining the relationship between dose and response. This article provides an update on integrated approaches towards drug development by linking pharmacokinetics, pharmacodynamics and disease aspects into mathematical models. Gradually, a transition is taking place from a rather empirical approach towards a modelling- and simulation-based approach to drug development. The main learning phases should be phases 0, I and II, whereas phase III studies should merely have a confirmatory purpose. In model-based drug development, mechanism-based mathematical models, which are iteratively refined along the path of development, incorporate the accumulating knowledge of the investigational drug, the disease and their mutual interference in different subsets of the target population. These models facilitate the design of the next study and improve the probability of achieving the projected efficacy and safety endpoints. In this article, several theoretical and practical aspects of an integrated approach towards drug development are discussed, together with some case studies from different therapeutic areas illustrating the application of pharmacokinetic/pharmacodynamic disease models at different stages of drug development.

Assessment of the validity of a population pharmacokinetic model for epirubicin

AIMS

The aim of this study was to evaluate a population model for epirubicin clearance using internal and external validation techniques.

METHODS

Jackknife samples were used to identify outliers in the population dataset and individuals influencing covariate selection. Sensitivity analyses were performed in which serum aspartate transaminase (AST) values (a covariate in the population model) or epirubicin concentrations were randomly changed by +/-10%. Cross-validation was performed five times, on each occasion using 80% of the data for model development and 20% to assess the performance of the model. External validation was conducted by assessing the ability of the population model to predict concentrations and clearances in a separate group of 79 patients.

RESULTS

Structural parameter estimates from all jackknife samples were within 7.5% of the final population estimates and examination of log likelihood values indicated that the selection of AST in the final model was not due to the presence of outliers. Alteration of AST or epirubicin concentrations by +/-10% had a negligible effect on population parameter estimates and their precision. In the cross-validation analysis, the precision of clearance estimates was better in patients with AST concentrations>150 U l-1. In the external validation, epirubicin concentrations were over-predicted by 81.4% using the population model and clearance values were also poorly predicted (imprecision 43%).

CONCLUSIONS

The results of internal validation of population pharmacokinetic models should be interpreted with caution, especially when the dataset is relatively small.

A semimechanistic-physiologic population pharmacokinetic/pharmacodynamic model for neutropenia following pemetrexed therapy

PURPOSE

The objectives of these analyses were to (1) develop a semimechanistic-physiologic population pharmacokinetic/pharmacodynamic (PK/PD) model to describe neutropenic response to pemetrexed and to (2) identify influential covariates with respect to pharmacodynamic response.

PATIENTS AND METHODS

Data from 279 patients who received 1,136 treatment cycles without folic acid or vitamin B12 supplementation during participation in one of eight phase II cancer trials were available for analysis. Starting doses were 500 or 600 mg pemetrexed per m2 body surface area (BSA), administered as 10-min intravenous infusions every 21 days (1 cycle). The primary analyses included 105 patients (279 cycles) for which selected covariates-including vitamin deficiency marker data (i.e., homocysteine, cystathionine, methylmalonic acid, and methylcitrate [I, II, and total] plasma concentrations)-were available. Classical statistical multivariate regression analyses and a semimechanistic-physiologic population PK/PD model were used to evaluate neutropenic response to single-agent pemetrexed administration.

RESULTS

The timecourse of neutropenia following single-agent pemetrexed administration was adequately described by a semimechanistic-physiologic model. Population estimates for system-based model parameters (i.e., baseline neutrophil count, mean transit time, and the feedback parameter), which mathematically represent current understanding of the process and physiology of hematopoiesis, were consistent with previously reported values. The population PK/PD model included homocysteine, cystathionine, albumin, total protein, and BSA as covariates relative to neutropenic response.

CONCLUSION

These results support the programmatic decision to introduce folic acid and vitamin B12 supplementation during pemetrexed clinical development as a means of normalizing patient homocysteine levels, thereby managing the risk of severe neutropenia secondary to pemetrexed administration. The current results also suggest that the addition of vitamin B6 supplementation to normalize patient cystathionine levels may further decrease the incidence of grade 4 neutropenia following pemetrexed administration. The results also suggest the use of folic acid as a means of lessening hematologic toxicity following administration of cytotoxic agents other than antifolates.

Population pharmacokinetic analysis of ten phase II clinical trials of pemetrexed in cancer patients

PURPOSE

The objectives of these population pharmacokinetic analyses were to (1) assess the overall disposition of pemetrexed, (2) characterize between-patient and within-patient variability and identify influential covariates with respect to pemetrexed pharmacokinetics; and, (3) provide individual empirical Bayesian estimates of pharmacokinetic parameters for use in a subsequent pharmacokinetic/pharmacodynamic evaluation of neutropenia following pemetrexed administration.

PATIENTS AND METHODS

Data from 287 patients who received 441 cycles without folic acid or vitamin B12 supplementation during participation in one of ten phase II cancer trials were evaluated by population pharmacokinetic analysis using NONMEM. Starting doses were 500 or 600 mg pemetrexed per m2 body surface area, administered as 10-min intravenous infusions every 21 days (1 cycle). The model was developed using data from eight of the ten studies. Predictive performance was evaluated using data from the other two studies.

RESULTS

The population pharmacokinetics of pemetrexed administered as a 10-min intravenous infusion are well characterized by a two-compartment model. Typical values of total systemic clearance, central volume of distribution, distributional clearance, and peripheral volume of distribution were 91.6 ml/min, 12.9 l, 14.4 ml/min, and 3.38 l, respectively. Based on these parameter estimates, the terminal elimination half-life of pemetrexed was approximately 3.5 h. Renal function was identified as a covariate with respect to total systemic clearance, and body surface area as a covariate with respect to the central volume of distribution.

CONCLUSION

Total systemic exposure (AUC) for a given dose of pemetrexed increases as renal function decreases. Since pharmacodynamic analyses have shown that AUC and not C (max) is the primary determinant of neutropenic response to pemetrexed, this suggests that dose adjustments based on renal function, rather than body surface area, might be considered for pemetrexed.

Population pharmacokinetics III: design, analysis, and application of population pharmacokinetic Studies

OBJECTIVE

To present a framework within which population pharmacokinetic (PPK) studies should be designed and analyzed and discuss the application of developed PPK models.

METHODS

Information on PPK was retrieved from a MEDLINE search (1979-December 2003) of the literature and a bibliographic evaluation of review articles and books. This information is used in conjunction with experience to explain the design and analysis of PPK studies. Also, examples are included to demonstrate the usefulness of PPK.

SYNTHESIS

A great deal of thought must be given to the design and analysis of PPK studies (ie, development of PPK models). Models are of 2 primary types--descriptive and predictive--and the process applied to these models is necessarily different. An approach that ensures model applicability is presented.

CONCLUSIONS

PPK models have great utility, and the applications are many. They are very different from single-subject pharmacokinetic models and therefore require different approaches to model estimation.

Population pharmacokinetic model for daunorubicin and daunorubicinol coadministered with zosuquidar.3HCl (LY335979)

PURPOSE

The impact of zosuquidar.3HCl, an inhibitor of P-glycoprotein, on the pharmacokinetics of daunorubicin and daunorubicinol was examined in a phase I trial using a population approach. Pharmacokinetic and pharmacodynamic properties of zosuquidar.3HCl were also determined.

METHODS

The pharmacokinetics of daunorubicin and daunorubicinol were studied following daunorubicin administration on day 1 (50 mg/m2 i.v. infusion over 10 min) alone and on day 3 concomitantly with zosuquidar.3HCl (i.v. 200 or 300 mg/m2 over 6 h or 400 mg over 3 h). Of a total of 18 patients entered, 16 with acute leukemia completed the study.

RESULTS

A three-compartment pharmacokinetic model adequately described daunorubicin concentration-time profiles. Five- and four-compartment models adequately described the daunorubicin-daunorubicinol pharmacokinetics in the absence and presence of zosuquidar.3HCl, respectively. The impact of zosuquidar.3HCl on coadministered daunorubicin was minimal, with a 10% reduction in daunorubicin clearance. The model predicted a 50% decrease in daunorubicinol apparent clearance in the presence of zosuquidar.3HCl. A direct concentration-effect relationship between zosuquidar.3HCl concentrations and inhibition of rhodamine 123 (Rh123) efflux in CD56 lymphocytes was defined by a sigmoid E(max) model. The IC(50) was 31.7 microg/l. The zosuquidar.3HCl dosing regimen led to concentrations in excess of the IC(90) (169.6 microg/l) and provided maximal P-glycoprotein inhibition during the distribution phases of daunorubicin.

CONCLUSIONS

The decrease in daunorubicin and daunorubicinol clearance in the presence of zosuquidar.3HCl likely reflects inhibition of P-glycoprotein in the bile canaliculi impeding their biliary excretion. The results need to be interpreted carefully due to the sequential nature of daunorubicin administration and analysis.

A population pharmacokinetic model for paclitaxel in the presence of a novel P-gp modulator, Zosuquidar Trihydrochloride (LY335979)

AIMS

To develop a population pharmacokinetic model for paclitaxel in the presence of a MDR modulator, zosuquidar 3HCl.

METHODS

The population approach was used (implemented with NONMEM) to analyse paclitaxel pharmacokinetic data from 43 patients who received a 3-h intravenous infusion of paclitaxel (175 mg x m(-2) or 225 mg x m(-2)) alone in cycle 2 or concomitantly with the oral administration of zosuquidar 3HCl in cycle 1.

RESULTS

The structural pharmacokinetic model for paclitaxel, accounting for the Cremophor ELTM impact, was a three-compartment model with a nonlinear model for paclitaxel plasma clearance (CL), involving a linear decrease in this parameter during the infusion and a sigmoidal increase with time after the infusion. The final model described the effect of Zosuquidar 3HCl on paclitaxel CL by a categorical relationship. A 25% decrease in paclitaxel CL was observed, corresponding to an 1.3-fold increase in paclitaxel AUC (from 14829 microg x l(-1) x h to 19115 microg x l(-1) x h following paclitaxel 175 mg x m(-2)) when zosuquidar Cmax was greater than 350 microg x l(-1). This cut-off concentration closely corresponded to the IC50 of a sigmoidal Emax relationship (328 microg x l(-1)). A standard dose of 175 mg x m(-2) of paclitaxel could be safely combined with doses of zosuquidar 3HCl resulting in plasma concentrations known, from previous studies, to result in maximal P-gp inhibition.

CONCLUSIONS

This analysis provides a model which accurately characterized the increase in paclitaxel exposure, which is most likely to be due to P-gp inhibition in the bile canaliculi, in the presence of zosuquidar 3HCl (Cmax > 350 microg x l(-1)) and is predictive of paclitaxel pharmacokinetics following a 3 h infusion. Hence the model could be useful in guiding therapy for paclitaxel alone and also for paclitaxel administered concomitantly with a P-gp inhibitor, and in designing further clinical trials.

Population pharmacokinetics of theophylline during paediatric extracorporeal membrane oxygenation

AIMS

To determine the population pharmacokinetics of theophylline during extracorporeal membrane oxygenation (ECMO) from routine monitoring data.

METHODS

Retrospective data were collected from 75 term neonates and children (age range 2 days to 17 years) receiving continuous infusions of aminophylline (mean rate 9.2 +/- 2.6 micro g kg-1 min-1) during ECMO. A total of 160 plasma concentrations (range 1-8 per patient), sampled at time intervals ranging from 10 h to 432 h, were included. Population PK analysis and model building were carried out using WinNonMix Professional (Version 2.0.1). Cross-validation was used to evaluate the validity and predictive accuracy of the model.

RESULTS

A one-compartment model with first order elimination combined with an additive error model was found to best describe the data. Of the covariables tested, bodyweight significantly influenced clearance and volume of distribution, whereas age was an important determinant of clearance, as adjudged by the differences in the -2 x log likelihood (P < 0.005) and the residual error value. The final model parameters were estimated as: clearance (l h-1) = 0.023 x bodyweight (kg) + 0.000057 x age (days) and volume of distribution (l) = 0.57 x bodyweight (kg). The interindividual variability in clearance and volume of distribution was 38% and 40%, respectively. The residual error corresponded to a standard deviation of 3.6 mg l-1. Cross-validation revealed a median (95% confidence interval) model bias of 9.4% (2.9, 16.5%) and precision of 29.5% (24.8, 36.0%).

CONCLUSIONS

The estimated clearance is significantly lower, and volume of distribution higher, than previously reported in non-ECMO patients of similar age. These differences are probably a result of the expanded circulating volume during ECMO and altered renal and hepatic physiology in this critically ill group. Large interindividual variability reflects the heterogeneous nature of patients treated on ECMO.

Fluoxetine pharmacokinetics in pediatric patients

The objective of this study was to evaluate the pharmacokinetic profile of fluoxetine (FLX) and its major metabolite, norfluoxetine (NORFLX), in children and adolescent patients undergoing psychiatric treatment. Twenty-one pediatric subjects--10 children (6-12 years) and 11 adolescents (13-18 years)--were administered 20 mg FLX for 60 days, with sparse blood samples taken throughout the open-label study. Subjects contributed 168 plasma concentrations. Pharmacokinetic parameters were estimated using a mixed effects nonlinear model. Mean steady-state FLX and NORFLX of 127 ng/mL and 151 ng/mL, respectively, were achieved in children and adolescents after 4 weeks of treatment, with high between-patient variability. FLX was 2-fold higher and NORFLX was 1.7-fold higher in children relative to adolescents; however, when normalized to body weight, FLX and NORFLX were similar for both age groups. Age, body weight, body mass index, and body surface area, modeled independently as continuous variables, significantly improved the population pharmacokinetic model when evaluated as patient factors. Body weight was the covariate retained in the final model. In conclusion, children have 2-fold higher FLX and NORFLX relative to adolescents that appear to be related to indices of body size. The accumulation profile and steady-state concentrations in adolescents appear similar to those in adults.

Population pharmacokinetics of digoxin in Egyptian pediatric patients: impact of one data point utilization

A population pharmacokinetic (PK) study was designed to estimate the PK parameters of digoxin among a selected group of Egyptian pediatric patients (n = 30) with mean age +/- SD and body weight +/- SD of 8.88 +/- 3.01 years and 23.9 +/- 5.8 kg, respectively. All patients had heart failure and were maintained on digoxin given orally. Nonlinear mixed effect modeling software version 5 (NONMEM Project Group, San Francisco, CA) and one-compartment modeling were used for fitting the data. A one-trough steady-state plasma concentration level of digoxin was used in the analysis. The population mean estimates for clearance (CL/f) and volume of distribution (V/f), in which f represents oral bioavailability, were 8.61 L/h and 450 L, respectively. Because of the limited number of samples per patient, regression analysis could not detect a correlation between patient covariates and estimated PK parameters. The analysis did not converge to obtain good parameter estimates. At least two samples per patient should be used to improve the PK estimation and allow better analysis of the relation between the potential covariates and estimated PK parameters.

Non-linear mixed effects modeling of sparse concentration data from rats: application to a glycogen phosphorylase inhibitor

We investigated the use of non-linear mixed effects modeling in two preclinical studies of the glycogen phosphorylase inhibitor 1,4-dideoxy-1,4-imino-D-arabinitol (DAB). In a 28-day repeated-dose toxicity study rats were dosed once daily p.o. with 0, 20, 45, 100, or 470 mg/kg of DAB in aqueous solutions by oral gavage. Three blood samples were obtained from each animal using a staggered sampling scheme. During the cause of model development, data were included from a safety pharmacological cardiovascular study, in which rats were dosed once orally with 0, 4, 40, or 400 mg/kg of DAB thereby enabling an extension of the dose range of the model. DAB was assayed in plasma using a validated LC/MS/MS method. Non-linear mixed effects modeling was performed using the software NONMEM. The covariate analysis comprised dose, sex and time. Exposure results (Cmax, AUC) obtained by mixed effects modeling were compared to results from noncompartmental analysis using naïve pooling of data. The final model was a one-compartment model with first order absorption and a saturation-like dose dependent increase of the (oral) clearance (CL/f) and volume of distribution (V/f). Furthermore, V/f increased (by 55%) from Day 1 to Day 28. The dose dependencies of CL/f and V/f were most likely due to dose dependent decreases of the fraction systemically absorbed (f). The mechanism behind the dose dependencies may be saturation of a (putative) carrier mediated transport or modulation of tight junctions causing a reduced paracellular transport across the intestinal epithelium. Exposure results obtained from the model compared well with results obtained using noncompartmental analysis. An analysis of the data requirements for non-linear mixed effects modeling showed that at least three concentration values per animal were required for model development. We conclude that non-linear mixed effects modeling is feasible even with dose dependent pharmacokinetics in preclinical studies, such as 28-day toxicity studies in rodents. Supplementing data from additional preclinical studies may be required in order to extend the dose range. Non-linear mixed effects models may prove to be valuable tools in early PK and PK-PD modeling during drug development.

Utilisation of pharmacokinetic-pharmacodynamic modelling and simulation in regulatory decision-making

Modelling and simulation (M&S) play an important role in regulatory decision-making that affects both the public and industry. Technological advances in various fields related to drug development call for more focus on ways to optimise current drug development practices. Recognition of the potential of M&S by regulatory agencies inevitably has a substantial impact on drug development. The objective of the current review is to present the various regulatory initiatives for application of M&S to clinical drug development. The relevant parts of the various recommendations issued by the US Food and Drug Administration (FDA), via guidance documents and advisory committee meeting proceedings, are highlighted. Application of M&S to a variety of activities, such as integrating pharmacokinetic-pharmacodynamic knowledge across a new drug application and designing efficient trials, is discussed. Some of the challenges that pharmaceutical institutions currently face when implementing M&S projects, such as team structure, communication with regulators, training and time constraints, are also presented, and solutions are proposed.

Pharmacokinetic/pharmacodynamic studies in drug product development

In the quest of ways for rationalizing and accelerating drug product development, integrated pharmacokinetic/pharmacodynamic (PK/PD) concepts provide a highly promising tool. PK/PD modeling concepts can be applied in all stages of preclinical and clinical drug development, and their benefits are multifold. At the preclinical stage, potential applications might comprise the evaluation of in vivo potency and intrinsic activity, the identification of bio-/surrogate markers, as well as dosage form and regimen selection and optimization. At the clinical stage, analytical PK/PD applications include characterization of the dose-concentration-effect/toxicity relationship, evaluation of food, age and gender effects, drug/drug and drug/disease interactions, tolerance development, and inter- and intraindividual variability in response. Predictive PK/PD applications can also involve extrapolation from preclinical data, simulation of drug responses, as well as clinical trial forecasting. Rigorous implementation of the PK/PD concepts in drug product development provides a rationale, scientifically based framework for efficient decision making regarding the selection of potential drug candidates, for maximum information gain from the performed experiments and studies, and for conducting fewer, more focused clinical trials with improved efficiency and cost effectiveness. Thus, PK/PD concepts are believed to play a pivotal role in streamlining the drug development process of the future.

Design of clinical pharmacology trials

1. There are a variety of methods that could be used to increase the efficiency of the design of experiments. However, it is only recently that such methods have been considered in the design of clinical pharmacology trials. 2. Two such methods, termed data-dependent (e.g. simulation) and data-independent (e.g. analytical evaluation of the information in a particular design), are becoming increasingly used as efficient methods for designing clinical trials. These two design methods have tended to be viewed as competitive, although a complementary role in design is proposed here. 3. The impetus for the use of these two methods has been the need for a more fully integrated approach to the drug development process that specifically allows for sequential development (i.e. where the results of early phase studies influence later-phase studies). 4. The present article briefly presents the background and theory that underpins both the data-dependent and -independent methods with the use of illustrative examples from the literature. In addition, the potential advantages and disadvantages of each method are discussed.

Population pharmacokinetics of magnesium in preeclampsia

OBJECTIVE

The purpose of this study was to determine the population pharmacokinetics of magnesium from sparse observational data in patients with preeclampsia.

STUDY DESIGN

Serum magnesium concentrations (1-11 per patient) were obtained retrospectively from the records of 116 patients with preeclampsia who had a loading dose of magnesium sulfate (16 or 20 mmol), followed by a maintenance dose (1 mmol/h) over an average of 28 hours. Population clearance, volume of distribution, and the baseline magnesium concentration were estimated using the NONMEM program.

RESULTS

The following population typical values, together with the interpatient variability (expressed as coefficient of variation) were obtained with the use of a 1-compartment model: systemic clearance, 4.28 L/h (37.3%); volume of distribution, 32.3 L (32.1%); baseline concentration, 0.811 mmol/L (18.5%). The average half-life was 5.2 hours. Clonus was not obtunded in 4 patients whose serum magnesium concentrations were similar to the average concentration of 1.7 mmol/L. The variability remaining unexplained after the population model was fitted to the data was 6.5% to 10.8%.

CONCLUSION

This study extended knowledge of the pharmacokinetic disposition of magnesium in preeclampsia. The results are potentially useful for the calculation of loading and maintenance doses, particularly when the relationship between serum concentration and effect in preeclampsia is clarified.

Population kinetics of tobramycin in neonates

The population kinetics of tobramycin were studied in 140 neonates (100/40 patients for the index/validation groups, respectively) of 30 to 42 weeks' gestational age and 0.8 to 4.25 kg current body weight in their first 2 weeks of life, undergoing routine therapeutic drug monitoring of their tobramycin serum levels. The 365 tobramycin concentration measurements obtained were analyzed by use of NONMEM according to a one-compartment open model with zero-order absorption and first-order elimination. The effect of a variety of demographic, developmental, and clinical factors (gender, height, birth weight, current weight, gestational age, postnatal age, postconceptional age, and serum creatinine concentration) on clearance and volume of distribution was investigated. Forward selection and backward elimination regression identified significant covariates. The final pharmacostatistical model with influential covariates was as follows (full population): clearance (L/h) = 0.0508 x current weight (kg), multiplied by 0.843 if birth weight was 2.5 kg or less (low-birthweight infants), and volume of distribution (L) = 0.533 x current weight (kg). Using the proportional error model for the random-effects parameters, interindividual variability for clearance and for volume of distribution was determined to be 25.8% and 21.9%, respectively, and the residual variability was 19.2%. In this study, the use of the NONMEM gave significant and consistent information on the pharmacokinetics and the determinants of the pharmacokinetic variability of tobramycin in neonates when compared with available bibliographic information. Moreover, the final population pharmacokinetic model may be used to design a priori recommendations for tobramycin and to improve the dosing readjustments through Bayesian estimation.

How can we do pharmacokinetic studies in the tropics?

Information regarding the pharmacokinetic (PK) and pharmacodynamic (PD) properties of a drug provides the basis for optimizing dosing. PK-PD information should be obtained from patients representative of the overall target population, but in many tropical hospitals or health care facilities it may be medically hazardous or logistically difficult for an ill patient or a young child to be sampled repeatedly. Traditional methods used to determine the pharmacokinetic properties of a drug require analysis of a large number of blood samples per subject. However, using modern statistical methods, sparse datasets (i.e. with assay results from only a few, or as little as one blood sample per subject) can now be analysed by a method termed 'the population approach'. Modern assay techniques can often be adapted to small blood volumes allowing finger prick blood samples to be taken. One of the major aims of the population approach is to distinguish and characterize patient and disease contributors to inter-individual variance in drug pharmacokinetics. The purpose of this paper is to explain the basis of the population approach, to highlight its advantages compared to traditional methods of analysis, and to review the application of the population approach to data from field studies of antimalarial drugs. The design of population pharmacokinetic studies is also discussed briefly. The principles discussed in the paper are also applicable to pharmacodynamic data.

Role of modelling and simulation in Phase I drug development

Although the use of pharmacokinetic/pharmacodynamic modelling and simulation (M&S) in drug development has increased during the last decade, this has most notably occurred in patient studies using the population approach. The role of M&S in Phase I, although of longer history, does not presently have the same impact on drug development. However, trends such as the increased use of biomarkers and clinical trial simulation as well as adoption of the learn/confirm concept can be expected to increase the importance of modelling in Phase I. To help identify the role of M&S, its main advantages and the obstacles to its rational use, an expert meeting was organised by COST B15 in Brussels, January 10-11, 2000. This article presents the views expressed at that meeting. Although it is clear that M&S occurs in only a minority of Phase I clinical trials, it is used for a large number of different purposes. In particular, M&S is considered valuable in the following situations: censoring because of assay limitation, characterisation of non-linearity, estimating exposure-response relationship, combined analyses, sparse sampling studies, special population studies, integrating PK/PD knowledge for decision making, simulation of Phase II trials, predicting multiple dose profile from single dose, bridging studies and formulation development. One or more of the following characteristics of M&S activities are often present and severely impede its successful integration into clinical drug development: lack of trained personnel, lack of protocol and/or analysis plan, absence of pre-specified objectives, no timelines or budget, low priority, inadequate reporting, no quality assurance of the modelling process and no evaluation of cost-benefit. The early clinical drug development phase is changing and if these implementation aspects can be appropriately addressed, M&S can fulfill an important role in reshaping the early trials by more effective extraction of information from studies, better integration of knowledge across studies and more precise predictions of trial outcome, thereby allowing more informed decision making.

The role of population pharmacokinetics in drug development in light of the Food and Drug Administration's 'Guidance for Industry: population pharmacokinetics'

Population pharmacokinetics (PPK) has evolved from a discipline primarily applied to therapeutic drug monitoring to one that plays a significant role in clinical pharmacology in general and drug development in particular. In February 1999 the US Food and Drug Administration issued a 'Guidance for Industry: Population Pharmacokinetics' that sets out the mechanisms and philosophy of PPK and outlines its role in drug development. The application of PPK to the drug development process plays an important role in the efficient development of safe and effective drugs. PPK knowledge is essential for mapping the response surface, explaining subgroup differences, developing and evaluating competing dose administration strategies, and as an aid in designing future studies. The mapping of the response surface is done to maximise the benefit-risk ratio, so that the impact of the input profile and dose magnitude on beneficial and harmful pharmacological effects can be understood and applied to individual patients. PPK combined with simulation methods provides a tool for estimating the expected range of concentrations from competing dose administration strategies. Once extracted, this knowledge can be applied to labelling or used to assess various future study designs. PPK should be implemented across all phases of drug development. For preclinical studies, PPK can be applied to allometric scaling and toxicokinetic analyses, and is useful for determining 'first time in man' doses and explaining toxicological results. Phase I studies provide initial understanding of the structural model and the effect of possible covariates, and may later be used to evaluate PPK differences between patients and healthy individuals. Phase II studies provide the greatest opportunity to map the response surface. With these PPK models it is possible to gain an improved understanding of the role of the dose on the response surface and of the range of expected responses. In phase III and IV studies, PPK is implemented to further refine the PPK model and to explain unexpected responses. Planning for the implementation of PPK across all phases of drug development is necessary, as well as planning for individual PPK studies. Planning should include: defining important questions, identifying covariates and drug-drug interactions that need to be investigated, and identifying the applications and intended use of the model(s). The plan for each project must have a strategy for data management, data collection, data quality assurance, staff training for data collection, data analysis and model validation.

Toxicokinetics of ethylene glycol during fomepizole therapy: implications for management. For the Methylpyrazole for Toxic Alcohols Study Group

STUDY OBJECTIVE

The elimination kinetics of ethylene glycol (EG) in human subjects treated with fomepizole (4-methylpyrazole) were analyzed to establish the efficacy of alcohol dehydrogenase (ADH) inhibition and to characterize elimination pathways.

METHODS

Drug concentration data from patients enrolled in the EG arm of the Methylpyrazole for Toxic Alcohols trial, a prospective, multicenter, open-label trial of fomepizole, were analyzed and compared with published estimates.

RESULTS

In 19 patients analyzed (EG concentrations of 3.5 to 211 mg/dL), elimination was first order during fomepizole monotherapy (half-life of 19.7+/-1.3 hours) and was not affected by the presence of ethanol. The elimination rate was significantly faster (half-life of <8.6+/-1.1 hours, P <.001) in the absence of fomepizole and ethanol. EG elimination by the kidneys was directly proportional to remaining renal function as estimated by creatinine clearance, with a fractional excretion of 25.5%+/-9.4%. Renal elimination and hemodialysis were the only significant routes of EG elimination as long as fomepizole concentrations were maintained well above 10 micromol/L (EG/fomepizole molar ratio, <100:1). All patients with normal serum creatinine concentrations at the initiation of fomepizole treatment had rapid rates of renal elimination (half-life of 16.8+/-0.8 hours).

CONCLUSION

At doses used, fomepizole effectively inhibits ADH-mediated metabolism of EG. Serum creatinine concentration at presentation and creatinine clearance can be used to predict EG elimination during fomepizole therapy and can help determine which patients will require hemodialysis to expedite EG elimination. An absolute EG concentration above 50 mg/dL should no longer be used as an independent criterion for hemodialysis in patients treated with fomepizole.

Impact of population pharmacokinetic-pharmacodynamic analyses on the drug development process: experience at Parke-Davis

BACKGROUND

Continued scepticism about the benefits of population pharmacokinetics and/or population pharmacodynamics, here referred to collectively as the population approach, hampers its widespread application in drug development. At the same time the sources of this scepticism have not been clearly defined. In an attempt to capture and clearly define these concerns and to help communicate the value of the population approach in drug development at Parke-Davis we conducted a survey of customers within the company. The results of this survey are presented here.

METHODS

All drug development programmes conducted over the past 10 years that included a population approach in data analysis and interpretation were identified. A brief description of the population analysis was prepared together with a brief description of how the resulting information was used in each drug development programme. These synopses were forwarded to relevant members of each drug development team together with a survey designed to solicit opinions as to the relevance and impact of these analyses.

RESULTS

The most frequent use of information derived from population-based analysis was in labelling. In all cases of drugs making to New Drug Application (NDA) submission the analyses resulted in information that was included in approved or proposed labelling. In almost half of the cases summarised here (5 of 12), population-based analysis was perceived to have resulted in information that influenced the direction of individual development programmes. In many of these cases the information was serendipitous. It is also noted that most of these analyses were not the result of clearly defined objectives and prospective analysis plans.

CONCLUSIONS

Use of the population approach, even when applied retrospectively, may have value in complementing or supporting interpretation of other data collected during the course of a trial. Atypical systemic exposure is quickly and easily assessed for correlation with adverse events or exceptional efficacy in retrospective or ad hoc evaluation. Although we know of no direct evidence, it is possible that such use of population pharmacokinetic data has facilitated NDA review and approval by providing insight into the role of atypical systemic drug exposure in otherwise spurious events.

Adaptive control methods for the dose individualisation of anticancer agents

Numerous studies have found a clear relationship between systemic exposure and the toxicity or (more rarely) the efficacy of anticancer agents. Moreover, the clearance of most of these drugs differs widely between patients. These findings, combined with the narrow therapeutic index of anticancer drugs, suggest that patient outcome would be improved if doses were individualised to achieve a target systemic exposure. Bayesian maximum a posteriori probability (MAP) forecasting is an efficient and robust method for the optimisation of drug therapy, but its use for anticancer drugs is not yet extensive. The aim of this paper is to review the application of population pharmacokinetics and MAP to anticancer drugs and to evaluate whether and when MAP Bayesian estimation improves the clinical benefit of anticancer chemotherapy. For each drug, the relationships between pharmacokinetic variables [e.g. plasma concentration or the area under the concentration-time curve] and pharmacodynamic effects are described. Secondly, the methodologies employed are considered and, finally, the results are analysed in terms of predictive performance as well as, where possible, the impact on clinical end-points. Some studies were retrospective and intended only to evaluate individual pharmacokinetic parameter values using very few blood samples. Among the prospective trials, a few studied the pharmacokinetic/pharmacodynamic relationships which provided the basis for routine pharmacokinetic monitoring. Others were performed in clinical context where MAP Bayesian estimation was used to determine maximum tolerated systemic exposure (e.g. for carboplatin, topotecan, teniposide) or for pharmacokinetic monitoring (e.g. for methotrexate or platinum compounds). Indeed, its flexibility in blood sampling times makes this technique much more applicable than other limited sampling strategies. These examples demonstrate that individual dose adjustment helps manage toxicity. The performance of pharmacokinetic monitoring is linked to the methodology used at each step of its design and application. Moreover, a limitation to the use of pharmacokinetic monitoring for certain anticancer drugs has been the difficulty in obtaining pharmacokinetic or pharmacodynamic data. Recent progress in analytical methods, as well as the development of noninvasive methods (such as positron emission tomography) for evaluating the effects of chemotherapy, will help to define pharmacokinetic-pharmacodynamic relationships. Bayesian estimation is the strategy of choice for performing pharmacokinetic studies, as well as ensuring that a given patient benefits from the desired systemic exposure. Together, these methods could contribute to improving cancer chemotherapy in terms of patient outcome and survival.