Ron J. Keizer

Clinical Pharmacokinetics of Therapeutic Monoclonal Antibodies

Monoclonal antibodies (mAbs) have been used in the treatment of various diseases for over 20 years and combine high specificity with generally low toxicity. Their pharmacokinetic properties differ markedly from those of non-antibody-type drugs, and these properties can have important clinical implications. mAbs are administered intravenously, intramuscularly or subcutaneously. Oral administration is precluded by the molecular size, hydrophilicity and gastric degradation of mAbs. Distribution into tissue is slow because of the molecular size of mAbs, and volumes of distribution are generally low. mAbs are metabolized to peptides and amino acids in several tissues, by circulating phagocytic cells or by their target antigen-containing cells. Antibodies and endogenous immunoglobulins are protected from degradation by binding to protective receptors (the neonatal Fc-receptor [FcRn]), which explains their long elimination half-lives (up to 4 weeks). Population pharmacokinetic analyses have been applied in assessing covariates in the disposition of mAbs. Both linear and nonlinear elimination have been reported for mAbs, which is probably caused by target-mediated disposition. Possible factors influencing elimination of mAbs include the amount of the target antigen, immune reactions to the antibody and patient demographics. Bodyweight and/or body surface area are generally related to clearance of mAbs, but clinical relevance is often low. Metabolic drug-drug interactions are rare for mAbs. Exposure-response relationships have been described for some mAbs. In conclusion, the parenteral administration, slow tissue distribution and long elimination half-life are the most pronounced clinical pharmacokinetic characteristics of mAbs.

Modeling and Simulation Workbench for NONMEM: Tutorial on Pirana, PsN, and Xpose

Several software tools are available that facilitate the use of the NONMEM software and extend its functionality. This tutorial shows how three commonly used and freely available tools, Pirana, PsN, and Xpose, form a tightly integrated workbench for modeling and simulation with NONMEM. During the tutorial, we provide some guidance on what diagnostics we consider most useful in pharmacokinetic model development and how to construct them using these tools.

Piraña and PCluster: A modeling environment and cluster infrastructure for NONMEM

Pharmacokinetic-pharmacodynamic modeling using non-linear mixed effects modeling (NONMEM) is a powerful yet challenging technique, as the software is generally accessed from the command line. A graphical user interface, Piraña, was developed that offers a complete modeling environment for NONMEM, enabling both novice and advanced users to increase efficiency of their workflow. Piraña provides features for the management and creation of model files, the overview of modeling results, creation of run reports and handling of datasets and output tables, and the running of custom R scripts on model output. Through the secure shell (SSH) protocol, Piraña can also be used to connect to Linux clusters (SGE, MOSIX) for distribution of workload. Modeling with NONMEM is computationally burdensome, which may be alleviated by distributing runs to computer clusters. A solution to this problem is offered here, called PCluster. This platform is easy to set up, runs in standard network environments, and can be extended with additional nodes if needed. The cluster supports the modeling toolkit Perl speaks NONMEM (PsN), and can include dedicated or non-dedicated PCs. A daemon script, written in Perl, was designed to run in the background on each node in the cluster, and to manage job distribution. The PCluster can be accessed from Piraña, and both software products have extensively been tested on a large academic network. The software is available under an open-source license.

Pharmacokinetics of Miltefosine in Old World Cutaneous Leishmaniasis Patients

ABSTRACT The pharmacokinetics of miltefosine in leishmaniasis patients are, to a great extent, unknown. We examined and characterized the pharmacokinetics of miltefosine in a group of patients with Old World (Leishmania major) cutaneous leishmaniasis. Miltefosine plasma concentrations were determined in samples taken during and up to 5 months after the end of treatment from 31 Dutch military personnel who contracted cutaneous leishmaniasis in Afghanistan and were treated with 150 mg miltefosine/day for 28 days. Samples were analyzed with a validated liquid chromatography-tandem mass spectrometry assay with a lower limit of quantification (LLOQ) of 4 ng/ml. Population pharmacokinetic modeling was performed with nonlinear mixed-effect modeling, using NONMEM. The pharmacokinetics of miltefosine could best be described by an open two-compartment disposition model, with a first elimination half-life of 7.05 days and a terminal elimination half-life of 30.9 days. The median concentration in the last week of treatment (days 22 to 28) was 30,800 ng/ml. The maximum duration of follow-up was 202 days after the start of treatment. All analyzed samples contained a concentration above the LLOQ. Miltefosine is eliminated from the body much slower than previously thought and is therefore still detectable in human plasma samples taken 5 to 6 months after the end of treatment. The presence of subtherapeutic miltefosine concentrations in the blood beyond 5 months after treatment might contribute to the selection of resistant parasites, and moreover, the measures for preventing the teratogenic risks of miltefosine treatment should be reconsidered.

Pharmacometrics Markup Language (PharmML): Opening New Perspectives for Model Exchange in Drug Development

The lack of a common exchange format for mathematical models in pharmacometrics has been a long‐standing problem. Such a format has the potential to increase productivity and analysis quality, simplify the handling of complex workflows, ensure reproducibility of research, and facilitate the reuse of existing model resources. Pharmacometrics Markup Language (PharmML), currently under development by the Drug Disease Model Resources (DDMoRe) consortium, is intended to become an exchange standard in pharmacometrics by providing means to encode models, trial designs, and modeling steps.

Treatment of hereditary angioedema with nanofiltered C1-esterase inhibitor concentrate (Cetor®): Multi-center phase II and III studies to assess pharmacokinetics, clinical efficacy and safety

From 1997, plasma-derived C1-inhibitor concentrate (Cetor®) has been available to HAE and AAE patients. Recently, a virus reducing 15 nm nanofiltration step has been introduced in the production process. A randomized, double-blind controlled cross-over study was performed to compare the pharmacokinetics (PK) of nanofiltered (C1-INH-NF) with conventional C1-inhibitor (C1-INH). Efficacy and safety were investigated in an open-label, on-demand and a prophylactic study. No differences in pharmacokinetic parameters between C1-INH and C1-INH-NF were found (13 non-symptomatic HAE patients). Both C1-inhibitor products equally increased plasma C4 levels. In the on-demand study, 14 acute angioedema attacks in 8 patients were analyzed. In the prophylactic study, 1 AAE and 5 HAE patients experienced in total 31 attacks during 748 observation days. In total 180,000 units of C1-INH-NF were administered. No product-related adverse events occurred, and no anti-C1-antibodies were induced. Nanofiltration in the production process of C1-inhibitor did not affect the pharmacokinetics, efficacy, and safety.

Model-based treatment optimization of a novel VEGFR inhibitor

AIM To evaluate dosing and intervention strategies for the phase II programme of a VEGF receptor inhibitor using PK-PD modelling and simulation, with the aim of maximizing (i) the number of patients on treatment and (ii) the average dose level during treatment. METHODS A previously developed PK-PD model for lenvatinib (E7080) was updated and parameters were re-estimated (141 patients, once daily and twice daily regimens). Treatment of lenvatinib was simulated for 16 weeks, initiated at 25 mg once daily. Outcome measures included the number of patients on treatment and overall drug exposure. A hypertension intervention design proposed for phase II studies was evaluated, including antihypertensive treatment and dose de-escalation. Additionally, a within-patient dose escalation was investigated, titrating up to 50 mg once daily unless unacceptable toxicity occurred. RESULTS Using the proposed antihypertension intervention design, 82% of patients could remain on treatment, and the mean dose administered was 21.5 mg day⁻¹. The adverse event (AE) guided dose titration increased the average dose by 4.6 mg day⁻¹, while only marginally increasing the percentage of patients dropping out due to toxicity (from 18% to 20.8%). CONCLUSIONS The proposed hypertension intervention design is expected to be effective in maintaining patients on treatment with lenvatinib. The AE-guided dose titration with blood pressure as a biomarker yielded a higher overall dose level, without relevant increases in toxicity. Since increased exposure to lenvatinib seems correlated with increased treatment efficacy, the adaptive treatment design may thus be a valid approach to improve treatment outcome.

Predictive ability of a semi-mechanistic model for neutropenia in the development of novel anti-cancer agents: two case studies

SummaryIn cancer chemotherapy neutropenia is a common dose-limiting toxicity. An ability to predict the neutropenic effects of cytotoxic agents based on proposed trial designs and models conditioned on previous studies would be valuable. The aim of this study was to evaluate the ability of a semi-mechanistic pharmacokinetic/pharmacodynamic (PK/PD) model for myelosuppression to predict the neutropenia observed in Phase I clinical studies, based on parameter estimates obtained from prior trials. Pharmacokinetic and neutropenia data from 5 clinical trials for diflomotecan and from 4 clinical trials for indisulam were used. Data were analyzed and simulations were performed using the population approach with NONMEM VI. Parameter sets were estimated under the following scenarios: (a) data from each trial independently, (b) pooled data from all clinical trials and (c) pooled data from trials performed before the tested trial. Model performance in each of the scenarios was evaluated by means of predictive (visual and numerical) checks. The semi-mechanistic PK/PD model for neutropenia showed adequate predictive ability for both anti-cancer agents. For diflomotecan, similar predictions were obtained for the three scenarios. For indisulam predictions were better when based on data from the specific study, however when the model parameters were conditioned on data from trials performed prior to a specific study, similar predictions of the drug related-neutropenia profiles and descriptors were obtained as when all data were used. This work provides further indication that modeling and simulation tools can be applied in the early stages of drug development to optimize future trials.

Oxymorphone active uptake at the blood–brain barrier and population modeling of its pharmacokinetic–pharmacodynamic relationship

The aim of this study was to characterize the blood-brain barrier (BBB) transport and pharmacokinetics-pharmacodynamics (PKPD) relationship of oxymorphone and to further elucidate its possible contribution to oxycodone analgesia. The BBB transport of oxymorphone was studied using microdialysis in male Sprague-Dawley rats. Samples from microdialysis blood and brain probes, brain tissue, and plasma were analyzed by liquid chromatography with tandem mass spectrometry. The effect was measured as tail-flick latency. The study consisted of a PKPD experiment with combined microdialysis and antinociceptive measurements (n = 8), and another antinociceptive effect experiment (n = 9) using a 10 times lower dose. The combined data were analyzed with an integrated PKPD model in nonlinear mixed effect modeling utilizing a specific method (M3) for handling missing PD observations. The concentration of unbound oxymorphone was higher in brain than in blood, with a ratio of 1.9 (RSE, 9.7%), indicating active uptake at the BBB. The integrated PKPD model described the oxymorphone BBB transport and PKPD relationship successfully, with an EC50 in the brain of 63 ng/mL, and the M3 method was able to address the issue of censored observations. Oxymorphone has active uptake transport at the BBB in rats, with moderate uptake clearance to the brain. Its contribution to analgesia after oxycodone administration is not significant.

Performance of Methods for Handling Missing Categorical Covariate Data in Population Pharmacokinetic Analyses

In population pharmacokinetic analyses, missing categorical data are often encountered. We evaluated several methods of performing covariate analyses with partially missing categorical covariate data. Missing data methods consisted of discarding data (DROP), additional effect parameter for the group with missing data (EXTRA), and mixture methods in which the mixing probability was fixed to the observed fraction of categories (MIXobs), based on the likelihood of the concentration data (MIXconc), or combined likelihood of observed covariate data and concentration data (MIXjoint). Simulations were implemented to study bias and imprecision of the methods in datasets with equal-sized and unbalanced category ratios for a binary covariate as well as datasets with non-random missingness (MNAR). Additionally, the performance and feasibility of implementation was assessed in two real datasets. At either low (10%) or high (50%) levels of missingness, all methods performed similarly well. Performance was similar for situations with unbalanced datasets (3:1 covariate distribution) and balanced datasets. In the MNAR scenario, the MIX methods showed a higher bias in the estimation of CL and covariate effect than EXTRA. All methods could be applied to real datasets, except DROP. All methods perform similarly at the studied levels of missingness, but the DROP and EXTRA methods provided less bias than the mixture methods in the case of MNAR. However, EXTRA was associated with inflated type I error rates of covariate selection, while DROP handled data inefficiently.