Population pharmacokinetics of imetelstat, a first-in-class oligonucleotide telomerase inhibitor.

Imetelstat is a novel, first-in-class, oligonucleotide telomerase inhibitor in development for the treatment of hematologic malignancies including lower-risk myelodysplastic syndromes and myelofibrosis. A nonlinear mixed-effects model was developed to characterize the population pharmacokinetics of imetelstat and identify and quantify covariates that contribute to its pharmacokinetic variability. The model was developed using plasma concentrations from 7 clinical studies including 424 patients with solid tumors or hematologic malignancies who received single-agent imetelstat via intravenous infusion at various dose levels (0.4-11.7 mg/kg) and schedules (every week to every 4 weeks). Covariate analysis included factors related to demographics, disease, laboratory results, renal and hepatic function, and antidrug antibodies. Imetelstat was described by a two-compartment, nonlinear disposition model with saturable binding/distribution and dose- and time-dependent elimination from the central compartment. Theory-based allometric scaling for body weight was included in disposition parameters. The final covariates included sex, time, malignancy, and dose on clearance; malignancy and sex on volume of the central compartment; and malignancy and spleen volume on concentration of target. Clearance in females was modestly lower, resulting in nonclinically relevant increases in predicted exposure relative to males. No effects on imetelstat pharmacokinetics were identified for mild-to-moderate hepatic or renal impairment, age, race, and antidrug antibody status. All model parameters were estimated with adequate precision (relative standard error < 29%). Visual predictive checks confirmed the capacity of the model to describe the data. The analysis supports the imetelstat body-weight-based dosing approach and lack of need for dose individualizations for imetelstat-treated patients.

Efficacy and safety exposure-response analyses of entrectinib in patients with advanced or metastatic solid tumors.

PURPOSE: Entrectinib is an anti-cancer agent that inhibits TRKA/B/C, ROS1, and ALK. Secondary pharmacokinetic (PK) exposure parameters for entrectinib derived from a previously described population PK model were used to characterize exposure-response relationships in patients treated with entrectinib. METHODS: Data were pooled from Phase 1 and 2 studies of entrectinib (600-800 mg/day in adults, 250-750 mg/m2/day in children) in 293 patients with NTRK-, ROS1-, or ALK-positive, locally advanced or metastatic tumors. Efficacy was evaluated by the changes in sum of target lesion diameters and best overall response defined by RECIST1.1. A longitudinal nonlinear mixed-effect model described the relationship between entrectinib exposure and tumor size data in patients with ROS1-positive non-small-cell lung cancer (NSCLC) or NTRK fusion-positive solid tumors. The relationship between exposure and treatment-emergent (TEAEs) or serious (SAEs) adverse events was assessed by logistic regression in all patients for whom secondary PK parameter estimates were derived. RESULTS: Among the 89 patients with evaluable efficacy data included in the exposure-efficacy analysis, 73% (65/89) achieved a complete or partial response. Entrectinib exposure distribution was similar in responders and non-responders. Model-described tumor shrinkage rates were 8-12 times greater than growth rates in both ROS-1-positive NSCLC patients and NTRK fusion-positive solid tumor patients, with no relationship between exposure and these rates. The probability of experiencing a Grade ≥ 3 TEAE or SAE increased with exposure, primarily at doses > 600 mg/day. CONCLUSION: These analyses supported that entrectinib at 600 mg/day provides an acceptable benefit-risk ratio in adults with NTRK-, ROS1-, or ALK-positive tumors, considered as rare disease.

Wide size dispersion and use of body composition and maturation improves the reliability of allometric exponent estimates.

To evaluate study designs and the influence of dispersion of body size, body composition and maturation of clearance or reliable estimation of allometric exponents. Non-linear mixed effects modeling and parametric bootstrap were employed to assess how the study sample size, number of observations per subject, between subject variability (BSV) and dispersion of size distribution affected estimation bias and uncertainty of allometric exponents. The role of covariate model misspecification was investigated using a large data set ranging from neonates to adults. A decrease in study sample size, number of observations per subject, an increase in BSV and a decrease in dispersion of size distribution, increased the uncertainty of allometric exponent estimates. Studies conducted only in adults with drugs exhibiting normal (30%) BSV in clearance may need to include at least 1000 subjects to be able to distinguish between allometric exponents of 2/3 and 1. Nevertheless, studies including both children and adults can distinguish these exponents with only 100 subjects. A marked bias of 45% (95%CI 41-49%) in the estimate of the allometric exponent of clearance was obtained when maturation and body composition were ignored in infants. A wide dispersion of body size (e.g. infants, children and adults) is required to reliably estimate allometric exponents. Ignoring differences in body composition and maturation of clearance may bias the exponent for clearance. Therefore, pharmacometricians should avoid estimating allometric exponent parameters without suitable designs and covariate models. Instead, they are encouraged to rely on the well-developed theory and evidence that clearance and volume parameters in humans scale with theory-based exponents.

Population pharmacokinetic analysis of entrectinib in pediatric and adult patients with advanced/metastatic solid tumors: support of new drug application submission.

PURPOSE: Entrectinib (ROZLYTREK®) is a CNS-active, potent, and selective inhibitor of ROS1, TRK A/B/C, and ALK kinase activity. It was recently approved for the treatment of ROS1-positive non-small cell lung cancer and NTRK gene fusion-positive solid tumors. The main objective of this analysis was to characterize the pharmacokinetics (PK) of entrectinib and its main active metabolite, M5. METHODS: A total of 276 cancer patients receiving oral entrectinib were included in the analysis. A model-based population approach was used to characterize the PK profiles of both entities using NONMEM® 7.4. A joint model captures the PK of both entrectinib and M5. The effects of pH modifiers, formulation, weight, age, and sex on model parameters were assessed. Model performance was evaluated using visual predictive checks (VPCs). RESULTS: The absorption of entrectinib was best described using a sequential zero- and first-order absorption model and the disposition with one-compartment model for each entity with linear elimination. Moderate-to-high between-patient variability was estimated in model parameters (from 30.8% for the apparent clearance of entrectinib to 122% for the first-order absorption rate constant). Theory-based allometric scaling using body weight on clearances and volumes and a 28% lower relative bioavailability of the F1 formulation in pediatric patients were retained in the model. The VPC confirmed the good predictive performance of the PopPK model. CONCLUSIONS: A robust population PK model was built and qualified for entrectinib and M5, describing linear PK for both entities. This model was used to support the ROZLYTREK® new drug application.

Physiologically Based Pharmacokinetic Modeling to Evaluate Formulation Factors Influencing Bioequivalence of Metoprolol Extended-Release Products.

The University of Florida Center for Pharmacometrics and Systems Pharmacology and the Food and Drug Administration Office of Generic Drugs have collaborated on a research project to develop a mechanism- and risk-based strategy that systematically investigates postmarketing reports of therapeutic inequivalence following the switch between brand and generic drug products. In this study we developed and qualified a physiologically based pharmacokinetic model to systematically investigate the influence of drug- and formulation-related properties on the oral absorption and bioequivalence of modified-release products using metoprolol as an example. Our findings show that the properties of the release-controlling polymer are the critical attributes for in vitro dissolution, in vivo absorption, and systemic exposure (ie, pharmacokinetics) and, thus, the bioequivalence of metoprolol extended-release products rather than the properties of the drug itself. Differences in dissolution rate can result in significant differences in maximum plasma concentration but not in area under the concentration-time curve.

Model-Based Assessment Using Conventional Bioequivalence Limits to Ensure Safety and Efficacy of Rivaroxaban in Patients Undergoing Hip or Knee Replacement.

We evaluated whether the current bioequivalence limit is adequate to ensure safety and efficacy of rivaroxaban in patients under total hip arthroplasty and total knee arthroplasty based on its model informed benefit/risk profile. Clinical data from a total of 7145 patients from 3 phase 2 and 4 phase 3 clinical trials were included in the current model-based exposure-response analysis. The relationships between rivaroxaban exposure measurements (ie, minimum or trough, maximum, average concentration, and area under the concentration-time curve [AUC] at steady state) and clinical outcomes (ie, the probabilities of major bleeding [MB] and venous thromboembolism [VTE]) were modeled using NONMEM 7.3. Model evaluation was performed using predictive checks and nonparametric bootstrap. Simulations were conducted to assess the study objectives. A shallow relationship was observed between explored exposure measurements within the tested dose range and the probability of VTE following rivaroxaban treatment. Trough concentrations were found to be a statistically significant predictor of the probability of MB. This relationship was better described using a power function. Model validation confirmed model adequacy. Based on the simulations results, the relative risk of MB of a hypothetical test product (with 20% change in AUC) will not statistically differ from the brand name drug. Twenty percent AUC variations do not change the relative risk of MB and is unlikely to compromise efficacy of therapy. A generic drug of rivaroxaban passing the typical bioequivalence assessment is expected to have similar safety and efficacy as the brand name drug.

Modelling the dose-response relationship: the fair share of pharmacokinetic and pharmacodynamic information.

AIMS: The aim of this paper is to investigate the role of drug concentration samplings in the modelling of the dose-response relationship. METHODS: Using an initial PK/PD model, a reference dataset was simulated. PK and PD samples were extracted to create reduced datasets. PK/PD and K-PD models were fitted to theses reduced datasets. Post hoc estimates from both types of models were compared to the initial PK/PD model and performance was assessed. RESULTS: K-PD models were largely biased when the drug has a nonlinear elimination. PK/PD models with 1 PK and 2 PD samples were superior to K-PD models with 3 PD samples. PK/PD models with 1 or 2 PK samples and 3 PD samples proved to be superior to K-PD models with 4 PD samples. CONCLUSIONS: K-PD models should not be used when the drug has nonlinear elimination. K-PD models should not replace PK/PD modelling but are an alternative approach if the PD information is large enough.

Modeling Testosterone Circadian Rhythm in Hypogonadal Males: Effect of Age and Circannual Variations.

The objective of this study was to characterize the baseline circadian rhythm of testosterone levels in hypogonadal men. A total of 859 baseline profiles of testosterone from hypogonadal men were included in this analysis. The circadian rhythm of the testosterone was described by a stretched cosine function. Model parameters were estimated using NONMEM(®) 7.3. The effect of different covariates on the testosterone levels was investigated. Model evaluation was performed using non-parametric bootstrap and predictive checks. A stretched cosine function deeply improved the data goodness of fit compared to the standard trigonometric function (p < 0.001; ΔOFV = -204). The effect of the age and the semester, defined as winter and spring versus summer and fall, were significantly associated with the baseline levels of testosterone (p < 0.001, ΔOFV = -15.6, and p < 0.001, ΔOFV = -47.0). Model evaluation procedures such as diagnostic plots, visual predictive check, and non-parametric bootstrap evidenced that the proposed stretched cosine function was able to model the time course of the diurnal testosterone levels in hypogonadal males with accuracy and precision. The circadian rhythm of the testosterone levels was better predicted by the proposed stretched cosine function than a standard cosine function. Testosterone levels decreased by 5.74 ng/dL (2.4%) every 10 years and were 19.3 ng/dL (8.1%) higher during winter and spring compared to summer and fall.

Population pharmacokinetic and pharmacodynamic analysis of tesamorelin in HIV-infected patients and healthy subjects.

The objective of this analysis was to characterize the time course of selected pharmacodynamic (PD) markers of tesamorelin: growth hormone (GH) and insulin-like growth factor (IGF-1) concentrations in HIV-infected patients and healthy volunteers. A total of 41 subjects in Phase I trials receiving subcutaneous daily doses of 1 or 2 mg of tesamorelin during 14 consecutive days were included in this analysis. A previous pharmacokinetic (PK) model of tesamorelin was used as the input function for the PD model of GH. Tesamorelin was hypothesized to stimulate the secretion of GH in an "episodic" manner, i.e., for a finite duration of time. The resulting PK/PD model of GH was used to describe the time course of IGF-1. The effect of age, body weight, body mass index, sex, race, and health status on the model parameters was evaluated. The model was qualified using predictive checks and non-parametric bootstrap. Within the range of the values evaluated no covariates were significantly associated with GH or IGF-1 model parameters. Model evaluation procedures indicated accurate prediction of the selected pharmacodynamic markers. The time course of GH and IGF-1 concentrations following multiple doses of tesamorelin were well predicted by the sequential PK/PD model developed using Phase I data.

Population pharmacokinetic analysis of tesamorelin in HIV-infected patients and healthy subjects.

BACKGROUND AND OBJECTIVES: Tesamorelin is a synthetic analogue of growth hormone-releasing factor (GRF), which increases basal and pulsatile growth hormone (GH) secretion and subsequently increases insulin-like growth factor (IGF)-1. Limited information is available about the pharmacokinetics of this compound. Consequently, the aim of this study was to characterize the population pharmacokinetics of tesamorelin in HIV-infected patients and healthy subjects. METHODS: A total of 38 HIV-infected patients and healthy subjects receiving subcutaneous tesamorelin doses of 1 or 2 mg administered daily during 14 consecutive days were included in the analysis. An open one-compartment model with first- and zero-order absorption and first-order elimination was developed to best describe the data using NONMEM(®) VII. The effect of different covariates on tesamorelin pharmacokinetics was investigated. Model evaluation was performed using predictive checks and non-parametric bootstrap. RESULTS: Plasma clearance and its interindividual variability [% coefficient of variation (CV)] was estimated to be 1,060 L/h (33.6 %). Volume of distribution was calculated to be 200 L (17.7 %). Age, body size measures, race and health status were not related to tesamorelin pharmacokinetic parameters within the range of covariates studied. The fraction of tesamorelin absorbed by a first-order process is 13.1 % higher on day 14 compared with day 1. Predictive checks and non-parametric bootstrap demonstrated that the model is appropriate in describing the time course of tesamorelin plasma concentrations in both HIV-infected patients and healthy subjects. CONCLUSIONS: An open one-compartment model with first and zero order absorption processes and linear elimination is suitable to characterize the pharmacokinetics of tesamorelin. The fraction of tesamorelin absorbed by a first-order process evolves with time. No clinically relevant covariates were identified as predictors of tesamorelin pharmacokinetics.

Population pharmacokinetic-pharmacodynamic analysis of neutropenia in cancer patients receiving PM00104 (Zalypsis(®)).

BACKGROUND AND OBJECTIVE: PM00104 (Zalypsis(®)) is a novel marine-derived compound that has shown antineoplastic activity against a number of human tumour cell lines. Myelosuppression was found to be a PM00104 dose-limiting toxicity during phase I studies. The objective of this study was to characterize the time course of neutropenia after intravenous PM00104 administration in cancer patients. METHODS: Absolute neutrophil counts (ANCs) and pharmacokinetic data from 144 patients receiving PM00104 doses ranging from 0.053 to 5 mg/m(2) were used to estimate the system-related (baseline ANC [Circ(0)], mean transit time [MTT], feedback on proliferation [γ] and maturation [δ]) and drug-specific (first-order elimination rate constant from effect compartment [k(e0)] [α and ß]) parameters of a modified Friberg's model. The concentrations in the effect compartment (C(e)) were assumed to reduce the proliferation rate of the progenitor cells according to the function [Formula: see text] Model evaluation and simulations were undertaken to evaluate the effect of dose intensity, dose density and the intravenous infusion duration on severe neutropenia incidence. RESULTS: The typical values (between-subject variability [%]) of the Circ(0), MTT, γ, δ, k(e0), α and ß were estimated to be 5.66 × 10(9) cells/L (13 %), 149 h (29 %), 0.136, 0.191, 0.00639 h(-1) (32 %), 0.332 L/µg (24 %) and 1.47, respectively. Age, bodyweight, sex, serum albumin, total protein, liver metastases, number of previous chemotherapy lines and performance status were not associated with model parameters. The model evaluation evidenced an accurate prediction of the neutropenia grade 3 and/or 4 incidence. Simulations indicated that PM00104 dose and dosing interval, but not infusion duration, were the main determinants of the neutropenia severity and duration. CONCLUSIONS: The time course of neutropenia following PM00104 was well characterized by the model developed. The model-predicted time course of the ANCs and its variability confirmed that neutropenia is reversible, of short duration and non-cumulative.

Population pharmacokinetics of PM00104 (Zalypsis(®)) in cancer patients.

OBJECTIVE: The aim of this study was to characterize the population pharmacokinetics of PM00104 (Zalypsis(®)) in cancer patients. METHODS: A total of 135 patients included in four phase I clinical trials who receive intravenous PM00104 at doses ranging from 53 to 5,000 µg/m(2) and administered as 1-, 3-, or 24-h infusion every 3 weeks or as 1-h infusion on days 1, 8, and 15 of a 28-day cycle, or 1-h infusion daily during 5 consecutive days every 3 weeks were included in the analysis. Pharmacokinetic data were analyzed with non-linear mixed effect model using NONMEM VI software. The effect of selected patient covariates on PM00104 pharmacokinetics was investigated. Model evaluation was performed using predictive checks and non-parametric bootstrap. RESULTS: An open four-compartment catenary linear model with first-order elimination was developed to best describe the data. Plasma clearance and its between-subject variability was 43.7 L/h (34%). Volume of distribution at steady state was 822 L (117%). Within the range of covariates studied, age, sex, body size variables, aspartate aminotransferase, alanine aminotransferase, alkaline phosphatase, total bilirubin, lactate dehydrogenase, creatinine clearance, albumin, total protein, hemoglobin, performance status, liver metastases, dose-limiting toxicity, and stable disease for 3 months were not statistically related to PM00104 pharmacokinetic parameters. Bootstrap and posterior predictive check evidenced the model was deemed appropriate to describe the time course of PM00104 plasma concentrations in cancer patients. CONCLUSIONS: The integration of phase I pharmacokinetic data demonstrated PM00104 linear elimination from plasma, dose proportionality up to 5,000 µg/m(2), and time-independent pharmacokinetics. No clinically relevant covariates were identified as predictors of PM00104 pharmacokinetics.