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.     

复方药物临床试验设计的统计学考虑

复方药物的创新研发在制药行业逐渐普及,设计科学合理的复方新药临床试验是复方药物成功上市的关键。本文围绕新药注册流程,介绍了复方药物在剂量探索阶段和确证性阶段所涉及的临床试验设计类型,并详细介绍了在剂量探索阶段析因设计的应用和安慰剂在该阶段设计中的必要性。     

Optimisation of sampling windows design for population pharmacokinetic experiments

This paper describes an approach for optimising sampling windows for population pharmacokinetic experiments. Sampling windows designs are more practical in late phase drug development where patients are enrolled in many centres and in out-patient clinic settings. Collection of samples under the uncontrolled environment at these centres at fixed times may be problematic and can result in uninformative data. Population pharmacokinetic sampling windows design provides an opportunity to control when samples are collected by allowing some flexibility and yet provide satisfactory parameter estimation. This approach uses information obtained from previous experiments about the model and parameter estimates to optimise sampling windows for population pharmacokinetic experiments within a space of admissible sampling windows sequences. The optimisation is based on a continuous design and in addition to sampling windows the structure of the population design in terms of the proportion of subjects in elementary designs, number of elementary designs in the population design and number of sampling windows per elementary design is also optimised. The results obtained showed that optimal sampling windows designs obtained using this approach are very efficient for estimating population PK parameters and provide greater flexibility in terms of when samples are collected. The results obtained also showed that the generalized equivalence theorem holds for this approach.     

Phase I clinical trial and pharmacokinetic evaluation of doxorubicin carried by polyisohexylcyanoacrylate nanoparticles

Summary Doxorubicin (DXR) incorporated into biodegradable acrylate nanoparticles such as polyisohexylcyanoacrylate (PIHCA) has been shown to increase DXR cytotoxicity and reduce cardiotoxicity by modifying tissue distribution in preclinical studies. We have conducted a phase I clinical trial of DXR-PIHCA in 21 patients with refractory solid tumors (10 male, 11 female, median age: 53 years, median PS: 1, prior free-DXR therapy: 7 patients). A total of 32 courses at 28 day intervals were administered at 6 dose levels (15, 30, 45, 60, 75 and 90 mg/m²). The drug was given as a 10 minute IV infusion on day 1 to the first 5 patients: 2 of them presented a grade 2 allergic reaction (W.H.O. criteria) during infusion, which was rapidly reversible once drug administration was discontinued. Subsequently, in the other 16 patients, the administration was modified to a 60 minute i.v. perfusion diluted in 250 cc of Dextrose 5%: only 1 patient presented the same allergic reaction. Grade 2 fever and vomiting occurred in 9 patients and 7 patients respectively during the first 24 h after treatment. There was no cardiac toxicity among the 18 evaluable patients. Grade 3 or 4 hematologic toxicity occurred at the 75 and 90 mg/m² dose level. The dose limiting toxicity was neutropenia. The maximum tolerated dose was 90 mg/m² and the recommended phase II dose was 75 mg/m². A pharmacokinetic evaluation of DXR-PIHCA was conducted in 3 patients each at a different dose level (60,60 and 75 mg/m²) and was compared with free DXR given to the same patients in the same conditions.     

用模型和模拟方法设计氨氯地平的群体药动学研究方案

合理的采样设计是建立可靠群体药动学模型的重要基础。应用非线性混合效应模型的群体药动学研究,是一种有效利用稀疏血样数据估算群体药动学参数的方法。本研究根据D最优化设计和贝叶斯法设计采样方案。以已报道的氨氯地平群体药动学模型为基础,根据临床研究的目的、给药方案和随访时间等设计几套采样方案,采用WinPOPT软件计算优化采样方案,用蒙特卡罗法(Monte Carlo)对各优化的采样方案分别建立一套含400个患者的NONMEM数据文件,用NONMEM7.2软件模拟氨氯地平的浓度数据,然后估算其重要药动学参数(CL/F,V/F和Ka),并计算其平均预测误差(MPE)和平均绝对预测误差(MAPE)。在6个采样方案中,以方案6和3对CL/F估算的准确度和精密度较优,MPE分别为0.1%和0.6%,MAPE均为0.7%。对V的估算,各采样方案间无明显差异。因此,选用氨氯地平拟合药动学参数的准确度和精密度较优,且采样点个数较少的方案3为最佳临床研究方案。本研究旨在为开展氨氯地平在肾功能损害合并高血压患者的群体药动学研究提供科学、有效的采样方法,为群体PK/PD研究提供一种优化设计临床研究方案的科学方法。     

An evaluation of a clinical pharmacokinetic service for serum digoxin levels

The appropriateness of requests by physicians for serum digoxin measurements (SDMs) and the appropriateness of responses by physicians to a reported SDM were evaluated with and without the contribution of a pharmacy-based clinical pharmacokinetic service (CPS). Also, for each patient, the difference between dosage regimens that had been established by means of SDMs and those regimens that would have been estimated by the method of Dobbs et al. was analyzed. This prospective evaluation involved two 3-week phases and included inpatients. During phase I the CPS was intact, while during phase II it was discontinued. There was a significant increase from phase I (23.4%) to phase II (36.4%) in the rate of inappropriate action or inaction with respect to requesting SDMs. There was also a significant increase from 9.7 to 24.6% in the rate of inappropriate dosage adjustments in response to a reported SDM. There was a statistically significant difference between the digoxin dosages estimated by the method of Dobbs et al. and the actual dosage regimen established with SDMs. The disparity between the CPS approach and the Dobb et al. method was such that 23.4% of digoxin dosage regimens determined with the guidance of SDMs did not result in an estimated steady-state level within the therapeutic range when those regimens were applied to the Dobbs et al. method. Thus, the pharmacy-based CPS improved the appropriateness of physician utilization of SDMs. Also, sole use of the Dobbs et al. method as an example of a noninvasive approach to digoxin dosing is not a reasonable alternative in a tertiary care institution.     

Dosing and switching strategies for paliperidone palmitate: based on population pharmacokinetic modelling and clinical trial data

Paliperidone palmitate is a second-generation, long-acting injectable (LAI) antipsychotic recently approved by the US FDA and European Medicines Agency for use in patients with schizophrenia. This article reviews the recommended dosing regimens for initiation and maintenance treatment with paliperidone palmitate in adult patients with schizophrenia. We also address issues of switching to paliperidone palmitate from other antipsychotics, managing missed doses and dosing in special patient populations. The dosing recommendations that were approved by the FDA and other regulatory agencies around the world are based on the results of population pharmacokinetic (PK) simulations and data from clinical trials that are presented in this review. A one-compartment disposition model with zero/first-order absorption best described the PK of paliperidone palmitate. Population PK models for extended-release paliperidone and long-acting risperidone were also developed and we report the results from these models. The PK profiles for 5000 patients were simulated after paliperidone palmitate injections. The population median and 90% prediction intervals of the simulated plasma concentration versus time profiles after multiple doses are graphically displayed in this review. Based on the data from model-based PK simulations, the approved recommended initiation regimen for paliperidone palmitate is 150?mg equivalent (mg eq.) paliperidone (paliperidone palmitate 234?mg) on day 1 followed by 100?mg eq. paliperidone (paliperidone palmitate 156?mg) on day 8, each administered into the deltoid muscle, using a 1-inch 23-gauge needle in those weighing <90?kg and a 1.5-inch 22-gauge needle in those weighing ≥90?kg. No oral supplementation is required. Monthly maintenance dosing is in the range of 25-150?mg eq. paliperidone (paliperidone palmitate 39-234?mg; recommended dose of 75?mg eq. paliperidone [paliperidone palmitate 117?mg]) injected into the deltoid (needle size is weight adjusted) or gluteal (using a 1.5-inch 22-gauge needle) muscle. The day 8 dose may be administered ±2 days and monthly doses ±7 days, without a clinically significant impact on plasma concentrations. The re-initiation schedule in patients whose last maintenance dose was >6 weeks previously is dependent upon the duration of time since the last paliperidone palmitate injection. In patients with mild renal impairment (creatinine clearance [CL(CR)]: 50-80?mL/min), dosage should be adjusted. No dose adjustment is required in patients with mild or moderate hepatic impairment; no data currently exist regarding severe hepatic impairment. Elderly patients with normal renal function should receive the same dosage as younger adult patients with normal renal function. In the event of an age-related decline in CL(CR), dosage should be adjusted accordingly. Paliperidone palmitate can be initiated the day after discontinuing previous oral antipsychotic treatment. In patients switching from other LAIs (including long-acting risperidone), paliperidone palmitate dosing should be initiated at the time of what would have been the next scheduled injection of the previous LAI, and continued monthly thereafter. In summary, following initiation dosing, paliperidone palmitate is administered on a monthly basis. It is the first of the second-generation antipsychotics to be available and approved with this dosing regimen. Population PK modelling presented in this review has helped provide practical guidance for administering this novel LAI antipsychotic.     

Piroxicam capsules versus suppositories: a pharmacokinetic and clinical trial

15 patients with rheumatoid arthritis or osteoarthritis received a single dose (20 mg) piroxicam (Felden) as suppository. Serum piroxicam concentrations were assayed by fluorometry 1, 2, 4, and 8 h after the installation of the suppository, the mean values being 1.3, 1.9, 1.8, and 1.8 mg/l, respectively. Then the patients continued on oral piroxicam 20 mg daily for maximum 3 weeks, and serum piroxicam levels (mean 6.3 mg/l) were checked at the end of this period. Nine patients then continued on piroxicam suppositories 20 mg daily for one week, and serum piroxicam levels (mean 4.5 mg/l) were again assayed at the end of this maintenance. Pain at rest, pain on motion, and joint movement restriction were scored on day 1, after oral maintenance, and after rectal maintenance. Reduced scores were found with time, but the only statistically significant effect was in the overall subjective pain relief measured after oral maintenance. Rectal irritation was recorded in one patient. It is concluded that a) absorption of piroxicam from suppository was adequate, b) it was possible to maintain adequate serum piroxicam levels by repeated administration of suppository for one week, and c) the gastrointestinal toleration was acceptable in these patients selected for showing poor tolerance towards other nonsteroidal antiinflammatories.     

A computationally efficient approach for the design of population pharmacokinetic studies

A computationally efficient procedure was devised for designing experiments in which population pharmacokinetic parameters are estimated. The method, referred to as the large-sample approach, evaluates the variances of parameter estimates for a population pharmacostatistical model. The procedure utilizes the NONMEM program and requires a single simulation that assumes many, say 1000, subjects. The approach reduced CPU time by about a factor of 50 when compared with the evaluation of the same variances by the direct simulation of experiments. The large-sample and simulation approaches yielded generally similar values for the variances of parameter estimates. The variances calculated by the large-sample approach were, in the case of a simple model, close to the expected variances. The proposed method identified correctly the imprecise parameter estimates but somewhat underestimated their variances.This work was supported by the Medical Research Council of Canada.     

A note on population pharmacokinetic studies with a single sampling design

The choice of sampling time point in a population pharmacokinetic study with severe limitation on the number of samples per study subject (single sampling design) is critical in obtaining reliable parameter estimates. The authors have investigated the relationship between the timing as well as the degree of distribution of a sampling point among study subjects and the reliability of the estimates of pharmacokinetic parameters in a population pharmacokinetic study. This was achieved through a simulation, assuming an intravenously administered drug whose pharmacokinetic profile follows a 1-compartment model. The convergence rate of the NLMIXED procedure as well as the values of bias and MSE for the estimated parameters showed great variability depending on the sampling schedules. The results indicate that, in the case of a single sampling design, the sampling points should be distributed as widely as possible over a time range along the concentration-time profile to obtain reliable parameter estimates.     

Statistical issues on objective,design, and analysis of noninferiority active-controlled clinical trial

In practice, "noninferiority" active-controlled trials have been designed for three different objectives: establishing evidence of efficacy over placebo, preserving a specific percentage of the effect size of the active control, or demonstrating the test treatment is "not much inferior" to the active control. All three objectives can be represented by the same set of statistical hypotheses with the parameters defined differently. The various designs and statistical analysis procedures for active-controlled trials proposed in the literature can be group into two basic types: the historical-controlled trial approach and the cross-study comparison approach. These approaches require some unverifiable constancy assumptions. Under the constancy assumptions, the cross-study comparison uses the estimate effect of active-control treatment as the unbiased estimate of the active/placebo difference in the current noninferiority trial. A normalized Z-statistic is used to test the hypotheses. On the other hand, the historical controlled trial approach uses a conservative confidence limit as if it were a constant to replace the active/placebo difference in the current trial. The two approaches may lead to consistent conclusions only when the constancy assumptions can be supported by a large number of historical studies giving a consistent active-control treatment effect over placebo and that the active-control effect does not change over time.     

A computationally efficient approach for the design of population pharmacokinetic studies.

A computationally efficient procedure was devised for designing experiments in which population pharmacokinetic parameters are estimated. The method, referred to as the large-sample approach, evaluates the variances of parameter estimates for a population pharmacostatistical model. The procedure utilizes the NONMEM program and requires a single simulation that assumes many, say 1000, subjects. The approach reduced CPU time by about a factor of 50 when compared with the evaluation of the same variances by the direct simulation of experiments. The large-sample and simulation approaches yielded generally similar values for the variances of parameter estimates. The variances calculated by the large-sample approach were, in the case of a simple model, close to the expected variances. The proposed method identified correctly the imprecise parameter estimates but somewhat underestimated their variances.     

Rationale for a non-inferiority clinical trial design focused on subpopulations

Although double-blind, placebo-controlled clinical trials are utilized extensively to characterize the efficacy and safety of new treatment options, the characteristics of the trial participants often do not most cases, one or more patient subgroups (whether defined by race, ethnicity, co-morbidity, concomitant medication, age, or gender) will be under-represented. Understanding treatment responses in these subpopulations is a vital component of the overall therapeutic profile of a medication. Several different approaches to subgroup analyses within a single trial have been described. In addition, meta-analytic and data pooling approaches utilize results from multiple clinical trials of similar design to increase the number of patients within a targeted subgroup. If the results from exploratory analyses are suggestive of a clinically relevant difference in treatment response for a particular subgroup, then implementation of a prospectively designed clinical trial may be warranted. In this commentary, we discuss the design and results of various studies that include subgroup analyses. In addition, we describe a novel study design with a non-inferiority subpopulation analysis (NISA) that may provide new insights with respect to subgroup analyses. The NISA study design relies on characterization of the dominant group of patients recruited to date in placebo-controlled trials. In the NISA study, the group of patients with those same characteristics is referred to as the Core group. The other key features of the NISA design include non-inferiority analyses comparing subgroups to the Core group and study conditions closely aligned with routine clinical practice (heterogeneous study population and open-label drug administration without placebo). Limitations of the NISA design include the requirement of previously conducted placebo-controlled trials, the inability to compare treatment response to placebo, and that NISA has yet to be validated in practice. We also describe the implementation of the NISA study design in two ongoing clinical trials. After completion of these two studies, the practical value of the NISA design can be more thoroughly evaluated.     

Rationale for a non-inferiority clinical trial design focused on subpopulations

Although double-blind, placebo-controlled clinical trials are utilized extensively to characterize the efficacy and safety of new treatment options, the characteristics of the trial participants often do not reflect those of the wider patient population. In most cases, one or more patient subgroups (whether defined by race, ethnicity, co-morbidity, concomitant medication, age, or gender) will be under-represented. Understanding treatment responses in these subpopulations is a vital component of the overall therapeutic profile of a medication. Several different approaches to subgroup analyses within a single trial have been described. In addition, meta-analytic and data pooling approaches utilize results from multiple clinical trials of similar design to increase the number of patients within a targeted subgroup. If the results from exploratory analyses are suggestive of a clinically relevant difference in treatment response for a particular subgroup, then implementation of a prospectively designed clinical trial may be warranted. In this commentary, we discuss the design and results of various studies that include subgroup analyses. In addition, we describe a novel study design with a non-inferiority subpopulation analysis (NISA) that may provide new insights with respect to subgroup analyses. The NISA study design relies on characterization of the dominant group of patients recruited to date in placebo-controlled trials. In the NISA study, the group of patients with those same characteristics is referred to as the Core group. The other key features of the NISA design include non-inferiority analyses comparing subgroups to the Core group and study conditions closely aligned with routine clinical practice (heterogeneous study population and open-label drug administration without placebo). Limitations of the NISA design include the requirement of previously conducted placebo-controlled trials, the inability to compare treatment response to placebo, and that NISA has yet to be validated in practice. We also describe the implementation of the NISA study design in two ongoing clinical trials. After completion of these two studies, the practical value of the NISA design can be more thoroughly evaluated.     

Development of a population pharmacokinetic database for tianeptine

Summary Two thousand three hundred and thirty five plasma concentrations of tianeptine from 112 patients enrolled in nine studies of tianeptine pharmacokinetics performed prior to the marketing of the drug were pooled for analysis using mixed-effect modeling. Studies represented a combination of single dose and multiple dosing at steady-state. Tianeptine plasma concentration time data were fit to a two compartment model with first order absorption using the NONMEM computer program.The results of this analysis suggested that alcoholism is associated with significant increase in clearance (124% increase) and volume of the central compartment (161% increase). The volume of the peripheral compartment is significantly lower in women (31% decrease) and in depressed patients (59% decrease).The population mean (interindividual variability) clearance was equal to 0.17 l·h^–1·kg^–1 (28.6%), the volume of central compartment was 0.13 l·kg^–1 (60.4%), intercompartmental clearance was 0.07 l·h^–1·kg^–1 (30.1%), volume of the tissue compartment was 1.17 l·kg^–1 (28.3%), and the absorption rate constant was 0.63 h^–1 (21.8%). The residual variability was approximately 30% at concentrations expected during clinical use of the drug.Because of the increased clearance, alcoholic patients would be expected to have significantly reduced concentrations during steady-state dosing. These population parameters provide a basis for developing initial dosing recommendations and for performing bayesian evaluations of drug concentrations obtained in post-marketing studies.     

Innovative clinical trial design for pediatric therapeutics

Until approximately 15 years ago, sponsors rarely included children in the development of therapeutics. US and European legislation has resulted in an increase in the number of pediatric trials and specific label changes and dosing recommendations, although infants remain an understudied group. The lack of clinical trials in children is partly due to specific challenges in conducting trials in this patient population. Therapeutics in special populations, including premature infants, obese children and children receiving extracorporeal life support, are even less studied. National research networks in Europe and the USA are beginning to address some of the gaps in pediatric therapeutics using novel clinical trial designs. Recent innovations in pediatric clinical trial design, including sparse and scavenged sampling, population pharmacokinetic analyses and ‘opportunistic’ studies, have addressed some of the historical challenges associated with clinical trials in children.     

Innovative clinical trial design for pediatric therapeutics

Until approximately 15 years ago, sponsors rarely included children in the development of therapeutics. US and European legislation has resulted in an increase in the number of pediatric trials and specific label changes and dosing recommendations, although infants remain an understudied group. The lack of clinical trials in children is partly due to specific challenges in conducting trials in this patient population. Therapeutics in special populations, including premature infants, obese children and children receiving extracorporeal life support, are even less studied. National research networks in Europe and the USA are beginning to address some of the gaps in pediatric therapeutics using novel clinical trial designs. Recent innovations in pediatric clinical trial design, including sparse and scavenged sampling, population pharmacokinetic analyses and 'opportunistic' studies, have addressed some of the historical challenges associated with clinical trials in children.     

Memantine pharmacotherapy: a naturalistic study using a population pharmacokinetic approach

BACKGROUND AND OBJECTIVE: Memantine plasma concentrations show considerable interindividual variability. High memantine plasma concentrations are associated with the occurrence of neuropsychiatric adverse effects such as confusion. The objective of the present study was, therefore, to investigate the reasons for the observed variability of the pharmacokinetics of memantine in a representative patient population and to explore patient covariates on drug disposition. SUBJECTS: Fifty-six ambulatory Western European patients aged 50-91 years. METHODS: This prospective study used a full population pharmacokinetic sampling design. After at least 11 days of continuous memantine intake, the patients provided pharmacokinetic profiles, with six measurements each over a 12-hour period, with a total of 335 serum memantine concentrations. Covariates considered for inclusion in the models were: subject demographic factors (age, total bodyweight, gender), laboratory tests (urinary pH), total daily dose of memantine, memantine formulation type, comedication eliminated via tubular secretion and smoking history. The model development was conducted in three sequential steps. First, an adequate basic structural model was chosen (e.g. a one-, two- or three-compartment pharmacokinetic model). The data were analysed to estimate population pharmacokinetic parameters with the nonlinear mixed-effects model computer program NONMEM. Second, the effects of covariates were investigated on post hoc estimates using multivariate statistics. Third, the covariates with significant effects in the second step were used to build a final covariate pharmacokinetic model, again using NONMEM. RESULTS: A two-compartment model with first-order absorption satisfactorily described memantine pharmacokinetics. In the final regression model, total bodyweight, memantine formulation type (solution vs tablets) and concomitant medication eliminated via tubular secretion were all important determinants of the apparent clearance (CL/F). The final regression model was: CL/F (L/h) = (1.92 + 0.048 x BW (kg)) x 0.530(FRM) x 0.769(CMD) where FRM = 1 for patients receiving memantine solution, otherwise FRM = 0; CMD = 1 for patients receiving a comedication eliminated via tubular secretion, otherwise CMD = 0; and BW is bodyweight. Compared with the basic model, the final population pharmacokinetic model explained 61% of the interindividual variance of the apparent clearance. CONCLUSIONS: The population pharmacokinetic model that was developed identified a set of sources of variability in the apparent clearance of memantine, which can be used as a reference in order to optimise memantine therapy in Western European patients.     

A pragmatic approach to the design of population pharmacokinetic studies

The publication of a seminal article on nonlinear mixed-effect modeling led to a revolution in pharmacokinetics (PKs) with the introduction of the population approach. Since then, interest in obtaining accurate and precise estimates of population PK parameters has led to work on population PK study design that extended previous work on optimal sampling designs for individual PK parameter estimation. The issues and developments in the design of population PK studies are reviewed as a prelude to investigating, via simulation, the performance of 2 approaches (population Fisher information matrix D-optimal design and informative block [profile] randomized [IBR] design) for designing population PK studies. The results of our simulation study indicate that the designs based on the 2 approaches yielded efficient parameter estimates. The designs based on the 2 approaches performed similarly, and in some cases designs based on the IBR approach were slightly better. The ease with which the IBR designs can be generated makes them preferable in drug development, where pragmatism and time are of great consideration. We, therefore, refer to the IBR designs as pragmatic designs. Pragmatic designs that achieve high efficiency in the estimation parameters should be used in the design of population PK studies, and simulation should be used to determine the efficiency of the designs.