Role of population pharmacokinetics in drug development. A pharmaceutical industry perspective

Safety of medicines during breastfeeding - from case report to modeling : A contribution from the ConcePTION project

INTRODUCTION

Despite many research efforts, current data on the safety of medicines during breastfeeding are either fragmented or lacking, resulting in restrictive labeling of most medicines. In the absence of pharmacoepidemiologic safety studies, risk estimation for breastfed infants is mainly derived from pharmacokinetic (PK) information on the medicine. This manuscript provides a description and a comparison of the different methodological approaches that can yield reliable information on medicine transfer into human milk and the resulting infant exposure.

AREA COVERED

Currently, most information on medicine transfer in human milk relies on case reports or traditional PK studies, which generate data that can hardly be generalized to the population. Some methodological approaches, such as population PK (popPK) and physiologically-based PK (PBPK) modeling, can be used to provide a more complete characterization of infant medicine exposure through human milk and simulate the most extreme situations, while decreasing the burden of sampling in breastfeeding women.

EXPERT OPINION

PBPK and popPK modeling are promising approaches to fill the gap of knowledge in medicine safety in breastfeeding, as illustrated with our escitalopram example.

Establishment and application of population pharmacokinetics model of vancomycin in infants with meningitis

BACKGROUND

To establish a population pharmacokinetics (PPK) model of vancomycin (VCM) for dose individualization in Chinese infants with meningitis.

METHODS

We collected the data of 82 children with meningitis in hospital from July 2014 to June 2016. The initial vancomycin dosage regimen for children was 10 or 15 mg/kg for q12 h, q8 h or q6 h. Serum concentrations were determined by Viva-E Analyzer before and after the fifth administration. The PPK model was developed by nonlinear mixed-effect model software, assessed by the bootstrap method and then tested in 20 infant patients.

RESULTS

The VCM clearance (CL) was increased by body weight (WT) and decreased by blood urea nitrogen (BUN). Pharmacokinetic parameters of VCM were not influenced by co-administered drugs. The trough concentrations of VCM were accurately predicted by the PPK model, with the prediction errors less than 32%.

CONCLUSION

A new individual strategy for VCM regimens was proposed and validated by the PPK model.

A randomized clinical efficacy study targeting mPGES1 or EP4 in dogs with spontaneous osteoarthritis

Canine studies of spontaneous osteoarthritis (OA) pain add valuable data supporting drug treatment mechanisms that may translate to humans. A multicenter, randomized, double-blind, placebo- and active-controlled study was conducted in client-owned dogs with moderate OA pain to evaluate efficacy of LYA, an inhibitor of microsomal prostaglandin E synthase-1 (mPGES1), an EP4 antagonist (LYB), and carprofen, versus placebo. Of 255 dogs screened, 163 were randomized (placebo/LYA/LYB/carprofen: n = 43/39/42/39) and 158 completed treatment. Efficacy versus placebo was assessed using Bayesian mixed-effect model for repeated measure analyses of the Canine Brief Pain Inventory (CBPI) pain interference score (PIS; primary endpoint), pain severity score, and overall impression, as well as the Liverpool Osteoarthritis in Dogs (LOAD) mobility score. The posterior probability that the difference to placebo was <0 at week 2 was 80% for LYA and 54% for LYB for CBPI PIS (both <95% predefined threshold). For secondary endpoints, the posterior probability that the difference to placebo was <0 at week 2 ranged from 89 to 96% for LYA and from 56 to 89% for LYB. The posterior probabilities comparing carprofen to placebo groups were ≥90% for all efficacy endpoints. The proportion of dogs with one or more adverse event was not significantly different from placebo (32.6%) for LYA (35.9%) or carprofen (25.6%), but the rate for LYB (59.5%) was higher versus placebo (P = 0.017). LYA treatment demonstrated consistent improvement in all efficacy measures, suggesting that inhibition of mPGES1 may be an effective treatment for chronic pain associated with OA.

Assessment of the glomerular filtration rate (GFR) in kidney transplant recipients using Bayesian estimation of the iohexol clearance

Background Plasma iohexol clearance (CLiohexol) is a reference technique for glomerular filtration rate (GFR) determination. In routine practice, CLiohexol is calculated using one of several formulas, which have never been evaluated in kidney transplant recipients. We aimed to model iohexol pharmacokinetics in this population, evaluate the predictive performance of three simplified formulas and evaluate whether a Bayesian algorithm improves CLiohexol estimation. Methods After administration of iohexol, six blood samples were drawn from 151 patients at various time points. The dataset was split into two groups, one to develop the population pharmacokinetic (POPPK) model (n = 103) and the other (n = 48) to estimate the predictive performances of the various GFR estimation methods. GFR reference values (GFRref) in the validation dataset were obtained by non-compartmental pharmacokinetic (PK) analysis. Predictive performances of each method were evaluated in terms of bias (ME), imprecision (root mean square error [RMSE]) and number of predictions out of the ±10% or 15% error interval around the GFRref. Results A two-compartment model best fitted the data. The Bayesian estimator with samples drawn at 30, 120 and 270 min allowed accurate prediction of GFRref (ME = 0.47%, RMSE = 3.42%), as did the Brøchner-Mortensen (BM) formula (ME = - 0.0425%, RMSE = 3.40%). With both methods, none of the CL estimates were outside the ±15% interval and only 2.4% were outside the ±10% for the BM formula (and none for the Bayesian estimator). In patients with GFR ≤30 mL/min/1.73 m2, the BM formula performed very well, while the Bayesian method could not be evaluated in depth due to too small a number of patients with adequate sampling times. Conclusions GFR can be estimated with acceptable accuracy in kidney transplant patients using the BM formula, but also using a Bayesian algorithm.

Antiplatelet Effect of a Pulaimab [Anti-GPIIb/IIIa F(ab)2 Injection] Evaluated by a Population Pharmacokinetic-pharmacodynamic Model

BACKGROUND

Cardiovascular disease has one of the highest mortality rates among all the diseases. Platelets play an important role in the pathogenesis of cardiovascular diseases. Platelet membrane glycoprotein GPIIb/IIIa antagonists are the most effective antiplatelet drugs, and pulaimab is one of these. The study aims to promote individual medication of pulaimab [anti-GPIIb/IIIa F(ab)2 injection] by discovering the pharmacological relationship among the dose, concentration, and effects. The goal of this study is to establish a population pharmacokineticpharmacodynamic model to evaluate the antiplatelet effect of intravenous pulaimab injection.

METHODS

Data were collected from 59 healthy subjects who participated in a Phase-I clinical trial. Plasma concentration was used as the pharmacokinetic index, and platelet aggregation inhibition rate was used as the pharmacodynamic index. The basic pharmacokinetics model was a two-compartment model, whereas the basic pharmacodynamics model was a sigmoid-EMAX model with a direct effect. The covariable model was established by a stepwise method. The final model was verified by a goodness-of-fit method, and predictive performance was assessed by a Bootstrap (BS) method.

RESULTS

In the final model, typical population values of the parameters were as follows: central distribution Volume (V1), 183 L; peripheral distribution Volume (V2), 349 L; Central Clearance (CL), 31 L/h; peripheral clearance(Q), 204 L/h; effect compartment concentration reaching half of the maximum effect (EC50), 0.252 mg/L; maximum effect value (EMAX), 54.0%; and shape factor (γ), 0.42. In the covariable model, thrombin time had significant effects on CL and EMAX. Verification by the goodness-of-fit and BS methods showed that the final model was stable and reliable.

CONCLUSION

A model was successfully established to evaluate the antiplatelet effect of intravenous pulaimab injection that could provide support for the clinical therapeutic regimen.

Bioformulative concepts on intracellular organ specific bioavailability

Bioavailability is an ancient but effective terminology by which the entire therapeutic efficacy of a drug directly or indirectly relays. Despite considering general plasma bioavailability, specific organ/tissue bioavailability will pave the path to broad spectrum dose calculation. Clear knowledge and calculative vision on bioavailability can improve the research and organ-targeting phenomenon. This article comprises a detailed introduction on bioavailability along with regulatory aspects, kinetic data and novel bioformulative approaches to achieve improved organ specific bioavailability, which may not be readily related to blood plasma bioavailability.

Population Pharmacokinetics of Diazoxide in Children with Hyperinsulinemic Hypoglycemia

BACKGROUND

Diazoxide is the first-line treatment for pediatric hyperinsulinemic hypoglycemia (HI). This study aimed to elucidate the pharmacokinetics of diazoxide in children with HI.

METHODS

We obtained 81 blood samples from 22 children with HI. Measured serum diazoxide concentrations were used for population pharmacokinetic analysis. Patient factors influencing pharmacokinetics were estimated using nonlinear mixed-effects model analysis. Relationships between drug exposure and adverse drug reactions were also investigated.

RESULTS

Diazoxide disposition in the body was described by a 1-compartment model. Oral clearance (CL/F) and the volume of distribution were proportional to body weight (WT), as expressed by CL/F in males (liters/h) = 0.0358 + 0.00374 × WT (kg). CL/F in females was 39% greater than that in males. Steady-state concentrations of diazoxide were similar following twice- and 3 times-daily dosing when the total daily doses were comparable. A patient whose serum diazoxide concentration exceeded 100 μg/mL over a 4-month period developed hyperglycemia. No significant correlation was observed between severity of hirsutism and diazoxide concentration.

CONCLUSION

We have proposed for the first time a population pharmacokinetic model for diazoxide in children with HI. The potential risk of diabetes mellitus and/or hyperglycemia increases when serum concentrations of diazoxide exceed 100 μg/mL.

What is the role for population pharmacokinetics in hemophilia?

Prevention of bleeding in hemophilia requires that plasma levels of the deficient factor exceed the desired minimum target level. Large interindividual variability suggests that knowledge of individual pharmacokinetic (PK) would help to achieve this goal, simultaneously minimizing infusion frequency and the amount of concentrate used. Population PK (PopPK) allows for the incorporation of determinants of interpatient variability and eliminates the need for extensive postinfusion plasma sampling. Barriers to implementation of PopPK are the need for concentrate specific models, Bayesian calculation power, specific expertise for validation and appraisal of forecasted estimates. The Web Accessible Population Pharmacokinetic Service – Hemophilia ( www.wapps-hemo.org ), developed by an international research network of hemophilia centers will test if PK-guided dose individualization can improve patient important outcomes in hemophilia.

Tailoring treatment of haemophilia B: accounting for the distribution and clearance of standard and extended half-life FIX concentrates

The prophylactic administration of factor IX (FIX) is considered the most effective treatment for haemophilia B. The inter-individual variability and complexity of the pharmacokinetics (PK) of FIX, and the rarity of the disease have hampered identification of an optimal treatment regimens. The recent introduction of extended half-life recombinant FIX molecules (EHL-rFIX), has prompted a thorough reassessment of the clinical efficacy, PK and pharmacodynamics of plasma-derived and recombinant FIX. First, using longer sampling times and multi-compartmental PK models has led to more precise (and favourable) PK for FIX than was appreciated in the past. Second, investigating the distribution of FIX in the body beyond the vascular space (which is implied by its complex kinetics) has opened a new research field on the role for extravascular FIX. Third, measuring plasma levels of EHL-rFIX has shown that different aPTT reagents have different accuracy in measuring different FIX molecules. How will this new knowledge reflect on clinical practice? Clinical decision making in haemophilia B requires some caution and expertise. First, comparisons between different FIX molecules must be assessed taking into consideration the comparability of the populations studied and the PK models used. Second, individual PK estimates must rely on multi-compartmental models, and would benefit from adopting a population PK approach. Optimal sampling times need to be adapted to the prolonged half-life of the new EHL FIX products. Finally, costs considerations may apply, which is beyond the scope of this manuscript but might be deeply connected with the PK considerations discussed in this communication.

Data Analysis Protocol for the Development and Evaluation of Population Pharmacokinetic Models for Incorporation Into the Web-Accessible Population Pharmacokinetic Service - Hemophilia (WAPPS-Hemo)

BACKGROUND

Hemophilia is an inherited bleeding disorder caused by a deficiency in a specific clotting factor. This results in spontaneous bleeding episodes and eventual arthropathy. The mainstay of hemophilia treatment is prophylactic replacement of the missing factor, but an optimal regimen remains to be determined. Rather, individualized prophylaxis has been suggested to improve both patient safety and resource utilization. However, uptake of this approach has been hampered by the demanding sampling schedules and complex calculations required to obtain individual estimates of pharmacokinetic (PK) parameters. The use of population pharmacokinetics (PopPK) can alleviate this burden by reducing the number of plasma samples required for accurate estimation, but few tools incorporating this approach are readily available to clinicians.

OBJECTIVE

The Web-accessible Population Pharmacokinetic Service - Hemophilia (WAPPS-Hemo) project aims to bridge this gap by providing a Web-accessible service for the reliable estimation of individual PK parameters from only a few patient samples. This service is predicated on the development of validated brand-specific PopPK models.

METHODS

We describe the data analysis plan for the development and evaluation of each PopPK model to be incorporated into the WAPPS-Hemo platform. The data sources and structure of the dataset are discussed first, followed by the procedures for handling both data below limit of quantification (BLQ) and absence of such BLQ data. Next, we outline the strategies for building the appropriate structural and covariate models, including the possible need for a process algorithm when PK behavior varies between subjects or significant covariates are not provided. Prior to use in a prospective manner, the models will undergo extensive evaluation using a variety of techniques such as diagnostic plots, bootstrap analysis and cross-validation. Finally, we describe the incorporation of a validated PopPK model into the Bayesian post hoc model to produce individualized estimates of PK parameters.

RESULTS

Dense PK data has been collected for more than 20 brands of factor concentrate from both industry-sponsored and investigator-driven studies. The model development process is underway for the majority of molecules, with refinement and validation to be completed in 2017. Further, the WAPPS-Hemo co-investigator network has contributed more than 300 PK assessments for use in model development and evaluation. This constitutes the largest repository of this type of PK data globally.

CONCLUSIONS

The WAPPS-Hemo service aims to eliminate barriers to the uptake of individualized PK-tailored hemophilia treatment. By incorporating this tool into routine practice, clinicians can implement a personalized dosing strategy without performing rigorous sampling or complex calculations. This service is centred on validated models developed according to the robust approach to PopPK modeling described herein.

CLINICALTRIAL

ClinicalTrials.gov NCT02061072; https://clinicaltrials.gov/ct2/show/NCT02061072 (Archived by WebCite at http://www.webcitation.org/6mRIXJh55).

The use of pharmacokinetics in dose individualization of factor VIII in the treatment of hemophilia A

INTRODUCTION

Hemophilia A is a bleeding disorder resulting from a lack of clotting factor VIII (FVIII), and treatment typically consists of prophylactic replacement of the deficient factor. However, high between subject variability precludes the development of a 'one size fits all' dosing strategy and necessitates an individualized approach. We sought to summarize the data on the pharmacokinetics of FVIII available as a basis for the development of population pharmacokinetic models to be used in dose tailoring. Areas covered: We reviewed the pharmacokinetics of FVIII as used for the treatment of hemophilia A, with a focus on the variability observed between patients and the application of pharmacokinetic methods to dose individualization. We also explored the covariates affecting pharmacokinetic parameters, the differences between plasma-derived and recombinant FVIII and the development of extended half-life products. Expert opinion: The pharmacokinetics of factor VIII in patients with hemophilia shows a high interpatient variability, and is affected by age, weight, level of von Willebrand factor, and blood group. A population approach to estimating individual pharmacokinetics is likely to provide the most successful strategy to tailor factor concentrate dosing to the individual needs and to ensure optimal patient outcomes, while also improving the cost-effectiveness of prophylactic replacement therapy.

The influence of personality on the sensitivity to subjective effects of Δ9-tetrahydrocannabinol

The effects of drugs are not only determined by their pharmacological action, but also by user characteristics. This analysis explored the influence of personality on the differences in subjective effects in response to a standardized pharmacological challenge with the cannabinoid CB1/CB2 partial agonist Δ9-tetrahydrocannabinol (THC). To express the sensitivity to THC, pharmacokinetic–pharmacodynamic (PK–PD) non-linear mixed effects modelling was applied to the subjective response of 184 healthy subjects to a pharmacological challenge with inhalation of THC. The subjective effects were measured using visual analogue scales and described by three clusters: ‘perception’, ‘relaxation’ and ‘dysphoria’. The sensitivity for THC (described as EC50) was related to scores on Cloninger׳s temperament and character inventory (TCI) using multiple linear regression. Effect compartment models were used to describe the PK–PD relations of THC. Within the multivariate model, ‘harm avoidance’ was significantly correlated with changes in ‘perception’, and ‘self-transcendence’ with changes in ‘dysphoria’. Within the psychobiological model of personality, ‘harm avoidance’ is related to serotonergic systems. Subjects with either very low (easy-going) or very high (cautious) scores were less sensitive to THC-induced changes in ‘perception’. ‘Self-transcendence’ relates to schizotypy. Subjects with more schizotypy were more sensitive to the dysphoric subjective effects of THC.

Population pharmacokinetics of imatinib in Iranian patients with chronic-phase chronic myeloid leukemia

PURPOSE

We evaluated the population pharmacokinetics (PPK) and exposure-response relationship of imatinib mesylate in Iranian patients with chronic myeloid leukemia (CML).This study was designed to assess steady state (SS) imatinib trough concentrations (Cmin) and pharmacokinetics parameters of imatinib in patients with CML in chronic phase after at least 12-month treatment.

METHODS

Plasma concentrations from a randomized controlled trial consist of 61 patients who received oral imatinib at doses ranged between 300 and 800 mg in various dosing interval, which were quantified using a validated reversed-phase high-performance liquid chromatographic method with UV detection method on different occasions at SS and evaluated using PPK model.

RESULTS

A one-compartment model with zero-order absorption and a lag time was sufficient in describing the concentration-time profile. Inter-individual variability (IIV) was modeled for all parameters. Oral clearance (CL/F) and the volume of distribution (V/F) were estimated to 10.8 L/h with 30 % IIV and 265 L with 53 % IIV, respectively. Inter-occasion variability (IOV) was included in CL/F (17 %) and V/F (22 %).The proportional residual error of the model was 8 %.

CONCLUSIONS

Simulation analysis from individual parameters shows exposure to imatinib is highly variable among patients. Imatinib trough plasma levels <1,257 ng/mL were associated with lower rates of major molecular response. Because of the wide IIV compared with IOV with imatinib in our study, trough levels may play a role in investigating instances of suboptimal response.

Individual and population pharmacokinetic compartment analysis: a graphic procedure for quantification of predictive performance

Objectives

Pharmacokinetic studies are important for optimizing of drug dosing, but requires proper validation of the used pharmacokinetic procedures. However, simple and reliable statistical methods suitable for evaluation of the predictive performance of pharmacokinetic analysis are essentially lacking. The aim of the present study was to construct and evaluate a graphic procedure for quantification of predictive performance of individual and population pharmacokinetic compartment analysis.

Methods

Original data from previously published pharmacokinetic compartment analyses after intravenous, oral, and epidural administration, and digitized data, obtained from published scatter plots of observed vs predicted drug concentrations from population pharmacokinetic studies using the NPEM algorithm and NONMEM computer program and Bayesian forecasting procedures, were used for estimating the predictive performance according to the proposed graphical method and by the method of Sheiner and Beal.

Results

The graphical plot proposed in the present paper proved to be a useful tool for evaluation of predictive performance of both individual and population compartment pharmacokinetic analysis.

Conclusion

The proposed method is simple to use and gives valuable information concerning time- and concentration-dependent inaccuracies that might occur in individual and population pharmacokinetic compartment analysis. Predictive performance can be quantified by the fraction of concentration ratios within arbitrarily specified ranges, e.g. within the range 0.8–1.2.

PKgraph: an R package for graphically diagnosing population pharmacokinetic models

Population pharmacokinetic (PopPK) modeling has become increasing important in drug development because it handles unbalanced design, sparse data and the study of individual variation. However, the increased complexity of the model makes it more of a challenge to diagnose the fit. Graphics can play an important and unique role in PopPK model diagnostics. The software described in this paper, PKgraph, provides a graphical user interface for PopPK model diagnosis. It also provides an integrated and comprehensive platform for the analysis of pharmacokinetic data including exploratory data analysis, goodness of model fit, model validation and model comparison. Results from a variety of modeling fitting software, including NONMEM, Monolix, SAS and R, can be used. PKgraph is programmed in R, and uses the R packages lattice, ggplot2 for static graphics, and rggobi for interactive graphics.

PKreport: report generation for checking population pharmacokinetic model assumptions

BACKGROUND

Graphics play an important and unique role in population pharmacokinetic (PopPK) model building by exploring hidden structure among data before modeling, evaluating model fit, and validating results after modeling.

RESULTS

The work described in this paper is about a new R package called PKreport, which is able to generate a collection of plots and statistics for testing model assumptions, visualizing data and diagnosing models. The metric system is utilized as the currency for communicating between data sets and the package to generate special-purpose plots. It provides ways to match output from diverse software such as NONMEM, Monolix, R nlme package, etc. The package is implemented with S4 class hierarchy, and offers an efficient way to access the output from NONMEM 7. The final reports take advantage of the web browser as user interface to manage and visualize plots.

CONCLUSIONS

PKreport provides 1) a flexible and efficient R class to store and retrieve NONMEM 7 output, 2) automate plots for users to visualize data and models, 3) automatically generated R scripts that are used to create the plots; 4) an archive-oriented management tool for users to store, retrieve and modify figures, 5) high-quality graphs based on the R packages, lattice and ggplot2. The general architecture, running environment and statistical methods can be readily extended with R class hierarchy. PKreport is free to download at http://cran.r-project.org/web/packages/PKreport/index.html.

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.

Recent advances in pharmacokinetic modeling

A major part of the science of pharmacokinetics is the modeling of the underlying processes that contribute to drug disposition. The purpose of pharmacokinetic models is to summarize the knowledge gained in preclinical and clinical studies at various stages in drug development and to rationally guide future studies with the use of adequately predictive models. This review highlights a variety of recent advances in mechanistic pharmacokinetic modeling. It is aimed at a broad audience, and hence, an attempt was made to maintain a balance between technical information and practical applications of pharmacokinetic modeling. It is hoped that drug researchers from all disciplines would be able to get a flavor of the function and capacity of pharmacokinetic modelers and their contribution to drug development. While this review is not intended to be a technical reference on modeling approaches, the roles of statistical applications and population methodologies are discussed where appropriate.

A comparison of nonlinear mixed-model analyses for a pediatric pharmacokinetic study

Nonlinear mixed models are important tools for analyzing repeated measures data. In particular, these models are used for population pharmacokinetic analyses for estimating population pharmacokinetic parameters. As more clinical studies are performed for the advancement of treatment of pediatric patients, methodology is needed for comparing results from pharmacokinetic studies in pediatric patients and adult control groups. These pediatric studies introduce complexities to the design and analysis, including how analysis of sparse data affects the limitations of model selection. A case study is presented demonstrating that good communication with regulatory agencies and appropriate selection of analysis models are integral parts of completing population analyses for timely approval and labeling of drugs for treating pediatric patients.

Pharmacokinetic/pharmacodynamic relationships of antimicrobial drugs used in veterinary medicine

The rise in incidence of antimicrobial resistance, consumer demands and improved understanding of antimicrobial action has encouraged international agencies to review the use of antimicrobial drugs. More detailed understanding of relationships between the pharmacokinetics (PK) of antimicrobial drugs in target animal species and their action on target pathogens [pharmacodynamics (PD)] has led to greater sophistication in design of dosage schedules which improve the activity and reduce the selection pressure for resistance in antimicrobial therapy. This, in turn, may be informative in the pharmaceutical development of antimicrobial drugs and in their selection and clinical utility. PK/PD relationships between area under the concentration time curve from zero to 24 h (AUC(0-24)) and minimum inhibitory concentration (MIC), maximum plasma concentration (C(max)) and MIC and time during which plasma concentrations exceed the MIC have been particularly useful in optimizing efficacy and minimizing resistance. Antimicrobial drugs have been classified as concentration-dependent where increasing concentrations at the locus of infection improve bacterial kill, or time-dependent where exceeding the MIC for a prolonged percentage of the inter-dosing interval correlates with improved efficacy. For the latter group increasing the absolute concentration obtained above a threshold does not improve efficacy. The PK/PD relationship for each group of antimicrobial drugs is 'bug and drug' specific, although ratios of 125 for AUC(0-24):MIC and 10 for C(max):MIC have been recommended to achieve high efficacy for concentration-dependent antimicrobial drugs, and exceeding MIC by 1-5 multiples for between 40 and 100% of the inter-dosing interval is appropriate for most time-dependent agents. Fluoroquinolones, aminoglycosides and metronidazole are concentration-dependent and beta-lactams, macrolides, lincosamides and glycopeptides are time-dependent. For drugs of other classes there is limited and conflicting information on their classification. Resistance selection may be reduced for concentration-dependent antimicrobials by achieving an AUC(0-24):MIC ratio of greater than 100 or a C(max):MIC ratio of greater than 8. The relationships between time greater than MIC and resistance selection for time-dependent antimicrobials have not been well characterized.

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 Pharmacokinetics I: Background, Concepts, and Models

OBJECTIVE

To present and emphasize the background, foundations, utility, and conceptual underlying theory of the population pharmacokinetic (PPK) approach with an examination of the advantages when compared with other approaches of pharmacokinetic modeling.

DATA SOURCES

Information on PPK was retrieved from a MEDLINE search (1979—June 2002) of literature and a bibliographic review of review articles and books.

STUDY SELECTION AND DATA EXTRACTION

All articles identified from data sources were evaluated and relevant information was included in this review.

DATA SYNTHESIS

PPK plays a pivotal role in developing dosing strategies for direct patient care and in drug development. PPK is valuable because it targets the patient group that will eventually receive the drug of interest, quantitates pharmacokinetic variability at several levels, and seeks to explain those sources of variability.

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 development.

Plasma and Cerebrospinal Fluid Population Pharmacokinetics of Temozolomide in Malignant Glioma Patients

PURPOSE

Scarce information is available on the brain penetration of temozolomide (TMZ), although this novel methylating agent is mainly used for the treatment of malignant brain tumors. The purpose was to assess TMZ pharmacokinetics in plasma and cerebrospinal fluid (CSF) along with its inter-individual variability, to characterize covariates and to explore relationships between systemic or cerebral drug exposure and clinical outcomes.

EXPERIMENTAL DESIGN

TMZ levels were measured by high-performance liquid chromatography in plasma and CSF samples from 35 patients with newly diagnosed or recurrent malignant gliomas. The population pharmacokinetic analysis was performed with nonlinear mixed-effect modeling software. Drug exposure, defined by the area under the concentration-time curve (AUC) in plasma and CSF, was estimated for each patient and correlated with toxicity, survival, and progression-free survival.

RESULTS

A three-compartment model with first-order absorption and transfer rates between plasma and CSF described the data appropriately. Oral clearance was 10 liter/h; volume of distribution (V(D)), 30.3 liters; absorption constant rate, 5.8 h(-1); elimination half-time, 2.1 h; transfer rate from plasma to CSF (K(plasma-->CSF)), 7.2 x 10(-4)h(-1) and the backwards rate, 0.76 h(-1). Body surface area significantly influenced both clearance and V(D), and clearance was sex dependent. The AUC(CSF) corresponded to 20% of the AUC(plasma). A trend toward an increased K(plasma-->CSF) of 15% was observed in case of concomitant radiochemotherapy. No significant correlations between AUC in plasma or CSF and toxicity, survival, or progression-free survival were apparent after deduction of dose-effect.

CONCLUSIONS

This is the first human pharmacokinetic study on TMZ to quantify CSF penetration. The AUC(CSF)/AUC(plasma) ratio was 20%. Systemic or cerebral exposures are not better predictors than the cumulative dose alone for both efficacy and safety.

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.

Application of resampling techniques to estimate exact significance levels for covariate selection during nonlinear mixed effects model building: some inferences

PURPOSE

One of the main objectives of the nonlinear mixed effects modeling is to provide rational individualized dosing strategies by explaining the interindividual variability using intrinsic and/or extrinsic factors (covariates). The aim of the current study was to evaluate, using computer simulations and real data, methods for estimating the exact significance level for including or excluding a covariate during model building.

METHODS

Original data were simulated using a simple one-compartment pharmacokinetic model with (full model) or without (null model) covariates (one or two). The covariate values in the original data were resampled (using either permutations or parametric bootstrap methods) to generate data under the null hypothesis that there is no covariate effect. The original and permuted data were fitted to null and full models, using first-order and first-order condition estimation (with or without interaction) methods in NONMEM, to compare the asymptotic and conditional p-value. Target log-likelihood ratio cutoffs for assessing covariate effects were derived.

RESULTS

The simulations showed that for sparse as well as dense data, the first-order condition estimation methods yielded the best results while the first-order method performs somewhat better for sparse data. Depending on the modeling objective, the appropriate asymptotic p-value can be substituted for the conditional significance level. Target log-likelihood ratio cutoffs should be determined separately for each covariate when exact p-values are important.

CONCLUSIONS

Resampling methods can be employed to estimate the exact significance level for including a covariate during nonlinear mixed effects model building. Some reasonable inferences can be drawn for potential application to design future population analyses.

Montelukast dose selection in children ages 2 to 5 years: comparison of population pharmacokinetics between children and adults

Montelukast, a leukotriene receptor antagonist, has demonstrated efficacy and tolerability in the treatment of asthma in patients age 6 years and older. The purpose of this open, one-period, multicenter population pharmacokinetic study was to identify a chewable tablet (CT) dose of montelukast for administration to children ages 2 to 5 years with asthma, yielding a single-dose pharmacokinetic profile (area under the plasma concentration-time curve [AUC]) comparable to that of the 10 mg film-coated tablet (FCT) dose in adults. Because patient numbers were small and the volume of blood that could be collected from individual 2- to 5-year-old patients was limited, a population pharmacokinetic approach was used to estimate population AUC (AUCpop). The 4 mg CT dose of montelukast was well tolerated and yielded an AUCpop (2721 ng.h/mL) similar to that of the adult AUCpop (2595 ng.h/mL) observed after a 10 mg FCT dose. These results support the selection of a 4 mg once-daily CT dose of montelukast for future efficacy and safety studies in children ages 2 to 5 years with asthma.

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.

Pharmacokinetic studies of neuromuscular blocking agents: good clinical research practice (GCRP)

In September 1997, an international consensus conference on standardization of studies of neuromuscular blocking agents was held in Copenhagen, Denmark. Based on the conference, a set of guidelines for good clinical research practice (GCRP) in pharmacokinetic studies of neuromuscular blocking agents is presented. Guidelines include: design of the study; relevant patient groups to investigate; test drug administration, sampling and analysis; pharmacokinetic analysis; pharmacokinetic/pharmacodynamic modeling; population pharmacokinetics; statistics; and presentation of pharmacokinetic data. The guidelines are intended to aid those working in this research area; it is hoped that they will assist researchers, editors of scientific papers, and pharmaceutical companies in improving the quality of pharmacokinetic studies.

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.

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.

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.

Population pharmacokinetics in phase I drug development: a phase I study of PK1 in patients with solid tumours

Doxorubicin pharmacokinetics were determined in 33 patients with solid tumours who received intravenous doses of 20-320 mg m(-2) HPMA copolymer bound doxorubicin (PK1) in a phase I study. Since assay constraints limited the data at lower doses, conventional analysis was not feasible and a 'population approach' was used. Bound concentrations were best described by a biexponential model and further analyses revealed a small influence of dose or weight on V1 but no identifiable effects of age, body surface area, renal or hepatic function. The final model was: clearance (Q) 0.194 I h(-1); central compartment volume (V1) 4.48 x (1+0.00074 x dose (mg)) I; peripheral compartment volume (V2) 7.94 I; intercompartmental clearance 0.685 I h(-1). Distribution and elimination half-lives had median estimates of 2.7 h and 49 h respectively. Free doxorubicin was present at most sampling times with concentrations around 1000 times lower than bound doxorubicin values. Data were best described using a biexponential model and the following parameters were estimated: apparent clearance 180 I h-(-1); apparent V1 (I) 1450 x (1+0.0013 x dose (mg)), apparent V2 (I) 21 300 x (1-0.0013 x dose (mg)) x (1+2.95 x height (m)) and apparent Q 6950 I h(-1). Distribution and elimination half-lives were 0.13 h and 85 h respectively.

Population pharmacokinetics of methylphenidate in children with attention-deficit hyperactivity disorder

Sources of individual variation in plasma methylphenidate (MP) concentrations during usual clinical use are not established. This was evaluated in a series of patients receiving clinical treatment with MP. A single plasma MP concentration was determined in each of 273 children and adolescents ages 5 to 18 years (mean: 11.1 years) who were clinically good responders to MP for the treatment of attention-deficit hyperactivity disorder. MP was given on a twice-daily schedule (mean dose: 25 mg/day) in 40% of patients and three times daily (mean dose: 39.3 mg/day) in 60%. A nonlinear regression model was applied to estimate overall population values of MP clearance and elimination half-life (t1/2), assuming a one-component model with first-order absorption and elimination, and further assuming that clearance is linearly related to body weight. The model incorporated each patient's dosage size and schedule, body weight, and time of the plasma sample. Iterated solutions of best fit were: t1/2, 4.5 hours (95% confidence interval [CI]: 3.1-8.1 hours), and apparent clearance, 90.7 ml/min/kg (95% CI: 74.6-106.7 ml/min/kg). The model explained 43% of the overall variance in MP concentrations (r2 = 0.43, p < .001). In a small subsample (N = 16), a second plasma sample was drawn at the same time of day and at the same dose; the correlation between the two concentration values was 0.83. The relatively noninvasive approach used in this study allows the assessment of pharmacokinetic properties of medications under conditions of appropriate clinical use in special populations such as children, adolescents, and the elderly.

Population pharmacokinetics of amikacin in patients with haematological malignancies

The aim of this study was to analyse the pharmacokinetic behaviour of amikacin in patients with haematological malignancies using a mixed-effect model and sparse data collected during routine clinical care. The patient population comprised 207 haematology patients divided into two groups: one for computing the population model (n = 134) and the other for validation (n = 73). A one-compartment model was used and the following covariates were tested for their influence on clearance and volume of distribution: age, gender, weight, parenteral nutrition, creatinine clearance, stage of antineoplastic treatment (induction, consolidation, intensification), number of weeks postchemotherapy, clinical diagnosis, Eastern Cooperative Oncology Group score, neutropenia, hypoalbuminaemia, concomitant medication (vancomycin and/or amphotericin B), overhydration, and autologous or allogenic bone marrow transplant. The nonlinear mixed-effect model (NONMEM) was used to assess the population pharmacokinetic model of amikacin in these patients. Apart from bodyweight and renal function, acute myeloblastic leukaemia and hypoalbuminaemia proved to be the most important covariates explaining the interindividual variability in amikacin pharmacokinetics in patients with haematological malignancies. The predictive performance of this population model for amikacin serum concentrations seems suitable for clinical purposes.

Desipramine clearance in children and adolescents: absence of effect of development and gender

OBJECTIVE

To examine the influence of development and gender on the pharmacokinetics of desipramine (DMI) in the pediatric population.

METHOD

DMI pharmacokinetic parameters were calculated from 407 routinely drawn, dose- and weight-normalized serum concentrations in 173 youths receiving DMI (90 children, 83 adolescents; 29 were female, 144 were male).

RESULTS

Mean pharmacokinetic parameters for the entire population included dose (3.78 +/- 1.51 mg/kg), weight- and dose-normalized serum concentration (45.41 +/- 47.39 [micrograms/L]/[mg/kg]), and DMI clearance (0.68 +/- 1.51 [L/kg]/hr). No between-group differences for children and adolescents were detected in dose (child, adolescent) (3.73 +/- 1.40 mg/kg, 3.83 +/- 1.68 mg/kg), weight- and dose-normalized serum concentrations (44.52 +/- 39.6 [micrograms/L]/[mg/kg], 46.34 +/- 34.89 [micrograms/L]/[mg/kg]; p = .62), and clearance (0.680 +/- 0.890 [L/kg]/hr, 0.695 +/- 1.05 [L/kg]/hr; p = .103). No between-group gender differences were detected in dose (male, female) (3.83 +/- 1.55 mg, 3.39 +/- 1.84 mg), weight- and dose-normalized serum concentrations (45.15 +/- 37.76 [micrograms/L]/[mg/kg], 47.14 +/- 34.96 [micrograms/L]/mg/kg]; p = .720), and clearance (0.699 +/- 0.89 [L/kg]/hr, 0.606 +/- 0.535 [L/kg]/hr; p = .390).

CONCLUSIONS

These results suggest that age and gender do not significantly influence DMI clearance or dose-normalized serum concentrations in the pediatric population.

The application of population pharmacokinetics to the drug development process

Population pharmacokinetics is playing an increasing role in clinical drug development. An overview of the population approach, including software and the advantages and limitations of the approach compared to the traditional approach to pharmacokinetic studies, is given. This paper also documents how the area has evolved over the past 15 years and addresses some of the issues that have arisen over the design and conduct of population studies. Finally, some alternative applications of the population approach are given for areas other than clinical drug development.

Expanding clinical applications of population pharmacodynamic modelling

Population pharmacokinetics or pharmacodynamics is the study of the variability in drug concentration or pharmacological effect between individuals when standard dosage regimens are administered. We provide an overview of pharmacokinetic models, pharmacodynamic models, population models and residual error models. We outline how population modelling approaches seek to explain interpatient variability with covariate analysis, and, in some approaches, to characterize the unexplained interindividual variability. The interpretation of the results of population modelling approaches is facilitated by shifting the emphasis from the perspective of the modeller to the perspective of the clinician. Both the explained and unexplained interpatient variability should be presented in terms of their impact on the dose-response relationship. Clinically relevant questions relating to the explained and unexplained variability in the population can be posed to the model, and confidence intervals can be obtained for the fraction of the population that is estimated to fall within a specific therapeutic range given a certain dosing regimen. Such forecasting can be used to develop optimal initial dosing guidelines. The development of population models (with random effects) permits the application of Bayes's formula to obtain improved estimates of an individual's pharmacokinetic and pharmacodynamic parameters in the light of observed responses. An important challenge to clinical pharmacology is to identify the drugs that might benefit from such adaptive-control-with-feedback dosing strategies. Drugs used for life threatening diseases with a proven pharmacokinetic-pharmacodynamic relationship, a small therapeutic range, large interindividual variability, small interoccasion variability and severe adverse effects are likely to be good candidates. Rapidly evolving changes in health care economics and consumer expectations make it unlikely that traditional drug development approaches will succeed in the future. A shift away from the narrow focus on rejecting the null hypothesis towards a broader focus on seeking to understand the factors that influence the dose-response relationship--together with the development of the next generation of software based on population models--should permit a more efficient and rational drug development programme.

Population analysis of the pharmacokinetics of tiagabine in patients with epilepsy

PURPOSE

In two open-label long-term safety studies, we determined tiagabine (TGB) pharmacokinetics in patients with epilepsy.

METHODS

In all, 2,147 plasma samples from 511 patients who participated in the studies were available. The total daily dose ranged from 2 mg administered once daily to 80 mg administered in four doses. A one-compartment model with first-order absorption and elimination was used to fit the TGB plasma concentration-time data, with a population pharmacokinetic approach.

RESULTS

The patients' average (+/-SD) weight and age were 73.8+/-20.7 kg and 32.1+/-12.3 years. The most significantly factor affecting TGB pharmacokinetics was concomitant administration of other antiepileptic drugs (AEDs). The central clearance value in patients receiving AEDs known to induce hepatic drug metabolism was 21.4 L/h, a value 67% higher than the central clearance estimate obtained for the patients receiving AEDs not known to affect hepatic drug metabolism (12.8 L/h). There was no evidence of any dose or time effect, indicating that TGB pharmacokinetics are linear. TGB pharmacokinetics were not different in white, black, or Hispanic patients, although our ability to explore racial effects was limited since 90% of the patients were white. No other demographic variables (including age and smoking) or any clinical chemistry measurements (including bilirubin, SGOT, and SGPT) were important in explaining the variability in the clearance estimates.

CONCLUSIONS

TGB pharmacokinetics are linear, influenced by enzyme-inducing AEDs, and largely unaffected by other demographic variables.

Population analysis of the pharmacokinetics and pharmacodynamics of seratrodast in patients with mild to moderate asthma

BACKGROUND

Seratrodast, a potent thromboxane receptor antagonist, is approved in Japan for the treatment of asthma and currently is being developed in the United States.

METHODS

This was a phase II, randomized, double-blind, parallel-group, placebo-controlled 15-center study of seratrodast in patients with mild to moderate asthma. A total of 183 patients were randomly assigned to receive daily doses of either placebo, or 80 mg seratrodast, or 120 mg seratrodast for 8 weeks. Pharmacokinetic and pharmacodynamic modeling was carried out by means of the population approach. A two-compartment model with zero-order input and first-order elimination best fitted the plasma concentration-time data.

RESULTS AND CONCLUSIONS

The pharmacokinetics of seratrodast were linear after single and multiple dosing for 8 weeks. The population estimates for oral clearance and apparent volume of distribution were 8.5 ml/hr/kg and 43.3 ml/kg, respectively. All pharmacokinetic parameters (the oral central compartment clearance, the volumes of distribution of the central and peripheral compartments, and the intercompartmental clearance) were estimated with a precision of 10% or less and were found to be associated with body weight. The residual variability was 30%. The values of oral clearance estimated in this study in male patients were similar to those previously estimated in healthy male subjects. Seratrodast at a dose of 120 mg daily produced an increase in forced expiratory volume in 1 second (FEV1) from baseline that was linearly correlated with its plasma concentrations. The average slope of the concentration-effect relationship was 0.222% and 0.470% per microgram/ml after single and multiple dosing, respectively. Interpatient variability in response was mainly affected by the initial severity of the disease. A lower percentage of predicted FEV1 (i.e., more severe obstruction) was associated with higher slopes, and greater increases in FEV1.