Semi-physiological Enriched Population Pharmacokinetic Modelling to Predict the Effects of Pregnancy on the Pharmacokinetics of Cytotoxic Drugs.

BACKGROUND AND OBJECTIVE: As a result of changes in physiology during pregnancy, the pharmacokinetics (PK) of drugs can be altered. It is unclear whether under- or overexposure occurs in pregnant cancer patients and thus also whether adjustments in dosing regimens are required. Given the severity of the malignant disease and the potentially high impact on both the mother and child, there is a high unmet medical need for adequate and tolerable treatment of this patient population. We aimed to develop and evaluate a semi-physiological enriched model that incorporates physiological changes during pregnancy into available population PK models developed from non-pregnant patient data. METHODS: Gestational changes in plasma protein levels, renal function, hepatic function, plasma volume, extracellular water and total body water were implemented in existing empirical PK models for docetaxel, paclitaxel, epirubicin and doxorubicin. These models were used to predict PK profiles for pregnant patients, which were compared with observed data obtained from pregnant patients. RESULTS: The observed PK profiles were well described by the model. For docetaxel, paclitaxel and doxorubicin, an overprediction of the lower concentrations was observed, most likely as a result of a lack of data on the gestational changes in metabolizing enzymes. For paclitaxel, epirubicin and doxorubicin, the semi-physiological enriched model performed better in predicting PK in pregnant patients compared with a model that was not adjusted for pregnancy-induced changes. CONCLUSION: By incorporating gestational changes into existing population pharmacokinetic models, it is possible to adequately predict plasma concentrations of drugs in pregnant patients which may inform dose adjustments in this population.

Does nonlinear blood-brain barrier transport matter for (lower) morphine dosing strategies?

Morphine blood-brain barrier (BBB) transport is governed by passive diffusion, active efflux and saturable active influx. This may result in nonlinear plasma concentration-dependent brain extracellular fluid (brainECF) pharmacokinetics of morphine. In this study, we aim to evaluate the impact of nonlinear BBB transport on brainECF pharmacokinetics of morphine and its metabolites for different dosing strategies using a physiologically based pharmacokinetic simulation study. We extended the human physiologically based pharmacokinetic LeiCNS-PK3.0, model with equations for nonlinear BBB transport of morphine. Simulations for brainECF pharmacokinetics were performed for various dosing strategies: intravenous (IV), oral immediate (IR) and extended release (ER) with dose range of 0.25-150 mg and dosing frequencies of 1-6 times daily. The impact of nonlinear BBB transport on morphine CNS pharmacokinetics was evaluated by quantifying (i) the relative brainECF to plasma exposure (AUCu,brainECF/AUCu,plasma) and (ii) the impact on the peak-to-trough ratio (PTR) of concentration-time profiles in brainECF and plasma. We found that the relative morphine exposure and PTRs are dose dependent for the evaluated dose range. The highest relative morphine exposure value of 1.4 was found for once daily 0.25 mg ER and lowest of 0.1 for 6-daily 150 mg IV dosing. At lower doses the PTRs were smaller and increased with increasing dose and stabilized at higher doses independent of dosing frequency. Relative peak concentrations of morphine in relation to its metabolites changed with increasing dose. We conclude that nonlinearity of morphine BBB transport affects the relative brainECF exposure and the fluctuation of morphine and its metabolites mainly at lower dosing regimens.

Allele-specific collateral and fitness effects determine the dynamics of fluoroquinolone resistance evolution.

Collateral sensitivity (CS), which arises when resistance to one antibiotic increases sensitivity toward other antibiotics, offers treatment opportunities to constrain or reverse the evolution of antibiotic resistance. The applicability of CS-informed treatments remains uncertain, in part because we lack an understanding of the generality of CS effects for different resistance mutations, singly or in combination. Here, we address this issue in the gram-positive pathogen Streptococcus pneumoniae by measuring collateral and fitness effects of clinically relevant gyrA and parC alleles and their combinations that confer resistance to fluoroquinolones. We integrated these results in a mathematical model that allowed us to evaluate how different in silico combination treatments impact the dynamics of resistance evolution. We identified common and conserved CS effects of different gyrA and parC alleles; however, the spectrum of collateral effects was unique for each allele or allelic pair. This indicated that allelic identity can impact the evolutionary dynamics of resistance evolution during monotreatment and combination treatment. Our model simulations, which included the experimentally derived antibiotic susceptibilities and fitness effects, and antibiotic-specific pharmacodynamics revealed that both collateral and fitness effects impact the population dynamics of resistance evolution. Overall, we provide evidence that allelic identity and interactions can have a pronounced impact on collateral effects to different antibiotics and suggest that these need to be considered in models examining CS-based therapies.

Population Pharmacokinetics of Unbound and Total Teicoplanin in Critically Ill Pediatric Patients.

BACKGROUND AND OBJECTIVES: Teicoplanin is a highly protein-bound antibiotic, increasingly used to treat serious Gram-positive infections in critically ill children. Maturational and pathophysiological intensive care unit-related changes often lead to altered pharmacokinetics. In this study, the objectives were to develop a pediatric population-pharmacokinetic model of unbound and total teicoplanin concentrations, to investigate the impact of plasma albumin levels and renal function on teicoplanin pharmacokinetics, and to evaluate the efficacy of the current weight-based dosing regimen. METHODS: An observational pharmacokinetic study was performed and blood samples were collected for quantification of unbound and total concentrations of teicoplanin after the first dose and in assumed steady-state conditions. A population-pharmacokinetic analysis was conducted using a standard sequential approach and Monte Carlo simulations were performed for a probability of target attainment analysis using previously published pharmacokinetic-pharmacodynamic targets. RESULTS: A two-compartment model with allometric scaling of pharmacokinetic parameters and non-linear plasma protein binding best described the data. Neither the inclusion of albumin nor the renal function significantly improved the model and no other covariates were supported for inclusion in the final model. The probability of target attainment analysis showed that the standard dosing regimen does not satisfactory attain the majority of the proposed targets. CONCLUSIONS: We successfully characterized the pharmacokinetics of unbound and total teicoplanin in critically ill pediatric patients. The highly variable unbound fraction of teicoplanin could not be predicted using albumin levels, which may support the use of therapeutic drug monitoring of unbound concentrations. Poor target attainment was shown for the most commonly used dosing regimen, regardless of the pharmacokinetic-pharmacodynamic target evaluated.

Model Evaluation of Continuous Data Pharmacometric Models: Metrics and Graphics.

This article represents the first in a series of tutorials on model evaluation in nonlinear mixed effect models (NLMEMs), from the International Society of Pharmacometrics (ISoP) Model Evaluation Group. Numerous tools are available for evaluation of NLMEM, with a particular emphasis on visual assessment. This first basic tutorial focuses on presenting graphical evaluation tools of NLMEM for continuous data. It illustrates graphs for correct or misspecified models, discusses their pros and cons, and recalls the definition of metrics used.

Integrated Simulation Framework for Toxicity, Dose Intensity, Disease Progression, and Cost Effectiveness for Castration-Resistant Prostate Cancer Treatment With Eribulin.

Quantitative model-based analyses are helpful to support decision-making in drug development. In oncology, disease progression/clinical outcome (DPCO) models have been used for early predictions of clinical outcome, but most of such approaches did not include adverse events or dose intensity. In addition, cost-effectiveness evaluations of investigational compounds are becoming increasingly important. Here, we developed an integrated model-based framework including relevant treatment effects for patients with castration-resistant prostate cancer treated with the anticancer agent eribulin. The framework included (i) a DPCO model relating prostate-specific antigen (PSA) dynamics to survival; (ii) models for adverse events including dose-limiting neutropenia and other graded toxicities; (iii) a model for Eastern Cooperative Oncology Group (ECOG) performance score; (iv) a model for dropout; (v) the consideration of cost effectiveness. The model allowed simulation of realistic treatment courses. Subsequently, simulations evaluating alternative treatment protocols or patient characteristics were performed in order to derive inferences on expected efficacy and cost effectiveness.

Disease Progression/Clinical Outcome Model for Castration-Resistant Prostate Cancer in Patients Treated With Eribulin.

Frameworks that associate cancer dynamic disease progression models with parametric survival models for clinical outcome have recently been proposed to support decision making in early clinical development. Here we developed such a disease progression clinical outcome model for castration-resistant prostate cancer (CRPC) using historical phase II data of the anticancer agent eribulin. Disease progression was captured using the dynamics of prostate-specific antigen (PSA). For clinical outcome, overall survival (OS) was used. The model for PSA dynamics comprised parameters for baseline PSA (23.2 ng/ml, relative standard error (RSE) 16.5%), growth rate (0.00879 day(-1), RSE 12.6%), drug effect (0.241 µg·h·l(-1) day(-1), RSE 32.6%), and resistance development (0.0113 day(-1), RSE 44.3%). OS was modeled according to a Weibull distribution. Predictors for survival included model-predicted PSA time to nadir (TTN), PSA growth rate, Eastern Cooperative Oncology Group (ECOG) score, and baseline PSA. The developed framework can be considered to support informative design and analysis of drugs developed for CRPC.

Real world cost of human epidermal receptor 2-positive metastatic breast cancer patients: a longitudinal incidence-based observational costing study in the Netherlands and Belgium.

Currently, no country-specific metastatic breast cancer (MBC) observational costing data are available for the Netherlands and Belgium. Our aim is to describe country-specific resource use and costs of human epidermal receptor 2 (HER-2)-positive MBC in the Netherlands and Belgium, making use of real-world data. The eligibility period for patient selection was from April 2004 to April 2010. Inclusion and retrospective data collection begins at the time of first diagnosis of HER-2-positive MBC during the eligibility period and ends 24 months post-index diagnosis of MBC or at patient death. We identified 88 eligible patients in the Netherlands and 44 patients in Belgium. The total costs of medical treatment and other resource use utilisation per patient was €48,301 in the Netherlands and €37,431 in Belgium. Majority of costs was related to the use of trastuzumab in both countries, which was 50% of the total costs in the Netherlands and 56% in Belgium respectively. Our study provides estimates of resource use and costs for HER-2-positive MBC in the Netherlands and Belgium. We noticed various differences in resource use patterns between both countries demonstrating caution is needed when transferring cost estimates between countries.

Optimizing anticancer drug treatment in pregnant cancer patients: pharmacokinetic analysis of gestation-induced changes for doxorubicin, epirubicin, docetaxel and paclitaxel.

BACKGROUND: Pregnant patients with cancer are increasingly treated with anticancer drugs, although the specific impact of pregnancy-induced physiological changes on the pharmacokinetics (PK) of anticancer drugs and associated implications for optimal dose regimens remains unclear. Our objectives were to quantify changes in PK during pregnancy for four frequently used anticancer agents doxorubicin, epirubicin, docetaxel and paclitaxel, and to determine associated necessary dose adjustments. PATIENTS AND METHODS: A pooled analysis of PK data was carried out for pregnant (Pr) and nonpregnant (NPr) patients for doxorubicin (n = 16 Pr/59 NPr), epirubicin (n = 14 Pr/57 NPr), docetaxel (n = 3 Pr/32 NPr) and paclitaxel (n = 5 Pr/105 NPr). Compartmental nonlinear mixed effect models were used to describe the PK and gestational effects. Subsequently, we derived optimized dose regimens aiming to match to the area under the concentration-time curve (AUC) in nonpregnant patients. RESULTS: The effect of pregnancy on volumes of distribution for doxorubicin, epirubicin, docetaxel and paclitaxel were estimated as fold-change of <1.32, <2.08, <1.37 and <4.21, respectively, with adequate precision [relative standard error (RSE) <37%]. For doxorubicin, no gestational effect could be estimated on clearance (CL). For epirubicin, docetaxel and paclitaxel, a fold-change of 1.1 (RSE 9%), 1.19 (RSE 7%) and 1.92 (RSE 21%) were, respectively, estimated on CL. Calculated dose adjustment requirements for doxorubicin, epirubicin, docetaxel and paclitaxel were +5.5%, +8.0%, +16.9% and +37.8%, respectively. Estimated changes in infusion duration were marginal (<4.2%) except for paclitaxel (-21.4%). CONCLUSION: Clinicians should be aware of a decrease in drug exposure during pregnancy and should not a priori reduce dose. The decrease in exposure was most apparent for docetaxel and paclitaxel which is supported by known physiological changes during pregnancy. The suggested dose adaptations should only be implemented after conduct of further confirmatory studies of the PK during pregnancy.

Time-dependent resource use and costs associated with different states of disease in patients diagnosed with HER-2-positive metastatic breast cancer.

Adequate reflection of disease progression and costs over time is essential in cost-effectiveness analyses based on health state-transition models. However, costing studies normally investigate the burden of metastatic breast cancer (MBC) without explicitly examining the impact of specific-disease states on health care costs over time. The objective of this study was to assess time-dependent costs of different health states of human epidermal receptor-2 (HER-2) positive MBC and the factors contributing to these costs. In the Netherlands, HER-2-positive MBC patients were identified in three different hospitals. Resource use was collected during 24 months, which was linked to unit costs and related to time with respect to date of MBC diagnosis, disease progression and death for each individual patient. Subsequently, monthly costs for different health states were calculated. Finally, a nonlinear mixed-effect modelling approach was used to provide a quantitative description of the time course of cumulative progression costs. Costs during stable disease were constant over time with a mean of $4,158. In contrast, monthly costs for progressive disease demonstrated a change over time with the largest costs in the first 2 months after diagnosis (p < 0.005). The developed mixed-effect model adequately described cumulative cost-time course and associated variability. During the last months of life, costs varied over time, with the last month of life as the most expensive one with a mean of $5,811 per patient per month. To reflect costs of HER-2-positive MBC accurately in Markov models, costs for stable disease can be defined time independent, however, costs of progressive disease should be defined time dependent, and costs related to the final months of life should be modelled as such. The mixed-effect model we have developed could now be considered for adequate description of the time-dependent cost of progressive disease.

Pharmacokinetics and clinical efficacy of phenobarbital in asphyxiated newborns treated with hypothermia: a thermopharmacological approach.

BACKGROUND AND OBJECTIVES: Therapeutic hypothermia can influence the pharmacokinetics and pharmacodynamics of drugs, the discipline which is called thermopharmacology. We studied the effect of therapeutic hypothermia on the pharmacokinetics of phenobarbital in asphyxiated neonates, and the clinical efficacy and the effect of phenobarbital on the continuous amplitude-integrated electroencephalography (aEEG) in a prospective study. PATIENTS AND METHODS: Data were obtained from the prospective SHIVER study, performed in two of the ten Dutch level III neonatal intensive care units. Phenobarbital data were collected between 2008 and 2010. Newborns were eligible for inclusion if they had a gestational age of at least 36 weeks and presented with perinatal asphyxia and encephalopathy. According to protocol in both hospitals an intravenous (repeated) loading dose of phenobarbital 20 mg/kg divided in 1-2 doses was administered if seizures occurred or were suspected before or during the hypothermic phase. Phenobarbital plasma concentrations were measured in plasma using a fluorescence polarization immunoassay. aEEG was monitored continuously. RESULTS AND CONCLUSION: A one-compartmental population pharmacokinetic/pharmacodynamic model was developed using a multi-level Markov transition model. No (clinically relevant) effect of moderate therapeutic hypothermia on phenobarbital pharmacokinetics could be identified. The observed responsiveness was 66%. While we still advise an initial loading dose of 20 mg/kg, clinicians should not be reluctant to administer an additional dose of 10-20 mg/kg. An additional dose should be given before switching to a second-line anticonvulsant drug. Based on our pharmacokinetic/pharmacodynamic model, administration of phenobarbital under hypothermia seems to reduce the transition rate from a continuous normal voltage (CNV) to discontinuous normal voltage aEEG background level in hypothermic asphyxiated newborns, which may be attributed to the additional neuroprotection of phenobarbital in infants with a CNV pattern.

Population pharmacokinetic-pharmacodynamic analysis of trastuzumab-associated cardiotoxicity.

Trastuzumab treatment is associated with cardiac dysfunction. The aim of this study was to develop a population pharmacokinetic-pharmacodynamic (PK-PD) model for the relationship between left ventricular ejection fraction (LVEF) and trastuzumab exposure and to identify associated clinically relevant covariates. Data from an unselected cohort of patients with early and advanced HER2-positive breast cancer receiving treatment with trastuzumab were analyzed using a nonlinear mixed-effects modeling approach. LVEF values from 240 patients were available. The data were best described by an effect-compartment model. The population LVEF recovery half-life after trastuzumab treatment (T(½rec)) was estimated at 49.7 days. The cumulative anthracycline dose was a significant determinant of the half maximal effect concentration (EC50), causing a 45.9% increase in sensitivity (decrease in EC50) at the maximum cumulative anthracycline dose. The developed population PK-PD model may be used to establish optimal treatment and cardiac monitoring strategies for trastuzumab.

Acute psychomotor, memory and subjective effects of MDMA and THC co-administration over time in healthy volunteers.

In Western societies a considerable percentage of young people expose themselves to the combination of 3,4-methylenedioxymethamphetamine (MDMA or 'ecstasy') and cannabis. The aim of the present study was to assess the acute effects of co-administration of MDMA and THC (the main psychoactive compound of cannabis) on pharmacokinetics, psychomotor performance, memory and subjective experience over time. We performed a four-way, double blind, randomized, crossover, placebo-controlled study in 16 healthy volunteers (12 male, four female) between the ages of 18 and 27. MDMA (100 mg) was given orally, THC (4, 6, and 6 mg, interval of 90 min) was vaporized and inhaled. THC induced more robust cognitive impairment compared with MDMA, and co-administration did not exacerbate single drug effects on cognitive function. However, co-administration of THC with MDMA increased desired subjective drug effects and drug strength compared with the MDMA condition, which may explain the widespread use of this combination.

Efficacy of 3,4-diaminopyridine and pyridostigmine in the treatment of Lambert-Eaton myasthenic syndrome: a randomized, double-blind, placebo-controlled, crossover study.

3,4-Diaminopyridine and pyridostigmine are widely used to treat Lambert-Eaton myasthenic syndrome (LEMS), either alone or in combination. 3,4-Diaminopyridine enhances the release of acetylcholine at the neuromuscular synapse, and pyridostigmine inhibits the degradation of this neurotransmitter. Although this could lead to a synergistic effect on neuromuscular transmission, no studies have compared the effects of these drugs in patients with LEMS. Therefore, we performed a placebo-controlled, double-dummy, double-blind, randomized, crossover study in nine patients with LEMS.