Post-prostatectomy radiotherapy adversely affects urinary continence irrespective of radiotherapy regime.

PURPOSE: To investigate the influence of different postoperative radiotherapy (RT) regimes on post-prostatectomy continence and QoL. METHODS: Men after prostatectomy (RP) and RT were assigned in adjuvant (ART), early salvage (ESRT) and salvage radiotherapy (SRT) groups depending on time of initiation, indication and pre-RT-PSA (≤/>0.5 ng/ml). Continence and QoL outcomes were evaluated by validated questionnaire. Statistical analysis included students t test, Chi square, Fisher's test, ROC- and McNemar-Bowker-Analyses. RESULTS: The mean follow-up was 5.1 years. 33.5, 38.2 and 28.3% received ART, ESRT and SRT, respectively. Mean time to RT was 0.3 (±0.4), 1.8 (±2.5) and 3.3 (±3.6) years respectively. Differences in age at RP (p = 0.54) and RT (p = 0.47) between groups were not significant. Mean-RT-dose was similar (p = 0.70). Differences in continence distribution between groups before (p = 0.56) and after RT (p = 0.38) were not significant. No significant differences were observed for frequency (p = 0.58) or amount (p = 0.88) of urine loss, impact on QoL (p = 0.13) and ICIQ-SF scores (p = 0.69) between groups. Even though no significant difference in post-RT-continence (p = 0.89) was observed in the direct comparison between groups, a significant worsening of long-term continence was observed in all groups (p < 0.001). We found no cutoff and no time-point after RP at which this negative effect of RT on continence became insignificant (AUC = 0.474). A subgroup with apparent local recurrence showed no differences for ICIQ-SF-score (p = 0.155), QoL (0.077), incontinence grade (p = 0.387), frequency (p = 0.182) and amount (p = 0.415) of urine loss. Proportionally more men in this subgroup remembered deterioration of continence after RT (p = 0.029). CONCLUSION: Postoperative RT adversely affects long-term continence; this negative effect is irrespective of time of initiation or indication for RT. These results suggest a need for innovative strategies of prostate cancer therapy with lasting oncological, functional and QoL outcomes.

Good Practices in Model-Informed Drug Discovery and Development: Practice, Application, and Documentation.

This document was developed to enable greater consistency in the practice, application, and documentation of Model-Informed Drug Discovery and Development (MID3) across the pharmaceutical industry. A collection of "good practice" recommendations are assembled here in order to minimize the heterogeneity in both the quality and content of MID3 implementation and documentation. The three major objectives of this white paper are to: i) inform company decision makers how the strategic integration of MID3 can benefit R&D efficiency; ii) provide MID3 analysts with sufficient material to enhance the planning, rigor, and consistency of the application of MID3; and iii) provide regulatory authorities with substrate to develop MID3 related and/or MID3 enabled guidelines.

Pharmacometrics: opportunity for reducing disease burden in the developing world: the case of Africa.

Pharmacometricians are virtually nonexistent in Africa and the developing world. The unrelenting burden of infectious diseases, which are often treated using medicines with narrow effectiveness and safety dose ranges, and the growing prevalence and recognition of non-communicable diseases represent significant threats for the patients, although affording an opportunity for advancing science. This article outlines the case for pharmacometricians to redirect their expertise to focus on the disease burden affecting the developing world.CPT: Pharmacometrics & Systems Pharmacology (2013) 2, e69; doi:10.1038/psp.2013.45; published online 28 August 2013.

Animal Health Modeling & Simulation Society: a new society promoting model-based approaches in veterinary pharmacology.

The Animal Health Modeling & Simulation Society (AHM&S) is a newly founded association (2012) that aims to promote the development, application, and dissemination of modeling and simulation techniques in the field of Veterinary Pharmacology and Toxicology. The association is co-chaired by Pr. Johan Gabrielsson (Europe), Pr. Jim Riviere (USA), and secretary Dr. Jonathan Mochel (Switzerland). This short communication aims at presenting the membership, rationale and objectives of this group.

Pharmacokinetic similarity of biologics: analysis using nonlinear mixed-effects modeling.

Our objective was to show, using two examples, that a pharmacokinetic (PK) similarity analysis can be performed using nonlinear mixed-effects models (NLMEM). We used two studies that compared different biosimilars: a three-way crossover trial with somatropin and a parallel-group trial with epoetin-α. For both data sets, the results of NLMEM-based analysis were compared with those of noncompartmental analysis (NCA). For the latter analysis, we performed an NLMEM-based equivalence Wald test on secondary parameters of the model: the area under the curve and the maximal concentration. Somatropin PK was described by a one-compartment model and epoetin-α PK by a two-compartment model with linear and Michaelis-Menten elimination. For both studies, similarity of PK was demonstrated by means of both NCA and NLMEM, and both methods led to similar results. Therefore, for establishing similarity, PK data can be analyzed by either of the methods. NCA is an easier approach because it does not require data modeling; however, NLMEM leads to a better understanding of the underlying biological system.

Modelling response time profiles in the absence of drug concentrations: definition and performance evaluation of the K-PD model.

The plasma concentration-time profile of a drug is essential to explain the relationship between the administered dose and the kinetics of drug action. However, in some cases such as in pre-clinical pharmacology or phase-III clinical studies where it is not always possible to collect all the required PK information, this relationship can be difficult to establish. In these circumstances several authors have proposed simple models that can analyse and simulate the kinetics of the drug action in the absence of PK data. The present work further develops and evaluates the performance of such an approach. A virtual compartment representing the biophase in which the concentration is in equilibrium with the observed effect is used to extract the (pharmaco)kinetic component from the pharmacodynamic data alone. Parameters of this model are the elimination rate constant from the virtual compartment (KDE), which describes the equilibrium between the rate of dose administration and the observed effect, and the second parameter, named EDK(50) which is the apparent in vivo potency of the drug at steady state, analogous to the product of EC(50), the pharmacodynamic potency, and clearance, the PK "potency" at steady state. Using population simulation and subsequent (blinded) analysis to evaluate this approach, it is demonstrated that the proposed model usually performs well and can be used for predictive simulations in drug development. However, there are several important limitations to this approach. For example, the investigated doses should extend from those producing responses well below the EC(50) to those producing ones close to the maximum response, optimally reach steady state response and followed until the response returns to baseline. It is shown that large inter-individual variability on PK-PD parameters will produce biases as well as large imprecision on parameter estimates. It is also clear that extrapolations to dosage routes or schedules other than those used to estimate the parameters should be undertaken with great caution (e.g., in case of non-linearity or complex drug distribution). Consequently, it is advised to apply this approach only when the underlying structural PD and PK are well understood. In any case, K-PD model should definitively not be substituted for the gold standard PK-PD model when correct full model can and should be identified.

Population pharmacokinetics of ibandronate in Caucasian and Japanese healthy males and postmenopausal females.

INTRODUCTION: Ibandronate is a potent, nitrogen-containing bisphosphonate that is licensed as a once-monthly oral preparation and is currently in clinical development as a novel intermittent intravenous (i.v.) injection in osteoporosis. Ibandronate pharmacokinetic (PK) data were used to develop a PK model that could ultimately be incorporated into a PK pharmacodynamic (PD) model to assist the ibandronate development program through computer-assisted trial design. This manuscript reports the use of non-linear mixed-effects modeling to characterize the PK of ibandronate, to examine the possible influence of ethnicity on the disposition of ibandronate and to develop an appropriate population PK model for ibandronate. METHODS: A retrospective, cross-study population PK analysis was performed using PK data from five phase I studies with i.v. ibandronate (0.125 - 2.0 mg) conducted in Caucasian and Japanese healthy male volunteers, postmenopausal Caucasian women without osteopenia and postmenopausal Japanese women with osteopenia. The following covariates were investigated to establish their influence on the central volume of distribution (V1) and drug clearance (CL): age, body weight, gender, disease status (healthy versus osteopenic), creatinine clearance (CLCR), and ethnicity (Japanese versus Caucasian). Serum concentrations of ibandronate were quantified by GC-MS or ELISA, and data were modeled using non-linear mixed-effects modeling implemented by the software program NONMEM. RESULTS: The PK of ibandronate was adequately described by a linear 3-compartment model. Disease status, body weight, gender and CLCR significantly influenced ibandronate CL (10 34%) and the latter 3 also influenced V1 (20 29%). Ethnicity was not a determinant for ibandronate PK in the final model. Although gender was the most influential covariate, differences in V1 and CL between the sexes were modest (29 and 34%, respectively) and the overall effects on ibandronate exposure (Cmax and AUC) were not clinically relevant. The final model described the observed PK of ibandronate well, and all PK parameters were estimated with an acceptable degree of precision (SE < 13%). CONCLUSION: The PK of i.v. ibandronate was well described by a linear 3-compartment population PK model that included disease status, body weight, gender and CLCR as covariates, but without greatly affecting ibandronate exposure (Cmax and AUC). Ethnicity did not influence ibandronate PK and was not included in the final model.

Population pharmacokinetic analysis of the major metabolites of capecitabine.

Capecitabine has been developed as an orally administered tumor selective fluoropyrimidine for use in the treatment of breast and colorectal cancer. The metabolic pathway for capecitabine includes 5'-deoxy-5-fluorocytidine (5'-DFCR) and 5'-deoxy-5-fluorouridine (5'-DFUR), which is then converted to the pharmacologically active agent 5-fluorouracil (5-FU). A previous analysis showed that systemic exposure to 5'-DFUR and alpha-fluoro-beta-alanine (FBAL), a catabolite of 5-FU, was predictive of dose limiting toxicities. Therefore, a multi-response population pharmacokinetic (PK) model for the description of plasma concentrations of 5'-DFUR, 5-FU and FBAL following oral administration of capecitabine was developed using NONMEM. PK data from a bioequivalence study in 24 patients with various solid tumors were used to develop the PK structural part of the population PK model. The 5'-DFUR, 5-FU and FBAL plasma concentrations were described by a linear disposition PK model with first order absorption and lag time. Sparse plasma concentration data from 54 phase II breast cancer patients were added to the bioequivalence data and the influence of covariates on the apparent oral clearances of 5'-DFUR, 5-FU and FBAL and on the apparent volume of distribution of FBAL was investigated. This was conducted by including all significant (p < 0.05) single covariate-PK parameter pairs in the full PK model, followed by one by one deletion (p < 0.001) from the population model. Statistically significant effects were found for the influence of gender, body surface area and total bilirubin on 5'-DFUR clearance and the influence of creatinine clearance on FBAL clearance. However, none of these effects were considered to have clinical relevance.

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.

Pharmacometrics: modelling and simulation tools to improve decision making in clinical drug development.

There is broad recognition within the pharmaceutical industry that the drug development process, especially the clinical part of it, needs considerable improvement to cope with rapid changes in research and health care environments. Modelling and simulation are mathematically founded techniques that have been used extensively and for a long time in other areas than the pharmaceutical industry (e.g. automobile, aerospace) to design and develop products more efficiently. Both modelling and simulation rely on the use of (mathematical and statistical) models which are essentially simplified descriptions of complex systems under investigation. It has been proposed to integrate pharmacokinetic (PK) and pharmacodynamic (PD) principles into drug development to make it more rational and efficient. There is evidence from a survey on 18 development projects that a PK/PD guided approach can contribute to streamline the drug development process. This approach extensively relies on PK/PD models describing the relationships among dose, concentration (and more generally exposure), and responses such as surrogate markers, efficacy measures, adverse events. Well documented empirical and physiologically based PK/PD models are becoming available more and more, and there are ongoing efforts to integrate models for disease progression and patient behavior (e.g. compliance) as well. Other types of models which are becoming increasingly important are population PK/PD models which, in addition to the characterization of PK and PD, involve relationships between covariates (i.e. patient characteristics such as age, body weight) and PK/PD parameters. Population models allow to assess and to quantify potential sources of variability in exposure and response in the target population, even under sparse sampling conditions. As will be shown for an anticancer agent, implications of significant covariate effects can be evaluated by computer simulations using the population PK/PD model. Stochastic simulation is widely used as a tool for evaluation of statistical methodology including for example the evaluation of performance of measures for bioequivalence assessment. Recently, it was suggested to expand the use of simulations in support of clinical drug development for predicting outcomes of planned trials. The methodological basis for this approach is provided by (population) PK/PD models together with random sampling techniques. Models for disease progression and behavioral features like compliance, drop-out rates, adverse event dependent dose reductions, etc. have to be added to population PK/PD models in order to mimic the real situation. It will be shown that computer simulation helps to evaluate consequences of design features on safety and efficacy assessment of the drug, enabling identification of statistically valid and practically realisable study designs. For both modelling and simulation a guidance on 'best practices' is currently worked out by a panel of experts comprising representatives from academia, regulatory bodies and industry, thereby providing a necessary condition that model-based analysis and simulation will further contribute to streamlining pharmaceutical drug development processes.

Pharmacokinetic/pharmacodynamic modeling in drug development.

We propose a framework for considering the role of pharmacokinetic/pharmacodynamic modeling in drug development and an appraisal of its current and potential impact on that activity. After some introduction, definitions, and background information on drug development, we discuss subject-matter models that underlie pharmacokinetic/pharmacodynamic modeling and show how they determine appropriate statistical models. We discuss the broad role modeling can play in drug development, enhancing primarily the "learning" steps, i.e. acquiring the information needed for the label and for planning efficient confirmatory clinical trials. Examples of past applications of modeling to drug development are presented in tabular form, followed by a discussion of some practical issues in application. Modeling will not reach its potential utility until it is manifest as a visible and separate work unit within a drug development program. We suggest that that work unit is the "in numero" study: a protocol-driven exercise designed to extract additional information, and/or answer a specific drug-development question, through an integrated model-based (meta-) analysis of existent raw data, often pooled across separate (clinical) studies.

Population pharmacokinetics of levodopa in patients with Parkinson's disease treated with tolcapone.

OBJECTIVE: To use pharmacostatistical models to evaluate the overall exposure of patients with Parkinson's disease to levodopa in the presence and absence of tolcapone. METHODS: Four hundred twelve patients with Parkinson's disease with fluctuating and nonfluctuating responses to levodopa participated in three multicentered, parallel, double-blind, placebo-controlled dose-finding studies and received either placebo or tolcapone in addition to levodopa-decarboxylase inhibitor therapy. Sparse blood samples were obtained from 393 patients for levodopa and 3-O-methyldopa assay, and the data were analyzed with use of the NONMEM program. RESULTS: The fraction of levodopa metabolized to 3-O-methyldopa was substantially reduced by the co-administration of tolcapone (by 65%, 74%, and 84% with tolcapone doses of 50, 200, and 400 mg, respectively, in fluctuators, and by 50% and 90% with doses of 200 and 400 mg, respectively, in nonfluctuators). This led to an overall reduction in levodopa clearance (CL) of approximately 15% to 25% in fluctuators and 20% to 30% in nonfluctuators. Because this was partly compensated for by a reduction in levodopa dose in these studies, the total daily exposure of patients to levodopa was only slightly increased (11% to 16%). The peak-trough fluctuations of plasma levodopa (Cmax-Cmin) were reduced in both populations in a dose-dependent fashion. CONCLUSIONS: Tolcapone effectively inhibited the formation of 3-O-methyldopa and resulted in a decrease in levodopa CL. The consequent increase in levodopa bioavailability was mostly offset by reductions in levodopa dose. It is possible that decreased fluctuations in plasma levodopa concentrations rather than increased levodopa exposure may explain the clinical benefits obtained with tolcapone.

Population pharmacokinetics of tolcapone in parkinsonian patients in dose finding studies.

AIMS: To use pharmacostatistical models to characterize tolcapone's pharmacokinetics in parkinsonian patients, and to identify any demographic subpopulations which may be at risk of either under- or over-exposure to this catechol-O-methyltransferase (COMT) inhibitor. METHODS: Four hundred and twelve patients participated in three multicentre, parallel, double-blind, placebo-controlled, dose-finding studies and received either placebo or tolcapone (50, 200 or 400 mg three times daily) in addition to levodopa/decarboxylase inhibitor therapy. Sparse blood samples were obtained from 275 patients for tolcapone assay and the concentrations (1414 in total) were analysed using the NONMEM program. RESULTS: The pharmacokinetic model which best described the data was a two-compartment open model with first-order absorption and possibly a lag-time. Tolcapone pharmacokinetics were shown to be stable, with no systematic trend between 2 and 6 weeks of treatment. The absorption of the drug was shown to be rapid and concomitant food intake had only a minor effect on the relative bioavailability (10-20% reduction compared with fasting). The overall clearance of tolcapone could be estimated with good precision (approximately 4. 5-5 l h-1 ), and none of the investigated covariates (e.g. sex, age, body weight) had any clinically significant influence on this parameter. The volume of distribution showed relatively high variability and was calculated to be approximately 30 l, leading to an estimated half-life in patients of approximately 5-8 h. CONCLUSIONS: Using sparse concentrations and mixed effect-effects modelling analysis it is possible to describe the pharmacokinetics of tolcapone in parkinsonian populations. The parameter estimates obtained agreed with those obtained from conventional pharmacokinetic studies and no subpopulation was shown to be at risk of either under- or over-exposure to tolcapone.

Relationships between exposure to saquinavir monotherapy and antiviral response in HIV-positive patients.

OBJECTIVE: The aim of this study was to confirm the most appropriate dosage of a new soft gelatin capsule (SGC) formulation of the HIV protease inhibitor saquinavir by investigating the relationships between systemic (plasma) exposure to saquinavir and plasma HIV RNA and CD4+ cell counts using empirical mathematical modelling. DESIGN AND SETTING: A randomised, non-blind, multicentre, dose-ranging 8-week study of monotherapy with 400, 800 or 1200 mg of saquinavir-SGC or 600 mg of the hard gelatin capsule (HGC) formulation, both administered 3 times daily, was carried out in protease inhibitor-naive, HIV-positive adults. Two surrogate markers of response, plasma HIV RNA level and CD4+ cell count, were fitted to 2 measures of systemic drug exposure, the area under the plasma concentration-time curve (AUC) and trough plasma concentration (Cmin), using 6 exposure-response models of progressively increasing complexity. Akaike and Schwarz model selection criteria were applied to determine the most effective pharmacokinetic-pharmacodynamic relationship. RESULTS: A total of 88 patients were randomised; pharmacokinetic and pharmacodynamic data were available for 84 patients. In terms of plasma HIV RNA, pharmacokinetic-pharmacodynamic relationships were best described by a 2-parameter maximum effect (Emax) model, which predicted a typical maximum reduction in viral load of 1.94 log10 copies/ml [coefficient of variation (CV) 12%], with a half-maximal antiviral response occurring at a Cmin of 50 micrograms/L (CV 40%). Saquinavir-SGC 1200 mg administered 3 times daily produced a median AUC to 24 hours (AUC24) of approximately 20,000 micrograms/L.h, corresponding to 85% of the maximum achievable antiviral effect as defined by the model. None of the models yielded a satisfactory fit for CD4+ cell count. CONCLUSION: Empirical mathematical modelling confirmed that, when administered 3 times daily, the optimum dose of saquinavir-SGC is 1200 mg, corresponding to 3600 mg/day.

Exploring clinical study design by computer simulation based on pharmacokinetic/pharmacodynamic modelling.

Computer simulations have been successfully applied in various industries (e.g. automobile, aerospace) to make product development more efficient. Just recently, it was suggested to use simulations in support of clinical drug development for predicting clinical outcomes of planned trials. The methodological basis for this approach is provided by pharmacokinetic and pharmacodynamic mathematical models together with Monte Carlo techniques. In the present paper, the basic notions of clinical trial simulation are introduced and illustrated with the example of an oral anticancer drug. It is shown that computer simulation helps to evaluate consequences of design features on safety and efficacy assessment of the drug which are not easily obtained otherwise. An overview of existing simulation resources with respect to training and software is provided.

An evaluation of the integration of pharmacokinetic and pharmacodynamic principles in clinical drug development. Experience within Hoffmann La Roche.

The integration of pharmacokinetic and pharmacodynamic principles into drug development has been proposed as a way of making it more rational and efficient. The use of these principles in drug development to make scientific and strategic decisions is defined as the 'pharmacokinetic-pharmacodynamic guided approach to drug development'. The objectives of this survey were: (i) to assess the extent the pharmacokinetic-pharmacodynamic guided approach to drug development has been used in a large multinational pharmaceutical company: (ii) to evaluate the impact of pharmacokinetic and/or pharmacodynamic results on clinical drug development; and (iii) to identify factors which prevented the full application of the pharmacokinetic-pharmacodynamic guided approach. This was done by looking at 18 projects in the current development portfolio at Hoffman La Roche and evaluating the use of this approach by interviewing the responsible clinical pharmacologist using a standardised questionnaire. (i) Benefits from using the pharmacokinetic-pharmacodynamic guided approach were reported in every project, independent of development phase and therapeutic area. This approach was more extensively used in the recent projects. The selection of dosages in clinical studies was found to be the most important application of pharmacokinetic-pharmacodynamic results in terms of an impact on drug development. (ii) Time savings, up to several months, could be quantified in 8 projects during the entry-into-man studies and in 6 projects during the phase II or III studies. In 4 projects, 1 clinical study was avoided. (iii) The most important scientific factor preventing the full application of the approach was the lack of knowledge on the predictive value of the pharmacodynamic or surrogate marker for effect (6 projects). The results of the survey have shown that the use of the pharmacokinetic-pharmacodynamic guided approach has contributed to making clinical drug development more rational and more efficient. Opportunities to apply the pharmacokinetic-pharmacodynamic approach should be identified in each project and a project specific strategy for the pharmacokinetic-pharmacodynamic guided approach should be defined during phase 0 of drug development.

Sparse sampling for assessment of drug exposure in toxicological studies.

In support of animal toxicity testing of new drugs, toxicokinetics is designed to assess the systemic exposure of the animals to the drug across dose levels, genders, and periods of the study. In small rodents, repeated sampling may alter the health of the animals and jeopardize the toxicity evaluation. One conventional way to circumvent this limitation is to collect serial samples from satellite animals maintained as the main study animals but not monitored for toxicity. We evaluated, on a real example, whether the exposure could be assessed in the main animals from sparse samples. The only acceptable designs consisted of one single sample per animal repeated on two or three study days. In the rat 13-week oral toxicity study of a new chemical entity, both serial sampling in the satellite animals and sparse sampling in the main animals were applied. Similar measures of exposure and qualitative conclusions were derived from the two groups of animals. The very sparse design applied to the main group yielded adequate estimation of the animal exposure, even with a very simple non-compartmental approach. The population pharmacokinetics analysis of the sparse data with NONMEM provided additional information about drug disposition and the influence of the covariates.

The use of population pharmacokinetics in drug development.

Currently, there is an increasing focus on the implementation of pharmacokinetic-pharmacodynamic (PK-PD) studies and modelling as essential tools for drug development. Strategies involving specifically the population approach, which are based on relatively recent statistical methodology (e.g. nonlinear mixed effects modelling, NONMEM) have been advocated for investigating pharmacokinetic and pharmacodynamic variability as well as dose-concentration-effect relationships. The present article outlines this approach, and discusses how it can be implemented within the framework of the studies currently performed as part of the clinical phases of new drug development. It also considers study design and performance, based on real-life experiences. Population approaches, if designed carefully and early, as part of the planning of the drug development programme, are expected to play a significant role at every phase of the programme and to contribute to providing information that is valuable for registration purposes. Statistical methodology and software are now widely available. However, practical issues such as integration of the population approach within existing protocols, quality control of the data, timing of laboratory and statistical analyses, as well as resource allocation, remain legitimate concerns to be considered in prospective studies.

Practical experience and issues in designing and performing population pharmacokinetic/pharmacodynamic studies.

An expert meeting to discuss issues relating to the design of population pharmacokinetic/pharmacodynamic (PK/PD) studies was held in Brussels in March 1995, under the auspices of the European Co-operation in Science and Technology (COST), Medicine (B1) programme. The purpose of the meeting was to discuss the experts' experience in designing and performing population PK/PD studies. The topics discussed were current practice, logistical issues, ensuring the accuracy of data, covariate assessment, communication, and protocol design.