Population Pharmacokinetic Approach Research Articles

Population pharmacokinetics of phenytoin in critically ill children

The objective was to study the population pharmacokinetics of bound and unbound phenytoin in critically ill children, including influences on the protein binding profile. A population pharmacokinetic approach was used to analyze paired protein-unbound and total phenytoin plasma concentrations (n = 146 each) from 32 critically ill children (0.08-17 years of age) who were admitted to a pediatric hospital, primarily intensive care unit. The pharmacokinetics of unbound and bound phenytoin and the influence of possible influential covariates were modeled and evaluated using visual predictive checks and bootstrapping. The pharmacokinetics of protein-unbound phenytoin was described satisfactorily by a 1-compartment model with first-order absorption in conjunction with a linear partition coefficient parameter to describe the binding of phenytoin to albumin. The partitioning coefficient describing protein binding and distribution to bound phenytoin was estimated to be 8.22. Nonlinear elimination of unbound phenytoin was not supported in this patient group. Weight, allometrically scaled for clearance and volume of distribution for the unbound and bound compartments, and albumin concentration significantly influenced the partition coefficient for protein binding of phenytoin. The population model can be applied to estimate the fraction of unbound phenytoin in critically ill children given an individual's albumin concentration.

Evaluating plasma pharmacokinetics of intravenous iron formulations: judging books by their covers?

Intravenous (IV) iron formulations provide a clinical treatment option for patients when iron supplementation is required but oral administration is unsuitable because of intolerance or lack of efficacy. IV iron use is increasing worldwide, especially in the chronic kidney disease (CKD) population [1]. Pharmacokinetic (PK) analysis of IV iron formulations is challenging unless the compound can be directly measured or it is manufactured with a radiolabelled form of iron (e.g. Fe) to distinguish the IV iron formulation from endogenous serum iron [2]. It is also not well appreciated by clinicians that IV iron formulations exhibit zero-order or capacity-limited metabolism by the reticuloendothelial system [3]. This results in longer residence time in plasma with higher administered doses, especially with larger molecular weight formulations [3]. Commercially available IV iron formulations consist of an iron oxyhydroxide core surrounded by carbohydrate shells of various sizes and polysaccharide branch characteristics in colloidal suspensions [4]. The size of commercially available IV iron–carbohydrate complexes range from 5 to 100 nm and thus meet the definition for nanoparticles, enhancing the complexity of PK studies of these agents [4]. In this issue of Clinical Pharmacokinetics, MuellerPlock et al. [5] evaluate plasma ferumoxytol data from healthy subjects and CKD patients, using a population PK approach seeking to bridge the PK profiles between populations with iron deficiency anaemia. This is arguably one of the larger PK analyses of IV iron plasma data to date, and ferumoxytol offers the distinct advantage of being able to be directly measured by nuclear magnetic resonance. The authors show that, as previously published, ferumoxytol plasma concentration–time profiles were best fitted with a two-compartment model with nonlinear elimination, consistent with the known capacity-limited metabolism by the reticuloendothelial system [3]. A limitation of Mueller-Plock et al.’s analysis, as well as the collective published data on IV iron plasma PK, is that these data likely represent an oversimplification of the PK profile of IV iron–carbohydrate complexes. Ferumoxytol is a superparamagnetic iron oxide nanoparticle (SPION), which was originally developed for use in magnetic resonance imaging (MRI). Biodistribution data for SPIONs demonstrate that different carbohydrate shell structures determine the relative uptake by endothelial and lymphatic cells, as well as by the reticuloendothelial system [6]. Thus, analysis of only short-term plasma PK provides limited information on the ultimate disposition and fate of these agents. Ultimately, the complexity of IV iron–carbohydrate nanoparticle formulations has important implications with regard to both efficacy and safety in treatment of iron deficiency anaemia. These agents have not been well studied with regard to comparative biodistribution, metabolic fate, and potential extracellular and intracellular deposition profiles, and further evaluation of these agents is urgently needed. Analysing short-term plasma data to infer IV iron–carbohydrate PK profiles has been typically acceptable for IV iron registry trials; however, on the basis of the SPION data in the MRI literature, these agents exhibit complicated PK and pharmacodynamic (PD) profiles, which can differ vastly between agents because of carbohydrate shell heterogeneity [6]. Thus, although shortterm plasma PK profiles among groups of healthy and This comment refers to the article available at doi:10.1007/s40262-014-0203-9.

Toward a comprehensive model of ∆(9)-tetrahydrocannabinol pharmacokinetics using a population pharmacokinetics approach.

In the article ‘‘Population pharmacokinetic model of THC integrates oral, intravenous, and pulmonary dosing and characterizes shortand long-term pharmacokinetics’’, Heuberger and colleagues [1] describe a model of D-tetrahydrocannabinol (THC) pharmacokinetics derived from a population pharmacokinetics approach. Population pharmacokinetics is an analytical strategy that develops a statistical model describing the functional relationship between the concentration of a drug and time, typically using non-linear regression with data from individual subjects [2]. A major advantage of this approach over more traditional methods is that the model can be derived from sparsely sampled clinical data, requiring only a few samples from each subject [2, 3]. Further, the data can come from distinct studies with different experimental designs [2]. Population pharmacokinetics is often used to identify pharmacokinetic differences between populations of interest (e.g., adults vs. children). However, the model can also be used to characterize pharmacokinetics of different routes of administration, while still accounting for individual differences in drug disposition [3]. These features can produce detailed models that are relevant to clinical applications (e.g., by guiding a dosing strategy that maintains a drug’s concentration within its therapeutic range) [2]. The model developed by Heuberger and colleagues could improve the therapeutic use of THC, which is under consideration for an expanding range of maladies [4–6]. The pharmacokinetics of THC are complex, and depend on the route of administration as well as individual subject factors such as metabolic capacity and adiposity [7]. This variability, along with the challenge of obtaining repeated samples in an individual over the extended duration required to capture THC elimination, poses a challenge to the development of a comprehensive model of THC pharmacokinetics. The population pharmacokinetic approach used by Heuberger and colleagues [1] addresses these challenges. The model the authors developed used historical data from four different datasets that included pulmonary (either smoked or vaporized), intravenous, and oral routes of administration. The model was then validated by performing visual predictive checks with data not used to build the model. This validation is an important aspect of the work and increases confidence that the model can be generalized to other studies, and, ultimately, to clinical applications. Notably, the model of Heuberger and colleagues (1) incorporates various routes of administration, (2) allows blood THC concentration estimates for an individual from relatively few samples, and (3) incorporates the long terminal phase of THC elimination. Below, the implications of these features are discussed, followed by a description of areas requiring additional research before the model can be applied clinically.

Pharmacokinetic studies in infants using minimal-risk study designs.

Infants are therapeutic orphans. Many drugs used in infants are used "off-label", increasing the risk of drug toxicity and suboptimal efficacy in this vulnerable population. This knowledge gap in clinical pharmacology is partly attributed to challenges associated with conducting clinical trials in infants. Consequently, there is a need for novel and efficient study designs more suited to this population. Available literature describing the use of minimal-risk approaches to characterize the pharmacokinetics (PK) of drugs in infants was critically reviewed. Population PK approach with sparse sampling was found to be well established. Other, more recent alternatives, like dried blood spots sampling, opportunistic design, and the use of non-blood matrices are promising strategies with an increasing number of applications in infants. Physiologically based pharmacokinetic modeling provides valuable insight in drug disposition but still needs more prospective validation. Increasing experience with these methods provides understanding of their strengths and limitations and will help improve the design of future PK studies in infants.

Abnormal olanzapine toxicokinetic profiles – population pharmacokinetic analysis

Context: Olanzapine is widely used in the treatment of schizophrenia and it is becoming more frequently responsible for overdoses. Standard pharmacokinetic models do not fit to the toxic concentration data.Objective: The aim of present study is to investigate the reasons for an abnormal olanzapine plasma concentration time curve in the range of toxic concentrations. Two hypotheses were verified: entering the enterohepatic cycle, and drug deposition and its desorption from activated charcoal used for gastrointestinal decontamination.Materials and methods: One-hundred thirty-five plasma concentration data from 21 patients hospitalized for acute olanzapine poisoning were analyzed with the use of the population pharmacokinetic approach. A non-linear mixed-effects modeling approach with Monolix 4.3.1 was employed.Results: A model assuming gallbladder emptying at irregular intervals was developed. Also, a model that describes desorption of olanzapine from the charcoal surface, in which the dose is divided into two absorbed fractions, was constructed. The analysis has found gastrointestinal decontamination and previous olanzapine treatment, as the significant covariates for toxicokinetic parameters of olanzapine.Conclusion: Our study provides interesting models for investigation of toxic concentration of olanzapine, which may also be used as the basis for further model development for other drugs as well. The investigated population was not large enough to reliably confirm any of the proposed models. It would be well worth continuing this study with more substantial data. Also, any additional information about olanzapine metabolite concentration could be vital.

Abstract 4625: Age dependence of doxorubicin pharmacokinetics in pediatric cancer patients; results of an FP7-funded clinical study

Abstract Doxorubicin is a key component of a number of treatment regimens used in paediatric oncology, despite the very limited pharmacology data on which current dosing regimens are based. We conducted a multicentre, multinational phase II pharmacokinetic study investigating age-dependency in the clearance of doxorubicin in children with solid tumours and leukaemia. The study was funded under the Framework Program 7 of the European Commission. 101 patients treated with doxorubicin according to a tumour-specific national or European therapeutic trial were recruited to the study, with a particular focus on children less than 3 years. Absolute doses of doxorubicin ranged from 2.4 to 57 mg, administered, with infusion durations ranging from 0.25 to 24 hours. Samples were collected after 2 administrations, with 5 samples collected in children <3yrs and 8 samples in children ≥3yrs. Doxorubicin and its major metabolite doxorubicinol were measured in plasma using a validated HPLC-fluorescence assay with a limit of quantification of 2 μg/L for each analyte. Markers such as troponin T and natriuretic peptides were measured to evaluate as clinical indicators of cardiotoxicity. Data were analysed using a population pharmacokinetic approach, including pharmacogenetic covariates. Data were available from all but 5 patients, with samples lost due to withdrawn consent, analytical issues or sample stability related to sample transport. A three compartment model was sufficient to characterize the pharmacokinetics of doxorubicin, with a further compartment to describe those of the major metabolite doxorubicinol. All parameters of the population model were scaled to body surface area. Age dependence of doxorubicin clearance was demonstrated, with children less than 3 years having a lower clearance (21.1±5.8 l/h/m2) than older children (26.6±6.7 l/h/m2) (p=0.0004), even after correcting for body weight. No other patient-related covariate, including liver function, was found to influence the parameters of the model. While the model provided a good fit to the doxorubicinol data, no covariate was identified which influenced the parameters of the metabolite model. Pharmacogenetic variants, including those in transporters and drug metabolizing enzymes, had little influence on pharmacokinetic parameters. Likewise, pharmacokinetics had only limited impact on markers of cardiotoxicity such as troponins or on measured cardiac function. This study yields new pharmacokinetic data on doxorubicin pharmacokinetics in very young patients, suggesting that lower doses may be appropriate in children less than 3 years. The data presented her may be useful for refining dosage regimens in this patient group. Citation Format: Alan V. Boddy, Nicolas Andre, Gianni Bisogno, Joachim Boos, Maurizio D'Incalci, Nina Kontny, Miriam Krischke, Swantje Voeller, Georg Hempel. Age dependence of doxorubicin pharmacokinetics in pediatric cancer patients; results of an FP7-funded clinical study. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4625. doi:10.1158/1538-7445.AM2014-4625

Abstract 4636: Pharmacokinetic (PK) food effect study of immediate-release onapristone and its primary metabolite (M1) in healthy female subjects: implications for design of a new formulation

Abstract Introduction: Onapristone is an antiprogestin with demonstrated clinical activity in breast cancer, reported to have a t1/2 between 2 and 4 hours. Drugs such as megestrol acetate and abiraterone generally show variability in absorption and, depending on the formulation, food effect (≥10 x Cmax variation; ≥5 x AUC variation). A study was conducted to determine the best formulation of onapristone to minimize this variability. Methods: The aim of this study was to determine the pharmacokinetic profile of onapristone and mono-desmethyl onapristone (M1), with and without food. Using a two-period, two-sequence, random assignment cross-over design, twelve healthy female subjects were given 10 mg of an oral immediate release formulation of onapristone either after an overnight fast, or within 30 minutes after a high-fat high-calorie meal, with a 2 week washout between dosing periods. PK sampling was performed following each oral administration at: 0, 15, 30, 45 and 60 minutes, 2, 4, 6, 8, 12, 16 and 24 hours (h). Parameters were calculated using the linear trapezoidal method. Population PK modeling was conducted using the nonlinear mixed effect model. Results: Onapristone plasma t1/2 (mean ± SD) was 4.36 ±0.81 h for the fasted and 3.76 ±0.36 h for the fed state. The absorption phase appeared linear. Onapristone tmax was delayed from 1 to 4 h after food intake. A small effect on the single dose onapristone pharmacokinetic profile was also observed, with a slightly decreased mean Cmax (18%) and increased AUC0-last (11%). Mean population CL of onapristone was 5.02 ±0.67 L/h and 6.63 ±0.87 L/h for fasted and fed states respectively. There was no food effect on M1 exposure but a decrease in M1 plasma peaks (∼35%) after food intake. The onapristone time-concentration curve was adequately described by a 2-compartment open model with linear elimination using a population PK approach. A significant food effect (p<0.0001) was observed on CL of onapristone but not M1. Modeling confirmed that food increased onapristone AUC. One subject aged 27 experienced a 23-day delay in menses after one 10mg onapristone dose and 1 subject experienced transient G2 liver enzyme elevation 3 weeks post-dose. Conclusion: Clinically meaningful Cmax can be reached with a 10 mg onapristone dose. The results are consistent with prior observations, indicating that food delayed absorption and increased AUC when taken concomitantly. Food effect is minimal compared to other drugs in class, but onapristone should preferably be administered 2 hours before or 1 hour after meals. This food effect is unlikely to have clinical consequences. As absorption is linear, a sustained release formulation would probably reduce Cmax by ∼25% while not substantially modifying AUC. Given the estimated t1/2 of 2-4 hours, adequate concentrations should be maintained with twice a day dosing. Citation Format: Keyvan Rezai, Stefan Proniuk, Alex Zukiwski, Erard Gilles, Didier Chassard, Caroline Denot, Haydee L. Ramos, Alice S. Bexon, François Lokiec. Pharmacokinetic (PK) food effect study of immediate-release onapristone and its primary metabolite (M1) in healthy female subjects: implications for design of a new formulation. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4636. doi:10.1158/1538-7445.AM2014-4636

Understanding variability in posaconazole exposure using an integrated population pharmacokinetic analysis.

Posaconazole oral suspension is widely used for antifungal prophylaxis and treatment in immunocompromised patients, with highly variable pharmacokinetics reported in patients due to inconsistent oral absorption. This study aimed to characterize the pharmacokinetics of posaconazole in adults and investigate factors that influence posaconazole pharmacokinetics byusing a population pharmacokinetic approach. Nonlinear mixed-effects modeling was undertaken for two posaconazole studies in patients and healthy volunteers. The influences of demographic and clinical characteristics, such as mucositis, diarrhea, and drug-drug interactions, on posaconazole pharmacokinetics were investigated using a stepwise forward inclusion/backwards deletion procedure. A total of 905 posaconazole concentration measurements from 102 participants were analyzed. A one-compartment pharmacokinetic model with first-order oral absorption with lag time and first-order elimination best described posaconazole pharmacokinetics. Posaconazole relative bioavailability was 55% lower in patients who received posaconazole than in healthy volunteers. Coadministration of proton pump inhibitors (PPIs) or metoclopramide, as well as the occurrence of mucositis or diarrhea, reduced posaconazole relative bioavailability by 45%, 35%, 58%, and 45%, respectively, whereas concomitant ingestion of a nutritional supplement significantly increased bioavailability (129% relative increase). Coadministration of rifampin or phenytoin increased apparent posaconazole clearance by more than 600%, with a smaller increase observed with fosamprenavir (34%). Participant age, weight, or sex did not significantly affect posaconazole pharmacokinetics. Posaconazole absorption was reduced by a range of commonly coadministered medicines and clinical complications, such as mucositis and diarrhea. Avoidance of PPIs and metoclopramide and administration with food or a nutritional supplement are effective strategies to increase posaconazole absorption.

A population pharmacokinetic modeling approach shows that serum penicillin G concentrations are below inhibitory concentrations by two weeks after benzathine penicillin G injection in the majority of young adults.

Serum penicillin G falls to low levels 2 weeks after injection as benzathine penicillin G (BPG) in young adults. Using Pmetrics and previously reported penicillin G pharmacokinetic data after 1.2 million units were given as BPG to 329 male military recruits, here we develop the first reported population pharmacokinetic model of penicillin G after BPG injection. We simulated time-concentration profiles over a broad range of pediatric and adult weights after alternative doses and dose frequencies to predict the probability of maintaining serum penicillin G concentrations of >0.02 mg/liter, a proposed protective threshold against group A Streptococcus pyogenes (GAS). The final population model included linear absorption into a central compartment, distribution to and from a peripheral compartment, and linear elimination from the central compartment, with allometrically scaled volumes and rate constants. With 1.2 million units of BPG given intramuscularly every 4 weeks in four total doses, only 23.2% of 5,000 simulated patients maintained serum penicillin G trough concentrations of >0.02 mg/liter 4 weeks after the last dose. When the doses were 1.8 million units and 2.4 million units, the percentages were 30.2% and 40.7%, respectively. With repeated dosing of 1.2 million units every 3 weeks and every 2 weeks for 4 doses, the percentages of simulated patients with a penicillin G trough concentration of >0.02 mg/liter were 37.8% and 65.2%, respectively. Our simulations support recommendations for more frequent rather than higher BPG doses to prevent recurrent rheumatic heart disease in areas of high GAS prevalence or during outbreaks.

CYP3A4*22 (c.522-191 C>T; rs35599367) is associated with lopinavir pharmacokinetics in HIV-positive adults.

The CYP3A4*22 (c.522-191 C>T; rs35599367) single nucleotide polymorphism has been associated with lower CYP3A4 mRNA expression and activity. We investigated the association of CYP3A4*22 with the pharmacokinetics of lopinavir through a population pharmacokinetic approach. The minor allele frequency for CYP3A4*22 was 0.035, and seven of 375 patients had a combination of CYP3A4*22 and SLCO1B1 521T>C alleles. Lack of information on the ethnicity in this cohort should be considered as a limitation. However, in the final model, the population clearance was 5.9 l/h and patients with CYP3A4*22/*22 had 53% (P=0.023) lower clearance compared with noncarriers. In addition, the combined effect of CYP3A4*22 with SLCO1B1 521T>C (previously shown to be associated with lopinavir plasma concentration) was analysed. We observed a 2.3-fold higher lopinavir trough concentration (Ctrough) in individuals with CYP3A4*22/*22, a 1.8-fold higher Ctrough with SLCO1B1 521CC and a 9.7-fold higher Ctrough in individuals homozygous for both single nucleotide polymorphisms, compared with noncarriers. A simulated dose-reduction scenario showed that 200/100 mg lopinavir/ritonavir was adequate to achieve therapeutic concentration in individuals with CYP3A4*22/*22 alone or in combination with SLCO1B1 521CC. These data further our understanding of the genetic basis for variability in the pharmacokinetics of lopinavir.

The effect of ABCG2 genotype on the population pharmacokinetics of sunitinib in patients with renal cell carcinoma.

Sunitinib, a multitargeted tyrosine kinase inhibitor, offers favorable therapeutic outcomes to patients with advanced renal cell carcinoma. However, to maximize the clinical benefits, an effective therapeutic management strategy with dose optimization is essential. The objectives of this analysis were to describe the pharmacokinetics (PK) of sunitinib by a population PK approach and to quantitatively evaluate the effect of potential predictive factors including ABCG2 genotype on the PK of sunitinib. Plasma concentration-time profiles at 3 consecutive days including a total of 245 sunitinib plasma concentrations were available from 19 Japanese patients with renal cell carcinoma. Blood samples were collected on days 2, 8, and 15 after the start of the therapy. Population PK analysis was performed using NONMEM 7.2. Body weight, gender, and genotype of ABCG2 421C>A were evaluated as potential covariates. Interoccasion variability (IOV) among the 3 sampling days was also assessed as a random effect parameter. The sunitinib PK profiles were best described by a 1-compartment model with first-order absorption. The ABCG2 421C>A genotype was identified as a significant covariate for the prediction of oral clearance (CL/F). No significant improvement in model fit was observed by including body weight and/or gender. A systematic difference in estimated population CL/F was observed between days 2 and 8, which was quantified as approximately 30% decrease over time. This difference was described as a covariate for CL/F in the model. IOV included as a random effect parameter significantly improved the model fit. This analysis provides a population PK model of sunitinib with the ABCG2 421C>A genotype as a predictive covariate for CL/F. It also suggests that IOV and change of CL/F over time need to be considered to predict the sunitinib PK more accurately. These findings will be implemented to optimize the pharmacotherapy of sunitinib.

Population pharmacokinetics and Bayesian estimation of tacrolimus exposure in paediatric liver transplant recipients

The objectives of this study were to develop a population pharmacokinetic (PopPK) model for tacrolimus in paediatric liver transplant patients and determine optimal sampling strategies to estimate tacrolimus exposure accurately. Twelve hour intensive pharmacokinetic profiles from 30 patients (age 0.4-18.4 years) receiving tacrolimus orally were analysed. The PopPK model explored the following covariates: weight, age, sex, type of transplant, age of liver donor, liver function tests, albumin, haematocrit, drug interactions, drug formulation and time post-transplantation. Optimal sampling strategies were developed and validated with jackknife. A two-compartment model with first-order absorption and elimination and lag time described the data. Weight was included on all pharmacokinetic parameters. Typical apparent clearance and central volume of distribution were 12.1 l h(-1) and 31.3 l, respectively. The PopPK approach led to the development of optimal sampling strategies, which allowed estimation of tacrolimus pharmacokinetics and area under the concentration–time curve (AUC) on the basis of practical sampling schedules (three or four sampling times within 4 h) with clinically acceptable prediction error limit. The mean bias and precision of the Bayesian vs. reference (trapezoidal) AUCs ranged from -2.8 to -1.9% and from 7.4 to 12.5%, respectively. The PopPK of tacrolimus and empirical Bayesian estimates represent an accurate and convenient method to predict tacrolimus AUC(0-12) in paediatric liver transplant recipients, despite high between-subject variability in pharmacokinetics and patient demographics. The developed optimal sampling strategies will allow the undertaking of prospective trials to define the tacrolimus AUC-based therapeutic window and dosing guidelines in this population.

Population pharmacokinetic modelling and evaluation of different dosage regimens for darunavir and ritonavir in HIV-infected individuals.

Darunavir is a protease inhibitor that is administered with low-dose ritonavir to enhance its bioavailability. It is prescribed at standard dosage regimens of 600/100 mg twice daily in treatment-experienced patients and 800/100 mg once daily in naive patients. A population pharmacokinetic approach was used to characterize the pharmacokinetics of both drugs and their interaction in a cohort of unselected patients and to compare darunavir exposure expected under alternative dosage regimens. The study population included 105 HIV-infected individuals who provided darunavir and ritonavir plasma concentrations. Firstly, a population pharmacokinetic analysis for darunavir and ritonavir was conducted, with inclusion of patients' demographic, clinical and genetic characteristics as potential covariates (NONMEM(®)). Then, the interaction between darunavir and ritonavir was studied while incorporating levels of both drugs into different inhibitory models. Finally, model-based simulations were performed to compare trough concentrations (Cmin) between the recommended dosage regimen and alternative combinations of darunavir and ritonavir. A one-compartment model with first-order absorption adequately characterized darunavir and ritonavir pharmacokinetics. The between-subject variability in both compounds was important [coefficient of variation (CV%) 34% and 47% for darunavir and ritonavir clearance, respectively]. Lopinavir and ritonavir exposure (AUC) affected darunavir clearance, while body weight and darunavir AUC influenced ritonavir elimination. None of the tested genetic variants showed any influence on darunavir or ritonavir pharmacokinetics. The simulations predicted darunavir Cmin much higher than the IC50 thresholds for wild-type and protease inhibitor-resistant HIV-1 strains (55 and 550 ng/mL, respectively) under standard dosing in >98% of experienced and naive patients. Alternative regimens of darunavir/ritonavir 1200/100 or 1200/200 mg once daily also had predicted adequate Cmin (>550 ng/mL) in 84% and 93% of patients, respectively. Reduction of darunavir/ritonavir dosage to 600/50 mg twice daily led to a 23% reduction in average Cmin, still with only 3.8% of patients having concentrations below the IC50 for resistant strains. The important variability in darunavir and ritonavir pharmacokinetics is poorly explained by clinical covariates and genetic influences. In experienced patients, treatment simplification strategies guided by drug level measurements and adherence monitoring could be proposed.

Vitamin D time profile based on the contribution of non-genetic and genetic factors in HIV-infected individuals of European ancestry.

Vitamin D deficiency is prevalent in HIV-infected individuals and vitamin D supplementation is proposed according to standard care. This study aimed at characterizing the kinetics of 25(OH)D in a cohort of HIV-infected individuals of European ancestry to better define the influence of genetic and non-genetic factors on 25(OH)D levels. These data were used for the optimization of vitamin D supplementation in order to reach therapeutic targets. 1,397 25(OH)D plasma levels and relevant clinical information were collected in 664 participants during medical routine follow-up visits. They were genotyped for 7 SNPs in 4 genes known to be associated with 25(OH)D levels. 25(OH)D concentrations were analysed using a population pharmacokinetic approach. The percentage of individuals with 25(OH)D concentrations within the recommended range of 20-40 ng/ml during 12 months of follow-up and several dosage regimens were evaluated by simulation. A one-compartment model with linear absorption and elimination was used to describe 25(OH)D pharmacokinetics, while integrating endogenous baseline plasma concentrations. Covariate analyses confirmed the effect of seasonality, body mass index, smoking habits, the analytical method, darunavir/ritonavir and the genetic variant in GC (rs2282679) on 25(OH)D concentrations. 11% of the inter-individual variability in 25(OH)D levels was explained by seasonality and other non-genetic covariates, and 1% by genetics. The optimal supplementation for severe vitamin D deficient patients was 300,000 IU two times per year. This analysis allowed identifying factors associated with 25(OH)D plasma levels in HIV-infected individuals. Improvement of dosage regimen and timing of vitamin D supplementation is proposed based on those results.

A population pharmacokinetic approach to describe cephalexin disposition in adult and aged dogs.

This study was conducted in order to characterize the pharmacokinetics of orally administered cephalexin to healthy adult and aged dogs, using a population pharmacokinetic approach. Two hundred and eighty-six cephalexin plasma concentrations obtained from previous pharmacokinetic studies were used. Sex, age, pharmaceutical formulation, and breed were evaluated as covariates. A one-compartment model with an absorption lag-time (Tlag) best described the data. The final model included age (adult; aged) on apparent volume of distribution (Vd/F), apparent elimination rate (ke/F), and Tlag; sex (female; male) on ke/F, and breed (Beagle; mixed-breed) on Vd/F. Addition of the covariates to the model explained 78% of the interindividal variability (IIV) in Vd/F, 36% in ke/F, and 24% in Tlag, respectively. Formulation did not affect the variability of any of the pharmacokinetic parameters. Tlag was longer, whereas Vd/F and ke/F were lower in aged compared to adult animals; in female aged dogs ke/F was lower than in male aged dogs; however, the differences were of low magnitude. Different disposition of cephalexin may be expected in aged dogs.

Use of a population pharmacokinetic approach for the clinical development of a fixed-dose subcutaneous formulation of trastuzumab.

A new subcutaneous (s.c.) trastuzumab formulation provides savings in terms of time and is preferred by patients and health care professionals relative to standard intravenous (i.v.) administration due to simpler and more rapid administration (2–5 minutes). Selection of the s.c. dose was based on a pharmacokinetic bridging approach that aimed to achieve noninferior trastuzumab serum trough concentrations (Ctrough) vs. reference i.v. administration. Using population modeling and simulation, we showed that a fixed 600-mg trastuzumab s.c. dose, administered thrice-weekly (Q3W) without a loading dose, would provide Ctrough (predose Cycle 8) and area under the time–concentration curve (AUC0–21 days, Cycle 7) at least as high as Q3W i.v. administration. The model was retrospectively validated using observed pharmacokinetic data from an independent phase III study of (neo)adjuvant trastuzumab (HannaH). These results provide a strong pharmacokinetic rationale for the trastuzumab s.c. 600-mg fixed dose, supported by the noninferior efficacy of this regimen vs. reference i.v. administration.

Semiphysiological versus empirical modelling of the population pharmacokinetics of free and total cefazolin during pregnancy.

This work describes a first population pharmacokinetic (PK) model for free and total cefazolin during pregnancy, which can be used for dose regimen optimization. Secondly, analysis of PK studies in pregnant patients is challenging due to study design limitations. We therefore developed a semiphysiological modeling approach, which leveraged gestation-induced changes in creatinine clearance (CrCL) into a population PK model. This model was then compared to the conventional empirical covariate model. First, a base two-compartmental PK model with a linear protein binding was developed. The empirical covariate model for gestational changes consisted of a linear relationship between CL and gestational age. The semiphysiological model was based on the base population PK model and a separately developed mixed-effect model for gestation-induced change in CrCL. Estimates for baseline clearance (CL) were 0.119 L/min (RSE 58%) and 0.142 L/min (RSE 44%) for the empirical and semiphysiological models, respectively. Both models described the available PK data comparably well. However, as the semiphysiological model was based on prior knowledge of gestation-induced changes in renal function, this model may have improved predictive performance. This work demonstrates how a hybrid semiphysiological population PK approach may be of relevance in order to derive more informative inferences.

CYP3A5*3 and bilirubin predict midazolam population pharmacokinetics in Asian cancer patients

We aim to evaluate the influence of covariates, including cytochrome P450 3A (CYP3A) genetic polymorphisms, on the pharmacokinetics of midazolam (MDZ) in Asian cancer patients, using a population pharmacokinetic approach. Pharmacokinetic data were obtained from 24 adult cancer patients who received an intravenous bolus dose of 1 mg MDZ as a CYP3A phenotyping probe, 1-day before starting FOLFIRI chemotherapy. Concentrations of MDZ and its major metabolites, 1'-hydroxymidazolam (1OHM) and 1'-hydroxymidazolam glucuronide (HMG) were measured using liquid chromatography/mass spectrometry. The population pharmacokinetic study was conducted using NONMEM. Demographics, clinical characteristics, and genetic polymorphisms were screened as covariates. A two-compartment model for MDZ and two sequential compartments representing 1OHM and HMG best described the data. The CYP3A5*3 and total bilirubin level significantly influenced MDZ clearance. The population typical MDZ clearance for CYP3A5*3 expressers was 22% lower than non-expressers. Baseline bodyweight was a statistically significant covariate for clearance and distribution volume of 1OHM. Creatinine clearance was positively correlated with HMG clearance. Our data indicate that CYP3A5*3, total bilirubin, bodyweight, and creatinine clearance are important predictors of MDZ and metabolite pharmacokinetics. Further studies in more patients are needed to explore the links between the identified covariates and the disposition of MDZ and its metabolites.

Utility of population pharmacokinetic modeling in the assessment of therapeutic protein-drug interactions

Assessment of pharmacokinetic (PK) based drug-drug interactions (DDI) is essential for ensuring patient safety and drug efficacy. With the substantial increase in therapeutic proteins (TP) entering the market and drug development, evaluation of TP-drug interaction (TPDI) has become increasingly important. Unlike for small molecule (e.g., chemical-based) drugs, conducting TPDI studies often presents logistical challenges, while the population PK (PPK) modeling may be a viable approach dealing with the issues. A working group was formed with members from the pharmaceutical industry and the FDA to assess the utility of PPK-based TPDI assessment including study designs, data analysis methods, and implementation strategy. This paper summarizes key issues for consideration as well as a proposed strategy with focuses on (1) PPK approach for exploratory assessment; (2) PPK approach for confirmatory assessment; (3) importance of data quality; (4) implementation strategy; and (5) potential regulatory implications. Advantages and limitations of the approach are also discussed.

Determination of the pharmacokinetics of glycopyrronium in the lung using a population pharmacokinetic modelling approach.

Glycopyrronium bromide (NVA237) is a once-daily long-acting muscarinic antagonist recently approved for the treatment of chronic obstructive pulmonary disease. In this study, we used population pharmacokinetic (PK) modelling to provide insights into the impact of the lung PK of glycopyrronium on its systemic PK profile and, in turn, to understand the impact of lung bioavailability and residence time on the choice of dosage regimen. We developed and validated a population PK model to characterize the lung absorption of glycopyrronium using plasma PK data derived from studies in which this drug was administered by different routes to healthy volunteers. The model was also used to carry out simulations of once-daily and twice-daily regimens and to characterize amounts of glycopyrronium in systemic compartments and lungs. The model-derived PK parameters were comparable to those obtained with noncompartmental analysis, confirming the usefulness of our model. The model suggested that the lung absorption of glycopyrronium was dominated by slow-phase absorption with a half-life of about 3.5 days, which accounted for 79% of drug absorbed through the lungs into the bloodstream, from where glycopyrronium was quickly eliminated. Simulations of once-daily and twice-daily administration generated similar PK profiles in the lung compartments. The slow absorption from the lungs, together with the rapid elimination from the systemic circulation, could explain how once-daily glycopyrronium provides sustained bronchodilatation with a low incidence of adverse effects in patients with chronic obstructive pulmonary disease. Its extended intrapulmonary residence time also provides pharmacokinetic evidence that glycopyrronium has the profile of a once-daily drug.