Pharmacodynamic-Mediated Drug Disposition (PDMDD) Model of Daratumumab Monotherapy in Patients with Multiple Myeloma.

BACKGROUND AND OBJECTIVE: We aimed to quantify the daratumumab concentration- and CD38 dynamics-dependent pharmacokinetics using a pharmacodynamic mediated disposition model (PDMDD) in patients with multiple myeloma (MMY) following daratumumab IV or SC monotherapy. Daratumumab, a human IgG monoclonal antibody targeting CD38 with a direct on-tumor and immunomodulatory mechanism of action, has been approved to treat patients with multiple myeloma (MM). METHODS: In total, 7788 daratumumab plasma samples from 850 patients with diagnosis of MMY were used. The serum concentration-time data of daratumumab were analysed using nonlinear mixed-effects modeling with NONMEM®. The PDMDD with quasi steady-state approximation (QSS) was compared to the previously developed Michaelis-Menten (MM) approximation with respect to the parameter estimates, the goodness-of-fit plots and prediction-corrected visual predictive check, as well as model-based simulations. The effect of patients' covariates on daratumumab pharmacokinetics was also investigated. RESULTS: The QSS approximation characterized the concentration- and CD38 dynamics-dependency of daratumumab pharmacokinetics within the doses ranging from 0.1 to 24 mg/kg after IV administration and 1200 and 1800 mg after SC administration in patients with MMY, mechanistically describing the binding of daratumumab and CD38, the internalization of the daratumumab-CD38 complex and the CD38 turnover. Compared to the previously developed MM approximation, the MM approximation with the non-constant total target and dose-correction provided substantial improvement of the model fit, but it was still not as good as the QSS approximation. The effect of the previously identified covariates as well as the newly identified covariate (baseline M protein) on daratumumab pharmacokinetics was confirmed, but the magnitude of the effect was deemed not clinically relevant. CONCLUSIONS: Accounting for the CD38 turnover and its binding capacity to daratumumab, the QSS approximation provided a mechanistic interpretation of daratumumab PK parameters and consequently well described the concentration- and CD38 dynamics-dependency of daratumumab pharmacokinetics. CLINICAL STUDIES INCLUDED IN THE ANALYSIS WERE REGISTERED WITH THE NCT NUMBER BELOW AT HTTP://WWW. CLINICALTRIALS: GOV : MMY1002 (ClinicalTrials.gov: NCT02116569), MMY1003 (NCT02852837), MMY1004 (NCT02519452), MMY1008 (NCT03242889), GEN501 (NCT00574288), MMY2002 (NCT01985126), MMY3012 (NCT03277105).

Plasma and Liver Pharmacokinetics of the N-Acetylgalactosamine Short Interfering RNA JNJ-73763989 in Recombinant Adeno-Associated-Hepatitis B Virus-Infected Mice.

JNJ-73763989 is an N-acetylgalactosamine conjugated short interfering RNA combination product consisting of two triggers in clinical development for chronic hepatitis B virus (HBV) infection treatment that induces a selective degradation of all HBV mRNA transcripts. Our aim is to characterize the plasma and liver pharmacokinetics (PK) of JNJ-73763989 after intravenous and subcutaneous administration in recombinant adeno-associated (rAAV) HBV infected mice. Forty-two male rAAV-HBV infected C57Bl/6 mice received JNJ-73763989 doses of 10 mg/kg i.v. or 1, 3 and 10 mg/kg s.c. Plasma and liver concentrations were analyzed simultaneously using nonlinear mixed-effects modeling with the NONMEM 7.4. A population PK model consisting of a two-compartment disposition model with transporter-mediated drug disposition, including internalization to the liver compartment, linear elimination from plasma and liver, and first-order absorption following subcutaneous administration, was suitable to describe both plasma and liver PK. After subcutaneous dosing, absolute bioavailability was complete and flip-flop kinetics were observed. JNJ-73763989 distributes from plasma to liver via transporter-mediated liver internalization in less than 24 hours, with sustained (>42 days) liver exposure. The saturation of transporter-mediated liver internalization was hypothesized to be due to asialoglycoprotein receptor saturation. Increasing the dose decreased the relative liver uptake efficiency in mice for intravenously and, to a lesser extent, subcutaneously administered JNJ-73763989. Lower dose levels administered subcutaneously in mice can maximize the proportion of the dose reaching the liver. SIGNIFICANCE STATEMENT: Pharmacokinetic modeling of JNJ-73763989 liver and plasma concentration-time data in mice indicated that the proportion of JNJ-73763989 reaching the liver may be increased by administering lower subcutaneous doses compared to higher intravenous doses. Model-based simulations can be applied to optimize the dose and regimen combination.

Exposure-response analyses of erdafitinib in patients with locally advanced or metastatic urothelial carcinoma.

BACKGROUND: Exposure-response analyses were conducted to explore the relationship between selected efficacy and safety endpoints and serum phosphate (PO4) concentrations, a potential biomarker of efficacy and safety, in locally advanced or metastatic urothelial carcinoma patients with FGFR alterations treated with erdafitinib. METHODS: Data from two dosing regimens of erdafitinib in a phase 2 study (NCT02365597), 6 and 8-mg/day with provision for pharmacodynamically guided titration per serum PO4 levels, were analyzed using Cox proportional hazard or logistic regression models. Efficacy endpoints were overall survival (OS), progression-free survival (PFS), and objective response rate (ORR). Safety endpoints were adverse events typical for FGFR inhibitors. RESULTS: Exposure-efficacy analyses on 156 patients (6-mg = 68; 8-mg = 88) showed that patients with higher serum PO4 levels within the first 6 weeks showed better OS (hazard ratio 0.57 [95% CI 0.46-0.72] per mg/dL of PO4; p = 0.01), PFS (hazard ratio 0.80 [0.67-0.94] per mg/dL of PO4; p = 0.01), and ORR (odds ratio 1.38 [1.02-1.86] per mg/dL of PO4; p = 0.04). Exposure-safety analyses on 177 patients (6-mg = 78; 8-mg = 99) showed that the incidence of selected adverse events associated with on-target off-tumor effects significantly rose with higher PO4. CONCLUSIONS: The exploratory relationship between serum PO4 levels and efficacy/safety outcomes supported the use of pharmacodynamically guided dose titration to optimize erdafitinib's therapeutic benefit/risk ratio. CLINICAL TRIAL REGISTRATION NUMBER: NCT02365597.

Erdafitinib's effect on serum phosphate justifies its pharmacodynamically guided dosing in patients with cancer.

A population pharmacokinetic (PK)-pharmacodynamic (PD) model was developed using data from 345 patients with cancer. The population PK-PD model evaluated the effect of erdafitinib total and free plasma concentrations on serum phosphate concentrations after once-daily oral continuous (0.5-12 mg) and intermittent (10-12 mg for 7 days on/7 days off) dosing, and investigated the potential covariates affecting erdafitinib-related changes in serum phosphate levels. Phosphate is used as a biomarker for erdafitinib's efficacy and safety: increases in serum phosphate were observed after dosing with erdafitinib, which were associated with fibroblast growth factor receptor target engagement via inhibition of renal fibroblast growth factor 23-mediated signaling. PK-PD model-based simulations were performed to assess the approved PD-guided dosing algorithm of erdafitinib (8 mg once-daily continuous dosing, with up-titration to 9 mg based on phosphate levels [<5.5 mg/dl] and tolerability at 14-21 days of treatment). The serum phosphate concentrations increased after the first dose and reached near maximal level after 14 days of continuous treatment. Serum phosphate increased with erdafitinib free drug concentrations: doubling the free concentration resulted in a 1.8-fold increase in drug-related phosphate changes. Dose adjustment after at least 14 days of dosing was supported by achievement of >95% maximal serum phosphate concentration. The peak-to-trough fluctuation within a dosing interval was limited for serum phosphate concentrations (5.68-5.65 mg/dl on Day 14), supporting phosphate monitoring at any time relative to dosing. Baseline phosphate was higher in women, otherwise, none of the investigated covariate-parameter relationships were considered clinically relevant. Simulations suggest that the starting dose of 8-mg with up-titration to 9-mg on Days 14-21 maximized the number of patients within the target serum phosphate concentrations (5.5-7 mg/dl) while limiting the number of treatment interruptions. The findings from the PK-PD model provided a detailed understanding of the erdafitinib concentration-related phosphate changes over time, which supports erdafitinib's dosing algorithm.

A quantitative systems pharmacology model for acute viral hepatitis B.

Hepatitis B liver infection is caused by hepatitis B virus (HBV) and represents a major global disease problem when it becomes chronic, as is the case for 80-90% of vertical or early life infections. However, in the vast majority (>95%) of adult exposures, the infected individuals are capable of mounting an effective immune response leading to infection resolution. A good understanding of HBV dynamics and the interaction between the virus and immune system during acute infection represents an essential step to characterize and understand the key biological processes involved in disease resolution, which may help to identify potential interventions to prevent chronic hepatitis B. In this work, a quantitative systems pharmacology model for acute hepatitis B characterizing viral dynamics and the main components of the innate, adaptive, and tolerant immune response has been successfully developed. To do so, information from multiple sources and across different organization levels has been integrated in a common mechanistic framework. The final model adequately describes the chronology and plausibility of an HBV-triggered immune response, as well as clinical data from acute patients reported in the literature. Given the holistic nature of the framework, the model can be used to illustrate the relevance of the different immune pathways and biological processes to ultimate response, observing the negligible contribution of the innate response and the key contribution of the cellular response on viral clearance. More specifically, moderate reductions of the proliferation of activated cytotoxic CD8+ lymphocytes or increased immunoregulatory effects can drive the system towards chronicity.

Delay differential equations based models in NONMEM.

Delay differential equations (DDEs) are commonly used in pharmacometric models to describe delays present in pharmacokinetic and pharmacodynamic data analysis. Several DDE solvers have been implemented in NONMEM 7.5 for the first time. Two of them are based on algorithms already applied elsewhere, while others are extensions of existing ordinary differential equations (ODEs) solvers. The purpose of this tutorial is to introduce basic concepts underlying DDE based models and to show how they can be developed using NONMEM. The examples include previously published DDE models such as logistic growth, tumor growth inhibition, indirect response with precursor pool, rheumatoid arthritis, and erythropoiesis-stimulating agents. We evaluated the accuracy of NONMEM DDE solvers, their ability to handle stiff problems, and their performance in parameter estimation using both first-order conditional estimation (FOCE) and the expectation-maximization (EM) method. NONMEM control streams and excerpts from datasets are provided for all discussed examples. All DDE solvers provide accurate and precise solutions with the number of significant digits controlled by the error tolerance parameters. For estimation of population parameters, the EM method is more stable than FOCE regardless of the DDE solver.

Clopidogrel, a CYP2C8 inhibitor, causes a clinically relevant increase in the systemic exposure to the active metabolite of selexipag in healthy subjects.

AIMS: Selexipag is a prostacyclin receptor agonist approved for the treatment of pulmonary arterial hypertension. Cytochrome P450 (CYP) 2C8 is involved in the metabolism of selexipag and its active metabolite, ACT-333679. This study evaluated the interaction of selexipag and clopidogrel, a CYP2C8 inhibitor. METHODS: The study had a 2-treatment, 1-sequence, crossover design. Pharmacokinetics (PK) and CYP2C8 genotype were assessed in healthy male subjects administered selexipag (200 µg twice daily [b.i.d.]) alone or with clopidogrel (300 mg single dose or 75 mg once daily [o.d.]). PK modelling and simulation were conducted to support dosing recommendations. RESULTS: Clopidogrel had a comparatively small effect on selexipag (<1.5-fold difference in any PK variable). For ACT-333679, the major contributor to the drug effect, the area under the plasma concentration-time curve during a dose interval and the maximum plasma concentration increased 2.25-fold (90% confidence interval [CI] 2.06, 2.46) and 1.69-fold (90% CI 1.55, 1.84), respectively with clopidogrel 300 mg and 2.70-fold (90% CI 2.45, 2.96) and 1.90-fold (90% CI 1.72, 2.11), respectively with clopidogrel 75 mg. The effect of clopidogrel on selexipag and ACT-333679 exposure was comparable for all identified CYP2C8 genotypes. PK simulations predicted comparable exposure to ACT-333679 following selexipag 400 µg b.i.d., 400 µg o.d. in combination with clopidogrel 75 mg o.d and 200 µg b.i.d. with clopidogrel 75 mg o.d. CONCLUSION: Results suggest that ACT-333679 exposure can be maintained within the therapeutic range by reducing selexipag dosing frequency to o.d. or dose to half, when selexipag is coadministered with clopidogrel.

Nicotine Population Pharmacokinetics in Healthy Smokers After Intravenous, Oral, Buccal and Transdermal Administration.

BACKGROUND: In 4 decades, numerous nicotine replacement therapy products have been developed. Population pharmacokinetic models can support exposure-response modeling and inform nicotine replacement therapy product development, but only limited model-based cross-study population pharmacokinetic analyses for nicotine replacement therapy products have been published. OBJECTIVES: The aim of this retrospective analysis was to assess the population pharmacokinetics of nicotine across intravenous, oral, transdermal and oromucosal (mouth spray, chewing gum, lozenge and inhaler) routes and formulations in healthy smoking subjects. METHODS: Data on 930 unique subjects (46,016 observations) from 29 single- and repeated-dose studies with multiple formulations across intravenous, oral, transdermal and oromucosal routes of administration were included. Data from intravenous and extravascular routes of administration were modelled separately for run efficiency reasons. For developing extravascular models, clearance and disposition parameters and their inter-individual variabilities were fixed to the estimates for intravenously delivered nicotine. Detectable pre-dose nicotine concentrations were modelled as a hypothetical nicotine bolus into the central compartment at the start of wash-out. Modelling repeated-dose oral and buccal administrations required a time-dependent increase in clearance or decrease in bioavailability to describe the data adequately. RESULTS: Disposition of intravenous nicotine was best described by a three-compartment model with initial and terminal half-lives of 7 min and 4.5 h, respectively, and the absorption of single oral doses was best described with a first-order absorption rate constant of 1.55 h-1. The data of buccal formulations were modelled with parallel oromucosal absorption and gastrointestinal absorption of a part of the dose that is swallowed. For transdermal nicotine, parallel zero- and first-order release from the patch and a transit-compartment absorption model best described the data. Key pharmacokinetic parameters were reliably estimated, with typical values for clearance (67 L/h for a 70-kg subject), volume of distribution (4.3 L/kg), oral bioavailability (40%) and transdermal bioavailability (76%) within expected ranges. The estimated fraction of the dose swallowed for buccal formulations ranged from 55% (gum) to 69% (lozenge). CONCLUSIONS: Robust population pharmacokinetic models were developed for five nicotine replacement therapy product types and for intravenous and oral nicotine. These population pharmacokinetic models are used in exposure-response analyses and simulation-based nicotine replacement therapy product design.

Efficacy and Safety Exposure-Response Relationships of Apalutamide in Patients with Nonmetastatic Castration-Resistant Prostate Cancer.

PURPOSE: To evaluate the relationship between exposure of apalutamide and its active metabolite, N-desmethyl-apalutamide, and selected clinical efficacy and safety parameters in men with high-risk nonmetastatic castration-resistant prostate cancer. PATIENTS AND METHODS: An exploratory exposure-response analysis was undertaken using data from the 1,207 patients (806 apalutamide and 401 placebo) enrolled in the SPARTAN study, including those who had undergone dose reductions and dose interruptions. Univariate and multivariate Cox regression models evaluated the relationships between apalutamide and N-desmethyl-apalutamide exposure, expressed as area under the concentration-time curve at steady state, and metastasis-free survival (MFS). Univariate and multivariate logistic regression models assessed the relationship between apalutamide and N-desmethyl-apalutamide exposure and common treatment-emergent adverse events including fatigue, fall, skin rash, weight loss, and arthralgia. RESULTS: A total of 21% of patients in the apalutamide arm experienced dose reductions diminishing the average daily dose to 209 mg instead of 240 mg. Within the relatively narrow exposure range, no statistically significant relationship was found between MFS and apalutamide and N-desmethyl-apalutamide exposure. Within apalutamide-treated subjects, skin rash and weight loss had a statistically significant association with higher apalutamide exposure. CONCLUSIONS: The use of apalutamide at the recommended dose of 240 mg once daily provided a similar delay in metastases across the SPARTAN patient population, regardless of exposure. The exploratory exposure-safety analysis supports dose reductions in patients experiencing adverse events.

Quantification of Radiation Injury on Neutropenia and the Link between Absolute Neutrophil Count Time Course and Overall Survival in Nonhuman Primates Treated with G-CSF.

PURPOSE: To model absolute neutrophil count (ANC) suppression in response to acute radiation (AR) exposure and evaluate ANC time course as a predictor of overall survival (OS) in response to AR exposure with or without treatment with granulocyte colony-stimulating factor in nonhuman primates. METHODS: Source data were obtained from two pivotal studies conducted in rhesus macaques exposed to 750 cGy of whole body irradiation on day 0 that received either placebo, daily filgrastim, or pegfilgrastim (days 1 and 8 after irradiation). Animals were observed for 60 days with ANC measured every 1 to 2 days. The population model of ANC response to AR and the link between observed ANC time course and OS consisted of three submodels characterizing injury due to radiation, granulopoiesis, and a time-to-event model of OS. RESULTS: The ANC response model accurately described the effects of AR exposure on the duration of neutropenia. ANC was a valid surrogate for survival because it explained 76% (95% CI, 41%-97%) and 73.2% (95% CI, 38.7%-99.9%) of the treatment effect for filgrastim and pegfilgrastim, respectively. CONCLUSION: The current model linking radiation injury to neutropenia and ANC time course to OS can be used as a basis for translating these effects to humans.

Prediction of Survival Benefit of Filgrastim in Adult and Pediatric Patients With Acute Radiation Syndrome.

Acute exposure to high doses of radiation leads to severe myelosuppression, but few treatments are currently available to treat hematopoietic syndrome of acute radiation syndrome. Granulocyte colony stimulating factors (e.g., filgrastim) stimulate proliferation of neutrophil precursors and enhance mature neutrophil function. Owing to ethical constraints on conducting clinical research in lethally irradiated humans, we developed a model-based strategy to integrate preclinical experience in irradiated nonhuman primates (NHPs) and other clinical myelosuppressive conditions to inform filgrastim dosing to treat hematopoietic syndrome of acute radiation syndrome. Models predicting neutrophil counts and overall survival based on drug exposures were calibrated and scaled from NHPs to adult and pediatric human subjects. Several scenarios were examined investigating variations in filgrastim doses, dose frequency, treatment initiation, and duration, as well as the effect of age and radiation dose rate. Model-based simulations and established safety profiles supported that a subcutaneous filgrastim dose of 10 µg/kg once daily provides a significant survival benefit (50%) over placebo in both adults and children, provided that the treatment is initiated within 1-14 days after radiation exposure and lasts 2-3 weeks. For treatment durations of longer than 3 weeks, filgrastim treatment is not expected to provide significantly greater benefit. This survival benefit is expected to hold for the wide range of radiation doses and dose rates (0.01-1,000 Gy/hours) examined.

Relating Nicotine Plasma Concentration to Momentary Craving Across Four Nicotine Replacement Therapy Formulations.

Tobacco use is a major health concern. To assist smoking cessation, nicotine replacement therapy (NRT) is used to reduce nicotine craving. We quantitatively described the relationship between nicotine pharmacokinetics (PKs) from NRTs and momentary craving, linking two different pharmacodynamic (PD) scales for measuring craving. The dataset comprised retrospective data from 17 clinical studies and included 1,077 adult smokers with 39,802 craving observations from four formulations: lozenge, gum, mouth spray, and patch. A PK/PD model was developed that linked individual predicted nicotine concentrations with the categorical and visual analogue PD scales through a joint bounded integer model. A maximum effect model, accounting for acute tolerance development, successfully related nicotine concentrations to momentary craving. Results showed that all formulations were similarly effective in reducing craving, albeit with a fourfold lower potency for the patch. Women were found to have a higher maximal effect of nicotine to reduce craving, compared with men.

Population Pharmacokinetics of Total and Free Erdafitinib in Adult Healthy Volunteers and Cancer Patients: Analysis of Phase 1 and Phase 2 Studies.

A population pharmacokinetic (PK) model was developed using data pooled from 6 clinical studies (3 in healthy volunteers and 3 in cancer patients) to characterize total and free plasma concentrations of erdafitinib following single- and multiple-dose administration, to understand clinically relevant covariates, and to quantify the inter- and intraindividual variability in erdafitinib PK. An open, linear, 3-compartment disposition model with first-order absorption and a lag time was used to describe the PK profile of total and free erdafitinib plasma concentrations. The PK of erdafitinib were linear and time independent. After oral administration, erdafitinib was rapidly absorbed, with a time to maximum concentration between 2 and 4 hours. In patients, erdafitinib total apparent oral clearance was 0.200 L/h (median free fraction = 0.24%), and the effective terminal half-life of total drug was 76.4 hours. Interindividual variability in PK parameters was moderate for oral clearance and central volume of distribution, and large for absorption rate and peripheral volume of distribution. Sex and renal function were significant covariates on free oral clearance, while weight, sex, and α1 -acid-glycoprotein were significant on oral central volume of distribution. Age, race, and mild hepatic impairment were not significant covariates of erdafitinib exposure. Given that the magnitude of the covariate effects were within 25% of reference values and that the recommended dosing regimen of erdafitinib comprises individual dose up-titrations and reductions based on presence or absence of toxicities, the clinical relevance of the investigated covariates is expected to be limited, and no dose adjustments are warranted.

Population Pharmacokinetics of Apalutamide and its Active Metabolite N-Desmethyl-Apalutamide in Healthy and Castration-Resistant Prostate Cancer Subjects.

BACKGROUND: Apalutamide is a next-generation androgen receptor inhibitor approved for treatment of subjects with high-risk, non-metastatic, castration-resistant prostate cancer (NM-CRPC). OBJECTIVE: The objective of this study was to characterize the population pharmacokinetics of apalutamide and its metabolite N-desmethyl-apalutamide in healthy male and castration-resistant prostate cancer subjects. METHODS: Plasma concentration data for apalutamide and N-desmethyl-apalutamide from 1092 subjects (seven clinical studies) receiving oral apalutamide (30-480 mg) once daily were pooled for a population pharmacokinetic analysis using a non-linear mixed-effect modelling approach. The impact of clinically relevant covariates was also assessed. RESULTS: Apalutamide absorption was rapid, and the apparent steady-state volume of distribution was large (276 L), reflecting a wide body distribution. Apalutamide was eliminated slowly, with its apparent clearance increasing from 1.31 L/h after the first dose to 2.04 L/h at steady state. No evidence of time-dependent disposition was observed for N-desmethyl-apalutamide, which was also widely distributed and slowly cleared (1.5 L/h). After 4 weeks of treatment, more than 95% of steady-state exposure of apalutamide and N-desmethyl-apalutamide was reached. At a dose of apalutamide 240 mg/day, apalutamide and N-desmethyl-apalutamide exposure exhibited 5.3- and 85.2-fold accumulation in plasma, respectively. Inter-individual variability in apalutamide apparent clearance is low (< 20%). Among the covariates evaluated, apalutamide and N-desmethyl-apalutamide exposure were statistically associated only with health status, body weight, and albumin concentration, and the effect was low (< 25%). CONCLUSIONS: A population pharmacokinetic modelling approach was successfully applied to describe the pharmacokinetics of apalutamide and N-desmethyl-apalutamide. No clinically relevant covariates were identified as predictors of apalutamide and N-desmethyl-apalutamide pharmacokinetics.

Effect of Macitentan on the Pharmacokinetics of the Breast Cancer Resistance Protein Substrates, Rosuvastatin and Riociguat, in Healthy Male Subjects.

BACKGROUND: Macitentan is a clinically approved endothelin receptor antagonist for the treatment of pulmonary arterial hypertension (PAH). Increasing use of combination drug therapy in PAH means that it is important to recognize potential drug-drug interactions (DDIs) that could affect the efficacy and safety of macitentan in patients with PAH. OBJECTIVE: Two Phase 1 studies were conducted to investigate the effect of macitentan at steady-state on the pharmacokinetics of the breast cancer resistance protein (BCRP) substrates, rosuvastatin and riociguat in healthy male subjects. Another objective was to determine the safety and tolerability of concomitant administration of rosuvastatin or riociguat with macitentan. METHODS: Healthy male subjects received a single oral dose of rosuvastatin 10 mg (n = 20) or riociguat 1 mg (n = 20) on Day 1 (reference treatment). A loading oral dose of macitentan 30 mg was administered on Day 5 followed by macitentan 10 mg once-daily from Day 6 to Day 15 (riociguat study) or Day 6 to Day 16 (rosuvastatin study). A concomitant oral dose of rosuvastatin 10 mg or riociguat 1 mg was administered on Day 10 (test treatment). Pharmacokinetics were evaluated for 96 h after treatment on Day 1 and for 144 h (riociguat study) or 168 h (rosuvastatin study) after treatment on Day 10. To compare the reference and test treatments, the geometric mean ratio was calculated for the maximum plasma concentration (Cmax), the area under the plasma concentration-time curve (AUC) from zero (pre-dose) to time of the last measured concentration above the limit of quantification (AUC0-t), the AUC from zero to infinity (AUC0-∞) and the terminal elimination half-life (t½) of rosuvastatin, riociguat and riociguat's metabolite, M1. The difference in the time to reach maximum plasma concentration (tmax) was determined by the Wilcoxon test. Trough levels of macitentan and its metabolite, ACT-132577, were measured and safety was monitored throughout. RESULTS: Ninety percent confidence intervals of the geometric mean ratios were within the bioequivalence criteria of 0.80-1.25. There was no significant difference between test and reference tmax. Rosuvastatin or riociguat did not affect the steady-state concentrations of macitentan and ACT-132577. The adverse event profile was consistent with the known safety profiles of the drugs. CONCLUSIONS: Macitentan 10 mg did not affect the pharmacokinetics of BCRP substrates, rosuvastatin or riociguat in healthy male subjects. EudraCT numbers: 2017-003095-31 and 2017-003502-41.

Assessment of the effect of erdafitinib on cardiac safety: analysis of ECGs and exposure-QTc in patients with advanced or refractory solid tumors.

PURPOSE: To characterize the effect of erdafitinib on electrocardiogram (ECG) parameters and the relationship between erdafitinib plasma concentrations and QTc interval changes in patients with advanced or refractory solid tumors. METHODS: Triplicate ECGs and continuous 12-lead Holter data were collected in the dose escalation part (Part 1) of the first-in-human study, with doses ranging from 0.5 to 12 mg. Triplicate ECG monitoring continued in Parts 2-4 where 2 dose regimens selected from Part 1 were expanded in prespecified tumor types. Analyses of ECG data included central tendency analyses, identification of categorical outliers and morphological assessment. A concentration-QTc analysis was conducted using a linear mixed-effect model based on extracted time matching Holter data. RESULTS: Central tendency, categorical outlier, and ECG morphologic analyses from 187 patients revealed no clinically significant effect of erdafitinib on heart rate, atrioventricular conduction or cardiac depolarization (PR and QRS), and no effect on cardiac repolarization (QTc). Concentration-QTc analysis from 62 patients indicated that the slopes of relationship between total and free erdafitinib plasma concentrations and QTcI (mean exponent of 0.395) were estimated as - 0.00269 ms/(ng/mL) and - 1.138 ms/(ng/mL), respectively. The predicted change in QTcI at the observed geometric mean of total and free concentration at the highest therapeutic erdafitinib dose (9 mg daily) was < 10 ms at the upper bound of the two-sided 90% confidence interval. CONCLUSIONS: ECG data and the concentration-QTc relationships demonstrate that erdafitinib does not prolong QTc interval and has no effects on cardiac repolarization or other ECG parameters. Clinical trial registration numbers NCT01703481, EudraCT: 2012-000697-34.

Population pharmacokinetics of trabectedin in adolescent patients with cancer.

PURPOSE: To characterize the trabectedin population pharmacokinetics in children and adolescent patients with cancer and compare it with the trabectedin pharmacokinetics in adults. METHODS: Plasma concentrations from ten adolescent and three children with cancer (age range 4.0-17.0 years) treated with trabectedin at doses ranging from 1.1 to 1.7 mg/m2, administered as a 24-h continuous intravenous infusion every 3 weeks, were available for the analysis. An external model evaluation was performed to verify whether a previously developed adult population pharmacokinetic model was predictive of the pediatric plasma concentrations of trabectedin. The maximum a posteriori estimation of the individual pharmacokinetic parameters for pediatric patients was conducted, after successful completion of the external evaluation step. The relationships between pharmacokinetic parameters and body size were evaluated. RESULTS: External evaluation methods showed no major differences between the adult population and children and adolescent patients of this study. The mean ± standard deviation (SD) of the individual estimated clearance and central volume of distribution in these children/adolescent patients was 36.4 ± 16.1 L/h and 13.2 ± 6.54 L, respectively. These values were similar to the typical values reported for adult patients-37.6 L/h and 13.9 L (for females) and 16.1 L (for males). The median area under the plasma concentration versus time curve (AUC) in children/adolescent patients was 55.1 µg h/L, while in the adult population the median AUC was 61.3 µg h/L, both administered a 1.5 mg/m2 dose regimen with mean (range) BSA for adults = 1.86 (0.90-2.80) vs children/adolescent patients = 1.49 (0.66-2.54). CONCLUSIONS: The adult population pharmacokinetic model adequately described the trabectedin plasma concentrations and its variability in the pediatric population of patients involved in this assessment that mostly comprised adolescents. The trabectedin systemic exposure achieved in this population was comparable (within 12%) to the exposure obtained in adult population when the same dose, expressed in mg/m2, was administered.

Immune network for viral hepatitis B: Topological representation.

The liver is a well-known immunotolerogenic environment, which provides the adequate setting for liver infectious pathogens persistence such as the hepatitis B virus (HBV). Consequently, HBV infection can derive in the development of chronic disease in a proportion of the patients. If this situation persists in time, chronic hepatitis B (CHB) would end in cirrhosis, hepatocellular carcinoma and eventually, the death of the patient. It is thought that this immunotolerogenic environment is the result of complex interactions between different elements of the immune system and the viral biology. Therefore, the purpose of this work is to unravel the mechanisms implied in the development of CHB and to design a tool able to help in the study of adequate therapies. Firstly, a conceptual framework with the main components of the immune system and viral dynamics was constructed providing an overall insight on the pathways and interactions implied in this disease. Secondly, a review of the literature was performed in a modular fashion: (i) viral dynamics, (ii) innate immune response, (iii) humoral and (iv) cellular adaptive immune responses and (v) tolerogenic aspects. Finally, the information collected was integrated into a single topological representation that could serve as the plan for the systems pharmacology model architecture. This representation can be considered as the previous unavoidable step to the construction of a quantitative model that could assist in biomarker and target identification, drug design and development, dosing optimization and disease progression analysis.

Pharmacokinetic-pharmacodynamic modelling of neutrophil response to G-CSF in healthy subjects and patients with chemotherapy-induced neutropenia.

AIM: The objective of the present study was to use pharmacokinetic-pharmacodynamic modelling to characterize the effects of chemotherapy on the granulopoietic system and to predict the absolute neutrophil counts (ANCs) for patients with chemotherapy-induced neutropenia treated with filgrastim and pegfilgrastim. METHODS: Data were extracted from 10 phase I-III studies conducted in 110 healthy adults, and 618 adult and 52 paediatric patients on chemotherapy following administration of filgrastim or pegfilgrastim. The structural model accounted for ANC dynamics and the effects of filgrastim and pegfilgrastim, chemotherapy and corticosteroids. The impact of neutrophils on drug disposition was based on a drug receptor-binding model that assumed quasi-equilibrium and stimulation of the production and maturation of neutrophils upon treatment. The chemotherapy and corticosteroid effects were represented by kinetic-pharmacodynamic-type models, where chemotherapy stimulated elimination of neutrophil precursors at the mitotic stage, and corticosteroids stimulated neutrophil production. RESULTS: The systemic half-lives of filgrastim (2.6 h) and pegfilgrastim (10.1 h) were as expected. The effective half-life of chemotherapy was 9.6 h, with a 2-day killing effect. The rate of receptor elimination from mitotic compartments exhibited extreme interindividual variability (% coefficient of variation >200), suggesting marked differences in sensitivity to chemotherapy effects on ANCs. The stimulatory effects of pegfilgrastim were significantly greater than those of filgrastim. Model qualification confirmed the predictive capability of this model. CONCLUSION: This qualified model simulates the time course of ANC in the absence or presence of chemotherapy and predicts nadir, time to nadir and time of recovery from different grades of neutropenia upon treatment with filgrastim and pegfilgrastim.

A cell-level model of pharmacodynamics-mediated drug disposition.

We aimed to develop a cell-level pharmacodynamics-mediated drug disposition (PDMDD) model to analyze in vivo systems where the PD response to a drug has an appreciable effect on the pharmacokinetics (PK). An existing cellular level model of PD stimulation was combined with the standard target-mediated drug disposition (TMDD) model and the resulting model structure was parametrically identifiable from typical in vivo PK and PD data. The PD model of the cell population was controlled by the production rate k in and elimination rate k out which could be stimulated or inhibited by the number of bound receptors on a single cell. Simulations were performed to assess the impact of single and repeated dosing on the total drug clearance. The clinical utility of the cell-level PDMDD model was demonstrated by fitting published data on the stimulatory effects of filgrastim on absolute neutrophil counts in healthy subjects. We postulated repeated dosing as a means of detecting and quantifying PDMDD as a single dose might not be sufficient to elicit the cellular response capable of altering the receptor pool to visibly affect drug disposition. In the absence of any PD effect, the model reduces down to the standard TMDD model. The applications of this model can be readily extended to include chemotherapy-induced cytopenias affecting clearance of endogenous hematopoietic growth factors, different monoclonal antibodies and immunogenicity effects on PK.