Clinical Pharmacokinetics

Cost-Neutral Optimization of Pazopanib Exposure by Splitting Intake Moments: A Prospective Pharmacokinetic Study in Cancer Patients Abstract Background and Objective Pazopanib is an oral tyrosine kinase inhibitor used in the treatment of renal cell carcinoma and soft-tissue sarcoma. At the approved dose of 800 mg once daily (QD), 16–20% of patients are being underdosed and at risk of decreased efficacy. This study aimed to show whether splitting intake moments, as a cost-neutral alternative to a dose increase, leads to an increased exposure. Methods We performed a cross-over trial comparing the pharmacokinetics of pazopanib 800 mg QD with pazopanib 400 mg twice daily. Pharmacokinetic sampling was performed at steady-state for both dosing schedules. Results Nine evaluable patients were included. At the 800 mg QD dosing schedule, median minimum plasma concentration (Cmin), area under the concentration–time curve from 0 to 24 h (AUC0–24h), and maximum plasma concentration (Cmax) were 23.2 mg/L (interquartile range 18.5–27.6), 773 mg h/L (557–1009), and 40.6 mg/L (36.4–56.4) compared with 41.6 mg/L (30.5–55.8, p = 0.004), 942 mg h/L (885–1419, p = 0.027), and 50.2 mg/L (46.8–72.5, p = 0.074) at 400 mg twice daily. One patient experienced a grade 3 event (i.e., diarrhea). Conclusions This study demonstrates that splitting intake moments of pazopanib leads to a 79% increase in Cmin, with acceptable tolerability. Therefore, this new dosing schedule offers a cost-neutral opportunity to optimize treatment in patients with low exposure. Clinical Trial Registration NL6137 (http://www.trialregister.nl).

An Update on Population Pharmacokinetic Analyses of Vancomycin, Part I: In Adults Abstract Despite the wide clinical use of vancomycin, controversy remains regarding its optimal dosage regimens. This can be attributed to the large between- and within-subject variability in the pharmacokinetics of vancomycin. This review aimed at providing a synthesis of population pharmacokinetic models of vancomycin in adults, determining the most reported pharmacokinetic models, and identifying various sources of variability in different special subpopulations to better inform vancomycin dosing. We searched PubMed and EMBASE for population pharmacokinetic studies of vancomycin published from January 2011 to May 2019. Inspection of the relevant lists of references was conducted, as well. This search resulted in a total of 30 eligible studies, which were included. One-, two-, and three-compartments models were reported to best describe vancomycin population pharmacokinetics in 13, 14, and 3 studies, respectively. Three-compartment models were implemented in three studies to account for an additional cerebrospinal fluid compartment. The most common predictors were creatinine clearance and bodyweight, in 20 and 13 studies, respectively. Estimated values of vancomycin clearance and total volume of distribution varied widely from 0.334 to 8.75 L/h (0.0054–0.1279 L/h/kg) and from 7.12 to 501.8 L (0.097–6.97 L/kg), respectively. Almost all studies implemented an exponential interindividual variability model, and the highest variability on clearance was 99.2%. In conclusion, this review highlights the wide ranges and the high variability of estimated population pharmacokinetic parameters. This information can help guide dosing in different subpopulations. Yet, additional analyses with pooled subpopulations might be needed to confirm the necessity of modified dosage regimens.

Effective Removal of Dabigatran by Idarucizumab or Hemodialysis: A Physiologically Based Pharmacokinetic Modeling Analysis Abstract Background Application of idarucizumab and hemodialysis are options to reverse the action of the oral anticoagulant dabigatran in emergency situations. Objectives The objectives of this study were to build and evaluate a mechanistic, whole-body physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) model of idarucizumab, including its effects on dabigatran plasma concentrations and blood coagulation, in healthy and renally impaired individuals, and to include the effect of hemodialysis on dabigatran exposure. Methods The idarucizumab model was built with the software packages PK-Sim® and MoBi® and evaluated using the full range of available clinical data. The default kidney structure in MoBi® was extended to mechanistically describe the renal reabsorption of idarucizumab and to correctly reproduce the reported fractions excreted into urine. To model the PD effects of idarucizumab on dabigatran plasma concentrations, and consequently also on blood coagulation, idarucizumab-dabigatran binding was implemented and a previously established PBPK model of dabigatran was expanded to a PBPK/PD model. The effect of hemodialysis on dabigatran was implemented by the addition of an extracorporeal dialyzer compartment with a clearance process governed by dialysate and blood flow rates. Results The established idarucizumab-dabigatran-hemodialysis PBPK/PD model shows a good descriptive and predictive performance. To capture the clinical data of patients with renal impairment, both glomerular filtration and tubular reabsorption were modeled as functions of the individual creatinine clearance. Conclusions A comprehensive and mechanistic PBPK/PD model to study dabigatran reversal has been established, which includes whole-body PBPK modeling of idarucizumab, the idarucizumab-dabigatran interaction, dabigatran hemodialysis, the pharmacodynamic effect of dabigatran on blood coagulation, and the impact of renal function in these different scenarios. The model was applied to explore different reversal scenarios for dabigatran therapy.

Clinical Pharmacokinetics and Pharmacodynamics of Imipenem–Cilastatin/Relebactam Combination Therapy Abstract On 16 July, 2019, the US Food and Drug Administration approved imipenem–cilastatin/relebactam (Recarbrio™) for the treatment of adults with complicated urinary tract infections and complicated intra-abdominal infections. This decision was based on substantial clinical and pre-clinical data, including rigorous pharmacokinetic and pharmacodynamic work, and is an important step forward in the management of these debilitating conditions. This article provides an overview of the body of research associated with imipenem–cilastatin/relebactam, beginning with an examination of the fundamental underpinnings of the pharmacokinetic/pharmacodynamic index. This is followed by the pharmacokinetic/pharmacodynamic work that led to the approval of this novel drug combination, including data derived from checkerboard and hollow fiber infection studies, as well as large, multi-center, phase III clinical trials known as RESTORE-IMI 1 and RESTORE-IMI 2. The article also explores how this important new antibiotic may be used to treat other infections in the years to come, including hospital-acquired bacterial pneumonia and ventilator-associated pneumonia attributed to imipenem-non-susceptible pathogens and certain atypical mycobacterial infections.

Population Pharmacokinetics of MCLA-128, a HER2/HER3 Bispecific Monoclonal Antibody, in Patients with Solid Tumors Abstract Background and Objectives MCLA-128 is a bispecific monoclonal antibody targeting the HER2 and HER3 receptors and is in development to overcome HER3-mediated resistance to anti-HER2 therapies. The aims of this analysis were to characterize the population pharmacokinetics of MCLA-128 in patients with various solid tumors, to evaluate patient-related factors that affect the disposition of MCLA-128, and to assess whether flat dosing is appropriate. Methods MCLA-128 concentration data following intravenous administration were collected in a phase I/II clinical trial. Pharmacokinetic data were analyzed using non-linear mixed-effects modeling. Different compartmental models were evaluated. Various body size parameters including body weight, body surface area, and fat-free mass were evaluated as covariates in addition to age, sex, HER2 status, and tumor burden. Results In total, 1115 serum concentration measurements were available from 116 patients. The pharmacokinetics of MCLA-128 was best described by a two-compartment model with linear and non-linear (Michaelis–Menten) clearance. Fat-free mass significantly affected the linear clearance and volume of distribution of the central compartment of MCLA-128, explaining 8.4% and 5.6% of inter-individual variability, respectively. Tumor burden significantly affected the non-linear clearance capacity. Simulations demonstrated that dosing based on body size parameters resulted in similar area under the plasma concentration-time curve for a dosing interval (AUC0–τ), maximum and trough concentrations of MCLA-128, compared to flat dosing. Conclusions This analysis demonstrated that the pharmacokinetics of MCLA-128 exhibits similar disposition characteristics to other therapeutic monoclonal antibodies and that a flat dose of MCLA-128 in patients with various solid tumors is appropriate.

Pharmacokinetic Modeling, Simulation, and Development of a Limited Sampling Strategy of Cycloserine in Patients with Multidrug-/Extensively Drug-Resistant Tuberculosis Abstract Background and Objective Multidrug-resistant tuberculosis has much poorer treatment outcomes compared with drug-susceptible tuberculosis because second-line drugs for treating multidrug resistant tuberculosis are less effective and are frequently associated with side effects. Optimization of drug treatment is urgently needed. Cycloserine is a second-line tuberculosis drug with variable pharmacokinetics and thus variable exposure when programmatic doses are used. The objective of this study was to develop a population pharmacokinetic model of cycloserine to assess drug exposure and to develop a limited sampling strategy for cycloserine exposure monitoring. Material and Methods Patients with multidrug-/extensively drug-resistant tuberculosis who were treated for > 7 days with cycloserine were eligible for inclusion. Patients received cycloserine 500 mg (body weight ≤ 50 kg) or 750 mg (body weight > 50 kg) once daily. MW/Pharm 3.83 (Mediware, Groningen, The Netherlands) was used to parameterize the population pharmacokinetic model. The model was compared with pharmacokinetic values from the literature and evaluated with a bootstrap analysis, Monte Carlo simulation, and an external dataset. Monte Carlo simulations were used to develop a limited sampling strategy. Results Cycloserine plasma concentration vs time curves were obtained from 15 hospitalized patients (nine male, six female, median age 35 years). Mean dose/kg body weight was 11.5 mg/kg (standard deviation 2.04 mg/kg). Median area under the concentration–time curve over 24 h (AUC0–24 h) of cycloserine was 888 h mg/L (interquartile range 728–1252 h mg/L) and median maximum concentration of cycloserine was 23.31 mg/L (interquartile range 20.14–33.30 mg/L). The final population pharmacokinetic model consisted of the following pharmacokinetic parameters [mean (standard deviation)]: absorption constant Ka_po of 0.39 (0.31) h−1, distribution over the central compartment (Vd) of 0.54 (0.26) L/kg LBM, renal clearance as fraction of the estimated glomerular filtration rate of 0.092 (0.038), and metabolic clearance of 1.05 (0.75) L/h. The population pharmacokinetic model was successfully evaluated with a bootstrap analysis, Monte Carlo simulation, and an external dataset of Chinese patients (difference of 14.6% and 19.5% in measured and calculated concentrations and AUC0–24 h, respectively). Root-mean-squared-errors found in predicting the AUC0–24 h using a one- (4 h) and a two- (2 h and 7 h) limited sampling strategy were 1.60% and 0.14%, respectively. Conclusions This developed population pharmacokinetic model can be used to calculate cycloserine concentrations and exposure in patients with multidrug-/extensively drug-resistant tuberculosis. This model was successfully validated by internal and external validation methods. This study showed that the AUC0–24 h of cycloserine can be estimated in patients with multidrug-/extensively drug-resistant tuberculosis using a 1- or 2-point limited sampling strategy in combination with the developed population pharmacokinetic model. This strategy can be used in studies to correlate drug exposure with clinical outcome. This study also showed that good target attainment rates, expressed by time above the minimal inhibitory concentration, were obtained for cycloserine with a minimal inhibitory concentration of 5 and 10 mg/L, but low rates with a minimal inhibitory concentration of 20 and 32.5 mg/L.

Population Pharmacokinetics of Imipenem in Critically Ill Patients: A Parametric and Nonparametric Model Converge on CKD-EPI Estimated Glomerular Filtration Rate as an Impactful Covariate Abstract Background Population pharmacokinetic (popPK) models for antibiotics are used to improve dosing strategies and individualize dosing by therapeutic drug monitoring. Little is known about the differences in results of parametric versus nonparametric popPK models and their potential consequences in clinical practice. We developed both parametric and nonparametric models of imipenem using data from critically ill patients and compared their results. Methods Twenty-six critically ill patients treated with intravenous imipenem/cilastatin were included in this study. Median estimated glomerular filtration rate (eGFR) measured by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation was 116 mL/min/1.73 m2 (interquartile range 104–124) at inclusion. The usual dosing regimen was 500 mg/500 mg four times daily. On average, five imipenem levels per patient (138 levels in total) were drawn as peak, intermediate, and trough levels. Imipenem concentration-time profiles were analyzed using parametric (NONMEM 7.2) and nonparametric (Pmetrics 1.5.2) popPK software. Results For both methods, data were best described by a model with two distribution compartments and the CKD-EPI eGFR equation unadjusted for body surface area as a covariate on the elimination rate constant (Ke). The parametric population parameter estimates were Ke 0.637 h−1 (between-subject variability [BSV]: 19.0% coefficient of variation [CV]) and central distribution volume (Vc) 29.6 L (without BSV). The nonparametric values were Ke 0.681 h−1 (34.0% CV) and Vc 31.1 L (42.6% CV). Conclusions Both models described imipenem popPK well; the parameter estimates were comparable and the included covariate was identical. However, estimated BSV was higher in the nonparametric model. This may have consequences for estimated exposure during dosing simulations and should be further investigated in simulation studies.

Therapeutic Drug Monitoring of Antiepileptic Drugs in Women with Epilepsy Before, During, and After Pregnancy Abstract During pregnancy, the pharmacokinetics of an antiepileptic drug is altered because of changes in the clearance capacity and volume of distribution. These changes may have consequences for the frequency of seizures during pregnancy and fetal exposure to antiepileptic drugs. In 2009, a review was published providing guidance for the dosing and therapeutic drug monitoring of antiepileptic drugs during pregnancy. Since that review, new drugs have been licensed and new information about existing drugs has been published. With this review, we aim to provide an updated narrative overview of changes in the pharmacokinetics of antiepileptic drugs in women during pregnancy. In addition, we aim to formulate advice for dose modification and therapeutic drug monitoring of antiepileptic drugs. We searched PubMed and the available literature on the pharmacokinetic changes of antiepileptic drugs and seizure frequency during pregnancy published between January 2007 and September 2018. During pregnancy, an increase in clearance and a decrease in the concentrations of lamotrigine, levetiracetam, oxcarbazepine’s active metabolite licarbazepine, topiramate, and zonisamide were observed. Carbamazepine clearance remains unchanged during pregnancy. There is inadequate or no evidence for changes in the clearance or concentrations of clobazam and its active metabolite N-desmethylclobazam, gabapentin, lacosamide, perampanel, and valproate. Postpartum elimination rates of lamotrigine, levetiracetam, and licarbazepine resumed to pre-pregnancy values within the first few weeks after pregnancy. We advise monitoring of antiepileptic drug trough concentrations twice before pregnancy. This is the reference concentration. We also advise to consider dose adjustments guided by therapeutic drug monitoring during pregnancy if the antiepileptic drug concentration decreases 15–25% from the pre-pregnancy reference concentration, in the presence of risk factors for convulsions. If the antiepileptic drug concentration changes more than 25% compared with the reference concentration, dose adjustment is advised. Monitoring of levetiracetam, licarbazepine, lamotrigine, and topiramate is recommended during and after pregnancy. Monitoring of clobazam, N-desmethylclobazam, gabapentin, lacosamide, perampanel, and zonisamide during and after pregnancy should be considered. Because of the risk of teratogenic effects, valproate should be avoided during pregnancy. If that is impossible, monitoring of both total and unbound valproate is recommended. More research is needed on the large number of unclear pregnancy-related effects on the pharmacokinetics of antiepileptic drugs.

Correction to: Evidence-Based Design of Fixed-Dose Combinations: Principles and Application to Pediatric Anti-Tuberculosis Therapy In the online supplementary

Modelling of the Time-Varying Pharmacokinetics of Therapeutic Monoclonal Antibodies: A Literature Review Abstract Therapeutic monoclonal antibodies (mAbs) are increasingly used to treat a variety of conditions. The sources of their interindividual pharmacokinetic (PK) variability have been extensively studied, but few data on their intraindividual PK variability are available. In this article, we reviewed the published population compartmental models used to describe the time-varying PK of mAbs in clinical settings. Of 189 publications, 13 report the use of time-varying parameters and 30 describe the effects of antidrug antibody (ADA) development. Currently published time-varying models mainly describe fast decreases in clearance due to target-mediated elimination or slow decreases in clearance owing to cachexia reduction. Immunogenicity models mostly describe ‘on–off’ increases of clearance due to a rapid elimination of mAbs–ADA complexes. Some more sophisticated models attempted to decipher the time course of immunogenic response, notably by accounting for the time of onset and progressive increase in ADA production. Currently available time-varying and immunogenicity models are empirical approximations of the complex mAb disposition, but they emphasize the necessity to account for the temporal variations of mAb PK in model building. The clinical implications of the time-varying PK of mAbs are not fully understood, but some publications reported a link between clearance decrease and disease improvement. The future perspectives offered by this knowledge include the possibility to adapt the regimen to the disease and the patients’ state, and also to immune status, and to monitor their evolution by monitoring PK variations.