Pediatric dosing is not only critical for successful pediatric trials in drug development but also paramount to safety and effective treatment at bedside. Due to the complex pharmacokinetic of children compared to adults, several challenges are posed in managing dosing precisely during drug development and after drug approval to clinicians. In particular, given the real-world practice, understanding the impact of development on the dose-exposure-response relationship is essential in optimizing the dosing to children of different ages. In this paper we propose a novel intelligent computing framework to examine how the growth and maturation create size- and age-dependent variability in pharmacokinetics and pharmacodynamics, and summarize the use of modeling-based approaches for dose finding in pediatric drug development, allowing clinicians to anticipate probable treatment effects and to have a higher likelihood of achieving optimal dose regimens early, as well as reducing the drug development cycling time and cost.

1.

Information on drug absorption and disposition in infants and children has increased considerably over the past 2 decades. However, the impact of specific age-related effects on pharmacokinetics, pharmacodynamics, and dose requirements remains poorly understood. Absorption can be affected by the differences in gastric pH and stomach emptying time that have been observed in the pediatric population. Low plasma protein concentrations and a higher body water composition can change drug distribution. Metabolic processes are often immature at birth, which can lead to a reduced clearance and a prolonged half-life for those drugs for which metabolism is a significant mechanism for elimination. Renal excretion is also reduced in neonates due to immature glomerular filtration, tubular secretion, and reabsorption. Limited data are available on the pharmacodynamic behavior of drugs in the pediatric population. Understanding these age effects provide a mechanistic way to identify initial doses for the pediatric population. The various factors that impact pharmacokinetics and pharmacodynamics mature towards adult values at different rates, thus requiring continual modification of drug dose regimens in neonates, infants, and children. In this paper, the age-related changes in drug absorption, distribution, metabolism, and elimination in infants and children are reviewed, and the age-related dosing regimens for this population are discussed.

Atorvastatin lactone, a metabolite of the HMG-CoA reductase inhibitor (statin) atorvastatin acid, is believed to be myotoxic. Our objectives were to develop a population pharmacokinetic model for atorvastatin acid and its lactone metabolite and to identify patient characteristics that are predictive of variability in the pharmacokinetic parameters of the parent drug and its lactone metabolite.

The population pharmacokinetics of mycophenolic acid (MPA) and its phenolic (MPAG) and acyl (AcMPAG) glucuronide metabolites were studied in patients taking enteric-coated mycophenolate sodium. Plasma samples (n = 232), obtained from 18 renal transplant recipients, were analyzed for MPA, MPAG, and AcMPAG using a validated high-performance liquid chromatography/ultraviolet assay. Population pharmacokinetic analysis was performed using NONMEM. The pharmacokinetics of MPA were best described by a 2-compartment model, with MPAG and AcMPAG produced from the central compartment and with enterohepatic recirculation of MPA via these 2 metabolites. Population mean estimates for MPA were apparent clearance (CL/F) of 10.6 L/h (interindividual variability [IIV] = 21.4%) and apparent volume of distribution of the central compartment (V(1)/F) of 25.9 L (IIV = 87.8%). Mean elimination rate constants of MPAG and AcMPAG were 0.323 h(-1) (IIV = 29.1%) and 0.206 h(-1) (IIV = 48.8%), respectively. The mean fraction of MPA converted to MPAG and AcMPAG, normalized by their volumes of distribution (FM(AG) and FM(AC), respectively), was also estimated. The elimination rate constant for MPAG and FM(AC) was influenced by glomerular filtration rate in patients with renal impairment. The visual predictive check, based on 100 simulated data sets each for MPA, MPAG, and AcMPAG, found that the final pharmacokinetic model adequately predicts the observed concentrations of all 3 species.

AIMS To study the population pharmacokinetics (PK) of MPA and its phenolic (MPAG) and acyl (AcMPAG) glucuronide metabolites in patients taking oral doses of mycophenolate mofetil (MMF)(1–2 g day−1). METHODS An average of 12 plasma samples per patient were obtained from 24 renal transplant recipients during a 12-hour steady state dosing interval (305 samples in total) and were analyzed for MPA, MPAG and AcMPAG using HPLC. PK analysis was performed using nonlinear mixed effect modeling (NONMEM). Interindividual variability (IIV) and residual variability in the PK were estimated. RESULTS A 2-compartment PK model was found to best fit the MPA data while a 1-compartment model was most suitable for MPAG and AcMPAG. Population mean estimates for MPA were: apparent clearance (CL/F) 5.68 L/hr (IIV=55.2%) and apparent volume of distribution (V/F) 51.1 L (IIV=133%). Population mean fraction of MPA converted to AcMPAG and MPAG normalized by the volume of distribution of the respective metabolites were 0.0265 L−1 and 0.9735 L−1, respectively. Population mean elimination rate constants of AcMPAG and MPAG were 0.531hr−1(IIV=39.9%) and 0.664 hr−1(IIV=42.3%), respectively. CONCLUSIONS A model describing the population PK of MPA, MPAG and AcMPAG was developed, which may be useful for predicting the time course of MPA and its metabolites after the administration of MMF. Additionally, it may be used for studying potential covariates affecting PK of MPA and its metabolites. Clinical Pharmacology & Therapeutics (2005) 79, P47–P47; doi: 10.1016/j.clpt.2005.12.168

A population pharmacokinetic analysis of cyclosporine (CsA) was performed, and the influence of covariates on CsA oral clearance and relative bioavailability was investigated. Data from 48 recipients of heart-lung (n = 21) or single (n = 18) or double (n = 9) lung transplant were included in the study. Patients received oral CsA as either a conventional formulation (Sandimmune) or a microemulsion (Neoral). Steady-state CsA concentrations were measured before and at approximately 2 and 6 hours after the morning dose of CsA at the end of weeks 1, 2, 3, 4, 13, 26, 39, and 52 posttransplantation. A total of 1004 CsA concentration observations were analyzed using mixed effects-modeling (NONMEM). A 1-compartment pharmacokinetic model and first-order oral absorption were used to fit the data. The absorption rate constants were fixed at 0.25 L/h for Sandimmune and 1.35 L/h for Neoral formulations. Oral clearance (CL/F) was estimated to be 22.1 L/h (95% confidence intervals [CI] 19.5-24.7 L/h). Itraconazole (ITRA), cystic fibrosis (CF), and weight (WT) were identified as significant covariates for CL/F according to the final model: CL/F = 22.1 - 11.3 x ITRA + 23.5 x CF + 0.129 x (WT - 58.7) L/h; where ITRA = 1 if the patient was taking concomitant itraconazole, otherwise 0; CF = 1 if the patient had cystic fibrosis, otherwise CF = 0; and WT is patient weight in kilograms. The relative oral bioavailability of Sandimmune to Neoral was 0.82. The bioavailability of both preparations increased during the first month posttransplantation. Age, gender, and type of transplant (single, double, or heart-lung) were not identified as significant covariates for CsA clearance. The population pharmacokinetic model developed identified some sources of variability in CsA pharmacokinetics; however, an appreciable degree of variability is still present in this patient population.

ABSTRACT A population pharmacokinetic analysis was conducted on nelfinavir in patients infected with human immunodeficiency virus (HIV) who were enrolled in a phase III clinical trial. The data consisted of 509 plasma concentrations from 174 patients who received nelfinavir at a dose of 500 or 750 mg three times a day. The analysis was performed using nonlinear mixed-effect modeling as implemented in NONMEM (version 4.0; double precision). A one-compartment model with first-order absorption best described the data. The timing and small number of early postdose blood levels did not allow accurate estimation of volume of distribution (V/F) and the absorption rate constant (ka). As a result, two models were used to analyze the data: model 1, in which oral clearance (CL/F),V/F, and ka were estimated, and model 2, in which V/F and ka were fixed to known values and only CL/F was estimated. Estimates of CL/F ranged from 41.9 to 45.1 liters/h, values in close agreement with previous studies. Neither body weight, age, sex, race, dose level, baseline viral load, metabolite-to-parent drug plasma concentration ratio, history of liver disease, nor elevated results of liver function tests appeared to be significant covariates for clearance. The only significant covariate-parameter relationship was concomitant use of fluconazole on CL/F, which was associated with a modest reduction in interindividual variability of CL/F. Patients who received concomitant therapy with fluconazole had a statistically significant reduction in nelfinavir CL/F of 26 to 30%. Since serious dose-limiting toxicity and concentration-related toxicities are not apparent for nelfinavir, this effect of fluconazole is unlikely to be of clinical significance.

A semi-physiological pharmacostatistical model was developed and used to study the manner in which intra-individual variability in hepatic clearance is transmitted to the area-under the plasma concentration-time curve from zero to infinity (AUC) of a drug and its metabolite. In order to clarify the effects, the model contained no other sources of variability. As the drug's hepatic extraction ratio increased, the coefficient of variation (CV) of the AUC of the drug increased, whereas that of the metabolite decreased. The AUC of the metabolite increased as the drug's non-hepatic clearance increased. At high extraction ratios, the CV of the AUC of the drug was insensitive to the contributions of other forms of clearance. The results suggest that under certain circumstances, smaller samples sizes could be used in bioequivalence studies for highly variable drugs if the test were based on the metabolite rather than the parent drug.

In the fall of 1997, the US Food and Drug Administration (FDA) proposed to add onto the existing 1994 regulations dealing with the "pediatric use" subsection of prescription drug labels. These new regulations were titled Docket No. 97N-0165 "Regulations Requiring Manufacturers to Assess the Safety and Effectiveness of New Drugs and Biological Products in Pediatric Patients"(1). These new rules will require pharmaceutical companies to collect data for those drugs whose indications may be applicable to usage in children before the compound will be approved (or soon thereafter). In some cases, manufacturers will also have to provide this information (within a length of time determined by both the PDA and the manufacturer) for drugs already marketed. It is proposed that, by including safety and effectiveness information on the label, the pediatric population will be less likely to have serious adverse events or subtherapeutic treatments. This article will cover in detail the 1997 proposed regulations and what it will mean for industry.

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.

The relative susceptibilities of a drug and its first-pass metabolite to various forms of pharmacokinetic variability were studied. Plasma concentrations of both species were simulated under conditions of interindividual variability in intrinsic hepatic clearance, intraindividual variability in hepatic clearance, and/or a concentration-dependent model for assay error. In comparison to the metabolite, the plasma concentrations of the parent drug displayed a heightened sensitivity to all forms of error. The bioequivalence parameters, AUC, C-max, and T-max of the parent drug and the metabolite were determined from an abbreviated data set. Compared to the metabolite, the AUC and C-max of the parent drug were much more sensitive to the added variability. The T-max of both species displayed similar variability. For a given level of manufacturer risk, a much larger group of subjects would be necessary to demonstrate bioequivalence with respect to the drug than with respect to the metabolite.

There are many procedures for estimating pharmacokinetic parameters in a population of patients. Those reviewed here include two traditional methods: Standard Two-Stage (STS) and Iterative Two-Stage methods, and three direct population pharmacokinetic (PPK) methods: Naive Pooled Data, Mixed-Effects Models, and Nonparametric methods. The classical method of estimation is the Standard Two-Stage method; however, multiple samples are required for each individual, which may not be feasible in certain populations. Direct population pharmacokinetic methods have been developed to analyze data sets consisting of a small number of samples per patient, by pooling the data into one data set and analyzing them simultaneously. In general, the direct population methods perform as well as the traditional methods and possess several advantages over traditional methods.

Objective: To survey pharmacists' knowledge of the adverse drug reaction (ADR) reporting process, as well as the nature and seriousness of ADRs observed by pharmacists, and to determine how pharmacists perceive their role in monitoring and reporting suspected reactions. Design: A survey was mailed to 793 Rhode Island pharmacists with a 40% (318) response rate. Results: Two hundred and thirty-five surveys were reviewed for final analysis. Pharmacists in retail settings were more likely than hospital pharmacists to be aware of ADRs relating to therapeutic inequivalence and over-the-counter products, and more likely to ask the patient about ADRs (40% vs 16%). Hospital pharmacists were more likely to receive ADR information from physicians (40% vs 15%). Almost all pharmacists (97%) believed that action should be taken when a serious ADR is suspected. Younger pharmacists (<45 y) were more willing to contact the physician and refer the patient to medical attention. Conclusions: Our results show that fewer than half of the respondents (41%) claimed to have observed a serious ADR (potentially life-threatening or requiring hospitalization), although almost all (97%) believed that pharmacists should take some action when a serious ADR is suspected. The influence of the practice setting, the number of years in practice, and the number of hours worked per week influenced the reporting practices and attitudes.

The application of pharmacokinetic principles can maximize the goals of drug administration from the time a drug is first administered td man during the initial phases of development, to well beyond the approval of the NDA. Population pharmacokinetics is playing an increasing role in this regard. This paper provides a comprehensive review of the principles and methods of population pharmacokinetics. Finally, examples of how population pharmacokinetics may be applied to optimize drug administration are presented.