A theoretical framework for estimation of AUCs in complete and incomplete sampling designs.

Nonclinical in vivo animal studies have to be completed before starting clinical studies of the pharmacokinetic behavior of a drug in humans. The drug exposure in animal studies is often measured by the area under the concentration versus time curve (AUC). The classic complete data design, where each animal is sampled for analysis once per time point, is usually only applicable for large animals. In the case of rats and mice, where blood sampling is restricted, the batch design or the serial sampling design needs to be considered. In batch designs samples are taken more than once from each animal, but not at all time points. In serial sampling designs only one sample is taken from each animal. In this paper we present an estimator for the AUC from 0 to the last time point that is applicable to all three designs. The variance and asymptotic distribution of the estimator are derived and confidence intervals based upon the asymptotic results are discussed and evaluated in a simulation study. Further, we define an estimator for linear combinations of AUCs and investigate its asymptotic properties mathematically as well as in simulation

Population pharmacokinetic modeling and simulation of immunoglobulin exposure with varying dosing intervals of subcutaneous immunoglobulin 20% (Ig20Gly) in patients with primary immunodeficiency diseases

Background Immunoglobulin (IG) replacement therapy in patients with primary immunodeficiency diseases (PID) can be administered daily to every 2 weeks subcutaneously (SCIG) or every 3 or 4 weeks intravenously (IVIG). Objectives Develop a population pharmacokinetic (PK) model simulating IG exposure with Ig20Gly, a 20% SCIG; determine the dose adjustment factor for Ig20Gly relative to IVIG. Methods Data from patients with PID treated with Ig20Gly and IVIG 10% were used to characterize IG population PK by nonlinear mixed-effects modeling and validated using data splitting and a visual predictive check. IG profiles were simulated for 1000 patients/interval treated with Ig20Gly (daily, every 2 days, every 3 days, twice weekly, weekly, every 2 weeks). An Ig20Gly adjustment factor of 130% was used to simulate Ig20Gly to IVIG AUC ratios for weekly or every 2 weeks Ig20Gly dosing intervals and a monthly IVIG dosing interval. Results A 1-compartment model, using weight as a covariate on clearance, derived from an index modeling dataset (n = 81) demonstrated predictability for a validation dataset (n = 21). The model estimate of bioavailability was 73.9%. Simulations for 6 dosing intervals showed similar mean profiles with overlapping prediction intervals. Mean AUC ratios of Ig20Gly to IVIG with a dose adjustment factor of 1.30:1 were 98.7% for weekly and 97.7% for twice-weekly administration demonstrating comparable exposure. Conclusion Ig20Gly exposures from daily to up to every 2 weeks appeared equivalent. A 1.30 conversion factor provided coverage comparable to IVIG when Ig20Gly is administered daily to every 2 weeks

Modeling to predict factor VIII levels associated with zero bleeds in patients with severe hemophilia A initiated on tertiary prophylaxis

Background Factor VIII (FVIII) trough levels > 1 IU/dL in patients with severe hemophilia A receiving regular prophylaxis may optimize bleed protection. Objectives In this post hoc analysis of patients receiving tertiary prophylaxis for approximately 1 year, the relationship between estimated FVIII levels and reported bleeds was investigated to predict the potential for zero bleeds. Methods Sixty-three patients (median [range] age, 28 [7–59] years) with severe hemophilia A (229 bleeds) were included. FVIII levels at time of each bleed were estimated from single-dose individual pharmacokinetics. The highest estimated FVIII level at which patients experienced a bleed was considered the “potentially effective trough level” for that bleed type. Kaplan–Meier estimates of proportions of patients with no bleeds above certain estimated FVIII levels were determined. Those not experiencing a bleed in the trial were assumed to have a bleed at 0 IU/dL (pragmatic approach) or at their median trough level (conservative approach). Results Kaplan–Meier estimates based on pragmatic approach predicted zero all bleeds, joint bleeds, and spontaneous joint bleeds in 1 year in 40, 43, and 63% of patients, respectively, when the potentially effective trough FVIII level was set at 1 IU/dL. Between 1 and 10 IU/dL, every 1 IU/dL rise in estimated FVIII level was associated with an additional 2% of patients having zero all bleeds. Conclusion This post hoc analysis confirms benefits with trough levels of approximately 1 to 3 IU/dL in most patients starting tertiary prophylaxis; prophylaxis with higher trough levels may help patients to achieve zero bleeds

SHP656, a polysialylated recombinant factor VIII (PSA-rFVIII): First-in-human study evaluating safety, tolerability and pharmacokinetics in patients with severe haemophilia A

Introduction SHP656 is the first factor VIII (FVIII) product developed using polysialylation (PSA) technology, in which full‐length recombinant (r) FVIII (anti‐haemophilic factor [recombinant]) is conjugated with a 20 kDa PSA polymer. Aim To compare the safety, immunogenicity and pharmacokinetics of SHP656 vs the parent rFVIII (octocog alfa) after single infusions of 25‐75 IU/kg in patients with severe haemophilia A (FVIII activity <1%). Methods Multinational, phase 1, prospective, open‐label, two‐period, fixed‐sequence, dose‐escalation trial (clinicaltrials.gov NCT02716194). Patients received single doses of rFVIII and then SHP656 sequentially at the same dose: 25 ± 3 IU/kg (Cohort 1), 50 ± 5 IU/kg (Cohort 2) and 75 ± 5 IU/kg (Cohort 3). Results Forty patients received rFVIII: 11 in Cohort 1, 16 in Cohort 2 and 13 in Cohort 3. Two patients withdrew before receiving SHP656, leaving 38 patients who completed the study and received both treatments. No treatment‐related adverse events (AEs), serious AEs, deaths, study withdrawals, thrombotic events or allergic reactions were reported; and no significant treatment‐related changes in laboratory parameters or vital signs. No patients developed FVIII inhibitors or antibodies to PSA. FVIII activity was significantly prolonged following SHP656 administration vs rFVIII with an approximately 1.5‐fold extension in mean residence time (P < .05). Exposure increased proportional to the SHP656 dose over the 25‐75 IU/kg dose range

Non-compartmental estimation of pharmacokinetic parameters for flexible sampling designs

Pharmacokinetic (PK) studies aim to understand the kinetics of absorption, distribution, metabolism and elimination of a drug. Typically, such studies involve measuring the concentration of the drug in the plasma or blood at several time points after drug administration. In studying the PK behaviour, either the non-compartmental approach or alternatively a modelling approach can be utilized. Traditionally, the non-compartmental approach makes minimal assumptions about the data-generating process but requires the data to be collected in a very structured way. Conversely, the modelling approach depends heavily on assumptions about the data-generating process but does not impose a specific data structure. In this paper, we will discuss non-compartmental methods for estimating the area under the concentration versus time curve and other common PK parameters that use minimal assumptions about the data structure making it applicable to a wide range of PK studies. We will evaluate the methods using simulation and give an illustrative example

Recurrent events modelling of haemophilia bleeding events

A pharmacokinetic-pharmacodynamic (PK-PD) approach is developed for modelling recurrent bleeding events in patients with severe haemophilia to investigate the relationship between factor VIII plasma activity level and the instantaneous risk of a bleed. The model incorporates patient-level pharmacokinetic (PK) information obtained through measurements taken prior to the study which are used to fit a non-linear mixed effects two-compartment PK model. Dosing times within the study are combined with the PK model to provide the estimated factor VIII plasma level for all patients, which is used as a time dependent covariate within the recurrent events model. Methods are developed to correct the attenuation in covariate effects that would otherwise arise due to the discrepancy between estimated and true factor VIII. In contrast to existing methods proposed for such data, such as count data regression or time-to-event analysis, the new method allows all the bleeding times to be used to investigate the relationship between current factor VIII and risk of a bleed. The performance of the proposed estimators are assessed via simulation and found to outperform the naive estimator, which treats the estimated factor VIII levels as if they were measured without error, both in terms of bias and mean squared error

Estimation of AUC from 0 to Infinity in Serial Sacrifice Designs.

Nonclinical in vivo animal studies have to be completed before starting clinical studies of the pharmacokinetic behavior of a drug in humans. The drug exposure in animal studies is often measured by the area under the concentration time curve (AUC). The classical complete data design where each animal is sampled for analysis once per time point is usually only applicable for large animals. In the case of rats and mice, where blood sampling is restricted, the batch design or the serial sacrifice design need to be considered. In batch designs samples are taken more than once from each animal, but not at all time points. In serial sacrifice designs only one sample is taken from each animal. This paper presents an estimator for AUC from 0 to infinity in serial sacrifice designs, the corresponding variance and its asymptotic distribution

Simultaneous confidence intervals by iteratively adjusted alpha for relative effects in the one-way layout.

A bootstrap based method to construct 1 � α simultaneous confidence intervals for relative effects in the one-way layout is presented. This procedure takes the stochastic correlation between the test statistics into account and results in narrower simultaneous confidence intervals than the application of the Bonferroni correction. Instead of using the bootstrap distribution of a maximum statistic, the coverage of the confidence intervals for the individual com- parisons are adjusted iteratively until the overall confidence level is reached. Empirical coverage and power estimates of the introduced procedure for many-to-one comparisons are presented and compared with asymptotic procedures based on the multivariate normal distribution