Modelling antibody dynamics in humans after different Ad26.COV2.S vaccination schemes.

AIMS: To develop a semimechanistic model that describes the kinetic profile and variability of antibody (Ab) concentrations following vaccination with Ad26.COV2.S at different doses and dosing intervals. METHODS: Data were collected from participants randomized into 5 clinical trials receiving the Ad26.COV2.S vaccine. The model considered key elements of humoral immune response, dose proportionality and the evolutionary processes of the immune response. Interindividual variability and covariates were explored. RESULTS: Fast and slow kinetic phases of Ab and their evolution over time were differentiated. After first and second administrations, Ab concentrations of both phases increased less than dose proportionally, indicating a saturation of B-cell production processes. Ab concentrations produced during the fast kinetic phase increased significantly after the second administration, indicating an underlying evolutive process after antigen exposures. For the slow kinetic phase, a less pronounced increase occurred after the second and third administrations but was relatively higher in subjects who had low concentrations after the first administration. Ab concentrations of the slow phase were higher in females and decreased with age. After multiple administrations, the fast phase had Ab maximum concentrations about 5 times higher than the slow phase. The limiting kinetic factors in the fast and slow phases were the elimination rates of Ab itself and Ab producing cells, respectively. CONCLUSION: The model appears suitable to quantitatively describe the inter- and intraindividual kinetics of the immune response and the impact of covariates after multiple administrations of a vaccine.

Mechanistic Model Describing the Time Course of Humoral Immunity Following Ad26.COV2.S Vaccination in Non-Human Primates.

Mechanistic modeling can be used to describe the time course of vaccine-induced humoral immunity and to identify key biologic drivers in antibody production. We used a six-compartment mechanistic model to describe a 20-week time course of humoral immune responses in 56 non-human primates (NHPs) elicited by vaccination with Ad26.COV2.S according to either a single-dose regimen (1 × 1011 or 5 × 1010 viral particles [vp]) or a two-dose homologous regimen (5 × 1010 vp) given in an interval of 4 or 8 weeks. Humoral immune responses were quantified by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike-specific binding antibody concentrations as determined by spike protein-enzyme-linked immunosorbent assay. The mechanistic model adequately described the central tendency and variability of binding antibody concentrations through 20 weeks in all vaccination arms. The estimation of mechanistic modeling parameters revealed greater contribution of the antibody production mediated by short-lived cells as compared with long-lived cells in driving the peak response, especially post second dose when a more rapid peak response was observed. The antibody production mediated by long-lived cells was identified as relevant for generating the first peak and for contributing to the long-term time course of sustained antibody concentrations in all vaccination arms. The findings contribute evidence on the key biologic components responsible for the observed time course of vaccine-induced humoral immunity in NHPs and constitute a step toward defining immune biomarkers of protection against SARS-CoV-2 that might translate across species. SIGNIFICANCE STATEMENT: We demonstrate the adequacy of a mechanistic modeling approach describing the time course of binding antibody concentrations in non-human primates (NHPs) elicited by different dose levels and regimens of Ad26.COV2.S. The findings are relevant for informing the mechanism-based accounts of vaccine-induced humoral immunity in NHPs and translational research efforts aimed at identifying immune biomarkers of protection against SARS-CoV-2 infection.

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.

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.

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.

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.

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.

Pharmacodynamic model for chemoradiotherapy-induced thrombocytopenia in mice.

A mechanistic model describing the effects of chemotherapy and radiation on platelet counts and endogenous thrombopoietin (eTPO) in mice was developed. Thrombocytopenia was induced in mice by injection of carboplatin followed by the whole body irradiation on days 0, 28, and 56, with platelet and eTPO samples collected over 84 days. The pharmacodynamic model consisted of a series of aging compartments representing proliferating megakaryocyte precursors, megakaryocytes, and platelets with possible eTPO clearance through internalization. The cytotoxic effects of treatment were described by the kinetics of the effect (K-PD) model, and stimulation of platelet production by eTPO was considered to be driven by receptor occupancy. The proposed PD model adequately described the platelet counts and eTPO concentrations in mice by accounting for nadirs and peaks of platelet count, and rebounds in eTPO time course profiles. The estimates of model parameters were in good agreement with their physiological values reported in literature for mice with platelet lifespan of 4.3 days and 185 cMpl receptors per platelet. The predicted duration of the treatment effect was 0.82 h (approximately 5 carboplatin half-lives in mice). The data was not informative about the eTPO stimulatory effect as the nominal precursor production rate was sufficient to account for platelet response to treatment. The model quantified the inverse relationship between eTPO levels and platelet counts and offered an explanation of the tolerance effect observed in the eTPO data. The simulated rebound in free receptors levels correlated with rebounds in eTPO levels. The model suggests that the duration of the toxic effects is determined by the turnover of the proliferating cells in the bone marrow. This indicates that the lifespan of the target cells (megakaryocyte precursors, megakaryocytes and platelets) is a key determinant in the duration of both drug exposure and toxicity due to treatment. The model can be extended to account for pharmacokinetics of exogenous drugs and be applied to analysis of human data.

A semi-mechanistic model of bone mineral density and bone turnover based on a circular model of bone remodeling.

Development of novel therapies for bone diseases can benefit from mathematical models that predict drug effect on bone remodeling biomarkers. Therefore, a bone cycle model (BCM) was developed that takes into consideration the concept of the basic multicellular unit and the dynamic equilibrium of bone remodeling. The model is a closed form cyclical model with four compartments representing resorption, formation, primary mineralization, and secondary mineralization. Equations describing the time course of bone turnover biomarkers were developed using the flow rate of bone cycle units (BCU) between the compartments or the amount of BCU in each compartment. A disease progression model representing bone loss in osteoporosis, a vitamin D and calcium supplementation (placebo) model, and a drug model for antiresorptive treatments were added to the model. Initial model parameter values were derived from published bone turnover data. The BCM accurately described biomarker-time profiles in postmenopausal women receiving either placebo or bisphosphonate treatment. The slow continual increase in bone mineral density (BMD) observed after 1 year of treatment was accurately described when changes in bone turnover were combined with increases in mineralization. For this purpose, the secondary mineralization compartment was replaced by three catenary chain compartments representing increasing mineral content. The refined BCM satisfactorily predicted biomarker profiles after long-term (10-year) bisphosphonate treatment. Furthermore, the model successfully described individual bone turnover markers and BMD results following treatment with denosumab in postmenopausal women. Analyses with this model could be used to optimize dosing regimens and to predict effects of novel osteoporotic treatments.

Using early biomarker data to predict long-term bone mineral density: application of semi-mechanistic bone cycle model on denosumab data.

Osteoporosis is a chronic skeletal disease characterized by low bone strength resulting in increased fracture risk. New treatments for osteoporosis are still an unmet medical need because current available treatments have various limitations. Bone mineral density (BMD) is an important endpoint for evaluating new osteoporosis treatments; however, the BMD response is often slower and less profound than that of bone turnover markers (BTMs). If the relationship between BTMs and BMD can be quantified, the BMD response can be predicted by the changes in BTM after a single dose; therefore, a decision based on BMD changes can be informed early. We have applied a bone cycle model to a phase 2 denosumab dose-ranging study in osteopenic women to quantitatively link serum denosumab pharmacokinetics, BTMs, and lumbar spine (LS) BMD. The data from two phase 3 denosumab studies in patients with low bone mass, FREEDOM and DEFEND, were used for external validation. Both internal and external visual predictive checks demonstrated that the model was capable of predicting LS BMD at the denosumab regimen of 60 mg every 6 months. It has been demonstrated that the model, in combination with the changes in BTMs observed from a single-dose study in men, is capable of predicting long-term BMD outcomes (e.g., LS BMD response in men after 1 year of treatment) in different populations. We propose that this model can be used to inform drug development decisions for osteoporosis treatment early via evaluating LS BMD response when BTM data become available in early trials.

Development and validation of an HPLC-UV method for sorafenib quantification in human plasma and application to patients with cancer in routine clinical practice.

BACKGROUND: Several factors such as low therapeutic index, large interindividual variability in systemic exposure, and the relationships between exposure and toxicity for sorafenib could justify its therapeutic drug monitoring (TDM). To support TDM, a selective and precise high-performance liquid chromatography with ultraviolet detection (HPLC-UV) method was developed and validated for the determination of sorafenib in human plasma. METHODS: After protein precipitation with acetonitrile, sorafenib and lapatinib (internal standard) were separated using isocratic elution on a Kromasil C18 column using a mobile phase of acetonitrile and 20 mmol/L ammonium acetate in a proportion 53:47 (vol/vol) pumped at a constant flow rate of 1.2 mL/min. Quantification was performed at 260 nm. Validation experiments were carried out after the guidelines for Bioanalytical Method Validation published by the Food and Drug Administration and the European Medicines Agency. RESULTS: Calibration curves were linear over the range 0.1-20 mcg/mL. Inter- and intra-day coefficients of variation were <3%. The limit of detection and the lower limit of quantification were 0.06 and 0.1 mcg/mL, respectively. Recoveries of sorafenib from plasma were >99% in all cases. CONCLUSIONS: This method was successfully applied to the determination of the drug in the plasma of 2 patients with cancer receiving sorafenib 200 and 400 mg orally twice daily, respectively, and could be useful for TDM of sorafenib in routine clinical practice.

Modeling of delays in PKPD: classical approaches and a tutorial for delay differential equations.

In pharmacokinetics/pharmacodynamics (PKPD) the measured response is often delayed relative to drug administration, individuals in a population have a certain lifespan until they maturate or the change of biomarkers does not immediately affects the primary endpoint. The classical approach in PKPD is to apply transit compartment models (TCM) based on ordinary differential equations to handle such delays. However, an alternative approach to deal with delays are delay differential equations (DDE). DDEs feature additional flexibility and properties, realize more complex dynamics and can complementary be used together with TCMs. We introduce several delay based PKPD models and investigate mathematical properties of general DDE based models, which serve as subunits in order to build larger PKPD models. Finally, we review current PKPD software with respect to the implementation of DDEs for PKPD analysis.

Model-based meta-analysis to quantify the effects of short interfering RNA therapeutics on hepatitis B surface antigen turnover in hepatitis B-infected mice.

The objective of this study was to compare the efficacy of short interfering RNA therapeutics (siRNAs) in reducing hepatitis B surface antigen (HBsAg) levels in hepatitis B-infected (HBV) mice across multiple siRNA therapeutic classes using model-based meta-analysis (MBMA) techniques. Literature data from 10 studies in HBV-infected mice were pooled, including 13 siRNAs, formulated as liposomal nanoparticles (LNPs) or conjugated to either cholesterol (chol) or N-acetylgalactosamine (GalNAc). Time course of the baseline- and placebo-corrected mean HBsAg profiles were modeled using kinetics of drug effect (KPD) model coupled to an indirect response model (IRM) within a longitudinal non-linear mixed-effects MBMA framework. Single and multiple dose simulations were performed exploring the role of dosing regimens across evaluated siRNA classes. The HBsAg degradation rate (0.72 day-1) was consistent across siRNAs but exhibited a large between-study variability of 31.4% (CV%). The siRNA biophase half-life was dependent on the siRNA class and was highest for GalNAc-siRNAs (21.06 days) and lowest for chol-siRNAs (2.89 days). ID50 estimates were compound-specific and were lowest for chol-siRNAs and highest for GalNAc-siRNAs. Multiple dose simulations suggest GalNAc-siRNAs may require between 4 and 7 times less frequent dosing at higher absolute dose levels compared to LNP-siRNAs and chol-siRNAs, respectively, to reach equipotent HBsAg-lowering effects in HBV mice. In conclusion, non-clinical HBsAg concentration-time data after siRNA administration can be described using the presented KPD-IRM MBMA framework. This framework allows to quantitatively compare the effects of siRNAs on the HBsAg time course and inform dose and regimen selection across siRNA classes. These results may support siRNA development, optimize preclinical study designs, and inform data analysis methodology of future anti-HBV siRNAs; and ultimately, support siRNA model-informed drug development (MIDD) strategies.

Model-Informed Clinical Development of Once-Every-6-Month Injection of Paliperidone Palmitate in Patients with Schizophrenia: A Pharmacometric Bridging Approach (Part I).

BACKGROUND AND OBJECTIVE: A model-informed drug development (MIDD) approach was implemented for paliperidone palmitate (PP) 6-month (PP6M) clinical development, using pharmacokinetics and pharmacokinetic/pharmacodynamic model-based simulations. METHODS: PP6M pharmacokinetics were simulated by extending the PP 3-month (PP3M) pharmacokinetic model to account for increased injection volume, and hence dose. Contribution of the MIDD approach to the design of the pivotal PP6M phase-3 study (PP6M/PP3M noninferiority study, NCT03345342) investigating schizophrenia relapse rates was twofold: (1) PP6M dose selection, and (2) hypothesis generation that lower trough concentrations (Ctrough) associated with PP6M, relative to PP3M, were not associated with lower efficacy, which was to be evaluated in the phase-3 study. Moreover, accompanied by an intense sampling scheme to adequately characterize paliperidone pharmacokinetics and to elucidate the potential relationship between concentration and safety/efficacy, the bridging strategy eliminated the need for additional phase-1/phase-2 clinical studies. RESULTS: Using a MIDD bridging strategy, PP6M doses were selected that, compared with PP3M, were expected to have a similar range of exposures and a noninferior relapse rate and safety profile. Clinical data from PP6M/PP3M noninferiority study confirmed that PP6M, compared with PP3M, had a similar range of exposures (T'jollyn et al. in Eur J Drug Metab Pharmacokinet 2024), as well as a noninferior relapse rate and safety profile (this manuscript). CONCLUSIONS: Consistency of the MIDD approach with observed clinical outcomes confirmed the hypothesis that lower Ctrough did not lead to increased relapse rates at the doses administered. Although higher paliperidone peak concentrations are achieved with corresponding doses of PP6M relative to PP3M in the phase-3 clinical study, types and incidences of treatment-related adverse events were comparable between PP6M and PP3M groups and no new safety concerns emerged for PP6M (Najarian et al. in Int J Neuropsychopharmacol 25(3):238-251, 2022).

Model-Informed Clinical Development of 6-Monthly Injection of Paliperidone Palmitate in Patients with Schizophrenia: Dosing Strategies Guided by Population Pharmacokinetic Modeling and Simulation (Part II).

BACKGROUND AND OBJECTIVE: Paliperidone palmitate 6-month (PP6M) intramuscular (IM) injection is the longest-acting treatment available for patients with schizophrenia. A population pharmacokinetic (popPK) modeling and simulation approach was deployed to inform dosing strategies for PP6M. METHODS: The extensive analysis database included 15,932 paliperidone samples from 700 patients receiving gluteal paliperidone palmitate 3-month (PP3M) or PP6M injections in the double-blind phase of a phase-3 noninferiority study (NCT03345342). Exposure parameters for paliperidone appeared to increase dose-proportionally within each dosing schedule (PP3M/PP6M). The range of paliperidone exposures after IM administration of PP6M overlaps with that of corresponding doses of oral paliperidone extended release, PP 1-month (PP1M), and PP3M. Model-based simulations were performed to investigate paliperidone exposures in different PP6M dosing scenarios and relevant subpopulations. RESULTS: A dosing window of ≤ 2 weeks earlier and ≤ 3 weeks later than the target 6-month interval for maintenance treatment with PP6M dosing maintains paliperidone exposures at levels that are not expected to substantially impact its safety and efficacy. For missed-dose scenarios, tailored re-initiation regimens are proposed that should be applied before resuming PP6M maintenance dosing. Regarding subpopulations, PP6M 700 mg eq. is the highest dose recommended in mild renal-impairment patients; the paliperidone pharmacokinetics after PP6M administration is not affected by sex, body mass index, or age in a clinically meaningful way. CONCLUSION: Paliperidone concentration-time profiles after PP6M and PP3M dosing were adequately described by the popPK model. Model-based simulation results provide guidance for clinicians on initiating PP6M therapy, transitioning between paliperidone formulations, the dosing windows to use for maintenance dosing, and managing missed PP6M doses.

Between subjects variability in haemoglobin and dose are not associated with the erythropoiesis-stimulating agent used to treat anaemia in dialysis: a meta-analysis.

AIMS: We aimed to compare mean and between subject variability in haemoglobin (Hb) and erythropoiesis-stimulating agents (ESA) dose across the ESA compounds used to treat anaemia in dialysis patients. METHODS: We performed a meta-analysis of randomized trials evaluating ESA in adult patients with chronic kidney disease on dialysis (target Hb 9-13.5 g dl(-1)), and compared mean Hb and its standard deviation (SD), and ESA dose and its coefficient of variation (CV) between the different agents [rHuEPO alfa or beta, darbepoetin alfa, pegylated-epoetin beta (PEG-EPO) or other epoetins]. The effect of route and frequency of administration, frequency of dose adjustments, study blinding and type, baseline value, Hb target and sampling frequency were also assessed. RESULTS: Among 4983 patients from 16 studies, pooled Hb mean and SD during the evaluation phase were 11.5 g dl(-1) (95% CI 11.3, 11.7) and 0.99 g dl(-1) (0.88, 1.09), respectively. The Hb mean and SD were not significantly influenced by the covariates tested. Only Hb SD was significantly lower in maintenance studies relative to correction studies. No differences in mean ESA dose and CV were found across the covariates, except that PEG-EPO monthly dose was 42% higher than the every 2 weeks dose and the rHuEPO i.v. dose was 32% higher than the s.c. dose. CONCLUSIONS: Between subject variability in haemoglobin and ESA dose in dialysis patients is not associated with the type of ESA, nor with the dosing interval or route of administration, except for higher dose requirements in PEG-EPO monthly administration relative to every 2 weeks or rHuEPO i.v. relative to s.c.

Romiplostim dose-response in patients with myelodysplastic syndromes.

AIM: To characterize the romiplostim dose-response in subjects with low or intermediate-1 risk myelodysplastic syndromes (MDS) receiving subcutaneous romiplostim. METHODS: Data from 44 MDS subjects receiving subcutaneous romiplostim (dose range 300-1500 µg week(-1) ) were used to develop a pharmacodynamic model consisting of a romiplostim-sensitive progenitor cell compartment linked to the peripheral blood compartment through four transit compartments representing the maturation in the bone marrow from megakaryocytes to platelets. A kinetics of drug effect model was used to quantify the stimulatory effect of romiplostim on the proliferation of sensitive progenitor cells and pharmacodynamics-mediated disposition was modelled by assuming the kinetics of drug effect constant (kDE ) to be proportional to the change in platelet count relative to baseline. RESULTS: The estimated values (between subject variability) for baseline platelet count, mean transit time, and kDE were 24 × 10(9) l(-1) (47%), 9.6 days (44%) and 0.28 days(-1) , respectively. MDS subjects had a shorter platelet lifespan (42 h) than healthy subjects (257 h). Romiplostim effect was described for responders (78%) and non-responders (22%). The average weekly stimulatory effect of romiplostim on the production rate of sensitive progenitor cells at baseline was 269% per 100 µg week(-1) for responders. Body weight, age, gender and race were not statistically related to romiplostim pharmacodynamic parameters. Visual predictive checks confirmed the model adequacy. CONCLUSION: The time course of platelet counts in MDS subjects receiving subcutaneous administration of escalating doses of romiplostim was characterized and showed a linear dose-response for romiplostim responders to increase the platelet counts.

Pharmacokinetic and pharmacodynamic modeling of romiplostim in animals.

PURPOSE: Romiplostim is a novel thrombopoiesis-stimulating peptibody that targets the thrombopoietin c-Mpl receptor, resulting in increased platelet production. The pharmacodynamic-mediated disposition (PDMDD) and its stimulatory effect on platelet production in Sprague-Dawley rats, rhesus monkeys, and cynomolgus monkeys following IV bolus and SC administration at various dose levels were determined. METHODS: The pharmacokinetic (PK) profile was described by a PDMDD model that accounts for romiplostim binding to the c-Mpl receptor. The PD model contained a series of aging compartments for precursor cells in bone marrow and platelets. The stimulatory function was described by an on-and-off function operating on the fractional receptor occupancy (RO). The threshold effect, RO(thr), and K(D) parameters were determinants of drug potency, whereas S(max) reflected drug efficacy. RESULTS: The model implicated that receptor-mediated clearance was negligible. RO(thr) estimated occupancies were 0.288, 0.385, 0.771 for rats, rhesus, and cynomolgus monkeys, respectively. The analogous estimated values of K(D) were 4.05, 2320, and 429 ng/mL, implying that romiplostim was much more potent in rats, which was confirmed by a dose-response (ratio of peak platelet count to baseline) relationship. CONCLUSIONS: The model adequately described romiplostim serum concentrations and platelet counts in rats, rhesus monkeys, and cynomolgus monkeys, and quantified linear clearance, PDMDD, and potency of romiplostim.

Development and validation of a high-performance liquid chromatography ultraviolet method for lapatinib quantification in human plasma.

A selective and precise high-performance liquid chromatography ultraviolet method was developed and validated for the determination of lapatinib in human plasma. After protein precipitation with acetonitrile, lapatinib and sorafenib were separated using isocratic elution (on a C18 Ultrabase column using a mobile phase of acetonitrile/20 mM ammonium acetate in a proportion 53:47 (v/v) pumped at a constant flow rate of 1.2 mL/min). Quantification was performed at 260 nm. Calibration curves were linear over the range 0.2-10 µg/mL. Inter- and intraday coefficients of variation were less than 7%. The limit of detection and the lower limit of quantification were 0.1 and 0.2 µg/mL, respectively. Recoveries of lapatinib from plasma were higher than 86.7% in all cases. The assay was applied to the determination of the drug in the plasma of 2 cancer patients receiving lapatinib, 1000 and 1250 mg orally, and could be useful for therapeutic drug monitoring of lapatinib in routine clinical practice.