In silico evaluation of limited blood sampling strategies for individualized recombinant factor IX prophylaxis in hemophilia B patients

Predictive performance of pharmacokinetic-guided prophylactic dosing of factor concentrates in hemophilia A and B

Background

Pharmacokinetic (PK)-guided dosing is used to individualize factor (F)VIII and FIX replacement therapy.

Objectives

This study investigates the reliability and feasibility of PK-guided prophylactic dosing of factor concentrates in hemophilia A and B.

Methods

In this multicenter, prospective cohort study, people of all ages with hemophilia received prophylactic treatment with factor concentrates based on individual PK parameters. During follow-up, at least 4 measured FVIII/FIX levels per patient were compared with corresponding predicted levels obtained by Bayesian forecasting. Predictive performance was defined as adequate when ≥80% of measured FVIII/FIX levels were within ±25% of prediction (relative error). Additionally, mean absolute error and mean error were calculated. In post hoc analyses, predictive performance was assessed allowing maximum absolute errors of 1 (trough), 5 (mid), and 15 (peak) IU/dL. Five-point scale questionnaires addressed feasibility of PK guidance.

Results

We included 50 patients (median age, 19 years; range: 2-72 years). Median follow-up was 36 weeks. Seventy-one percent of levels (58% trough, 83% mid, and 80% peak) were within ±25% of prediction. Mean absolute errors were 0.8 (trough), 2.0 (mid), and 8.6 (peak) IU/dL. In post hoc analyses, 81% (trough), 96% (mid), and 82% (peak) of levels were within set limits. Patients reported low burden and high satisfaction.

Conclusion

PK-guided dosing was reliable according to post hoc analyses, based on low absolute errors that were regarded as clinically irrelevant in most cases. The predefined predictive performance was achieved in mid and peak factor levels but not in trough factor levels due to measurement inaccuracy. PK guidance also seemed feasible.

Limited sampling strategies for individualized BAX 855 prophylaxis in severe hemophilia A: in silico evaluation

OBJECTIVE

Limited sampling strategies (LSS) lower the burden of pharmacokinetic (PK)-guided dosing, but an extensive evaluation of LSS for BAX 855 (Adynovi) is currently lacking. This study aimed to develop a LSS for BAX 855 and combine this with a LSS of a standard half-life (SHL) factor VIII (FVIII) concentrate in a clinical setting.

METHODS

Individual PK parameters of BAX 855 were estimated for 10 000 virtual patients with severe hemophilia A using Monte Carlo simulations. Several LSS consisting of 2-6 samples were examined based on patient burden, bias and accuracy of clearance, elimination half-life, volume of distribution and trough levels at 72 h (C72). Analyses were performed separately for adults and children <12 years.

RESULTS

The preferred LSS for BAX 855 consisted of three sampling points at 15-30 min, 48 h and 72 h for both adults (mean accuracy C72: 14.0% vs. 10.8% using six samples) and children (mean accuracy C72: 14.9% vs. 11.4% using six samples). The best strategy with two samples (peak, 48 h) resulted in an adequate, but lower accuracy than strategies with ≥3 samples (mean accuracy C72: 22.3%). The optimal combination of the LSS of SHL FVIII and BAX 855 led to six samples during four clinical visits.

CONCLUSION

This in silico study has identified that two to three samples are necessary to estimate the individual PK of BAX-855 adequately. These samples can be collected in one or two clinical visits. When combining PK profiling of SHL FVIII and BAX 855, six samples during four clinical visits are needed.

In silico evaluation of limited sampling strategies for individualized dosing of extended half-life factor IX concentrates in hemophilia B patients

PURPOSE

Hemophilia B is a bleeding disorder, caused by a factor IX (FIX) deficiency. Recently, FIX concentrates with extended half-life (EHL) have become available. Prophylactic dosing of EHL-FIX concentrates can be optimized by assessment of individual pharmacokinetic (PK) parameters. To determine these parameters, limited sampling strategies (LSSs) may be applied. The study aims to establish adequate LSSs for estimating individual PK parameters of EHL-FIX concentrates using in silico evaluation.

METHODS

Monte Carlo simulations were performed to obtain FIX activity versus time profiles using published population PK models for N9-GP (Refixia), rFIXFc (Alprolix), and rIX-FP (Idelvion). Fourteen LSSs, containing three or four samples taken within 8 days after administration, were formulated. Bayesian analysis was applied to obtain estimates for clearance (CL), half-life (t_1/2), time to 1% (Time_1%), and calculated weekly dose (Dose_1%). Bias and precision of these estimates were assessed to determine which LSS was adequate.

RESULTS

For all PK parameters of N9-GP, rFIXFc and rIX-FP bias was generally acceptable (range: -5% to 5%). For N9-GP, precision of all parameters for all LSSs was acceptable (< 25%). For rFIXFc, precision was acceptable for CL and Time_1%, except for t_1/2 (range: 27.1% to 44.7%) and Dose_1% (range: 12% to 29.4%). For rIX-FP, all LSSs showed acceptable bias and precision, except for Dose_1% using LSS with the last sample taken on day 3 (LSS 6 and 10).

CONCLUSION

Best performing LSSs were LSS with samples taken at days 1, 5, 7, and 8 (N9-GP and rFIXFc) and at days 1, 4, 6, and 8 (rIX-FP), respectively.

Development and Validation of a Population-Pharmacokinetic Model for Rurioctacog Alfa Pegol (Adynovate®): A Report on Behalf of the WAPPS-Hemo Investigators Ad Hoc Subgroup

BACKGROUND AND OBJECTIVE

Rurioctacog alfa pegol (Adynovate) is a modified recombinant factor VIII concentrate used for treating hemophilia A. Aiming to improve treatment tailoring on the Web-Accessible Population Pharmacokinetic Service-Hemophilia (WAPPS-Hemo) platform for patients of all ages treated with Adynovate, we have developed and evaluated a population pharmacokinetic (PopPK) model. On the platform, PopPK models are used as priors for Bayesian forecasting that derive individual PK of hemophilia patients and are subsequently used for personalized dose regimen design.

METHODS

Factor activity measurements and demographic covariate data from patients infused with Adynovate were extracted from the WAPPS-Hemo database. Evaluations testing the appropriateness of Bayesian forecasting included 10-fold cross validation, a limited sampling analysis (LSA), and an external evaluation using additional independent data extracted from the WAPPS-Hemo database at a later date.

RESULTS

The model was constructed using 650 plasma factor activity observations (555 one stage assay and 95 chromogenic assay - 4.6% below limit of quantification) measured in 154 patients from 36 hemophilia centres. A two-compartment model including between subject variability on clearance and central volume was selected as the base model. Covariates were fat free mass on clearance and central volume, age on clearance and assay type on activity. The final model was well-suited to predict PK parameters of new individuals (n = 26) from sparse observations.

CONCLUSIONS

The development of a PopPK model for Adynovate using real-world data increases the covariate space (e.g. age) beyond what is possible from clinical trial data. This model is available on the WAPPS-Hemo platform for tailoring treatment in hemophilia A patients.

Clinical, pharmacokinetic and economic analysis of the first switch to an extended half-life factor IX (albutrepenonacog alfa, rFIX-FP) in Spain

Extended half-life of factor IX (FIX) demonstrated clinical benefit and lower treatment burden than standard half-life FIX products in clinical trials. We analysed the impact in efficacy, pharmacokinetics (PKs) and costs of the switch from nonacog alfa (rFIX) to albutrepenonacog alfa (rFIX-FP) in the first patient with haemophilia B (HB) treated in Spain outside clinical trials. A 7-year-old boy presented with HB with poor venous access and repetition infections using rFIX, which was switched to rFIX-FP. Prophylaxis was adjusted by PKs using WAPPS-Hemo tailoring from 100 IU/kg/week of rFIX to 80 IU/kg/3 weeks of rFIX-FP. Comparing 6 months before, rFIX-FP reduced 68.5% FIX consumption/kg and 58.3% infusion frequency, but total costs/weight showed a slight increase. Ratio of half-life between rFIX and rFIX-FP was 3.4–3.7. This case report revealed that switch to rFIX-FP decreased frequency and FIX consumption, without adverse events and bleeds.

Population Pharmacokinetics of Clotting Factor Concentrates and Desmopressin in Hemophilia

Hemophilia A and B are bleeding disorders caused by a deficiency of clotting factor VIII and IX, respectively. Patients with severe hemophilia (< 0.01 IU mL⁻¹) and some patients with moderate hemophilia (0.01–0.05 IU mL⁻¹) administer clotting factor concentrates prophylactically. Desmopressin (d-amino d-arginine vasopressin) can be applied in patients with non-severe hemophilia A. The aim of administration of factor concentrates or desmopressin is the prevention or cessation of bleeding. Despite weight-based dosing, it has been demonstrated that factor concentrates still exhibit considerable pharmacokinetic variability. Population pharmacokinetic analyses, in which this variability is quantified and explained, are increasingly performed in hemophilia research. These analyses can assist in the identification of important patient characteristics and can be applied to perform patient-tailored dosing. This review aims to present and discuss the population pharmacokinetic analyses that have been conducted to develop population pharmacokinetic models describing factor levels after administration of factor VIII or factor IX concentrates or d-amino d-arginine vasopressin. In total, 33 publications were retrieved from the literature. Two approaches were applied to perform population pharmacokinetic analyses, the standard two-stage approach and non-linear mixed-effect modeling. Using the standard two-stage approach, four population pharmacokinetic models were established describing factor VIII levels. In the remaining 29 analyses, the non-linear mixed-effect modeling approach was applied. NONMEM was the preferred software to establish population pharmacokinetic models. In total, 18 population pharmacokinetic analyses were conducted on the basis of data from a single product. From all available population pharmacokinetic analyses, 27 studies also included data from pediatric patients. In the majority of the population pharmacokinetic models, the population pharmacokinetic parameters were allometrically scaled using actual body weight. In this review, the available methods used for constructing the models, key features of these models, patient population characteristics, and established covariate relationships are described in detail.

Model-Based Evaluation of Linear Limited and Bayesian Sparse Sampling for Therapeutic Monitoring of Recombinant Coagulation Factor IX

Dosing of coagulation factor products is mainly determined based on a patient's body weight; however, several studies have reported high interindividual variability in their pharmacokinetics (PK). The objective of this study was to develop and evaluate 2 sparse sampling methods for the estimation of AUC of recombinant factor IX (BeneFIX) as proof of concept for dose individualization. A population pharmacokinetic model was used to generate the plasma factor IX activity-versus-time data. The linear limited sampling model (LLSM) was developed based on the correlation of factor IX activity versus AUC_0-72 hours following screening of several blood sampling times in adolescent and adult subjects (n = 90 subjects). Factor IX trough concentrations were predicted from a relationship established from AUC versus factor IX activity measured 72 hours postdosing. Using the best selected sampling time, the LLSM and Bayesian model were validated in separate data sets (n = 75 subjects). Using the LLSM and Bayesian analysis, a blood sample at 24 hours predicted AUC with bias and root mean square error < 5% and < 15%, respectively. The predicted trough concentrations were ≥1 IU/dL in 99% and 100% of subjects by the LLSM and Bayesian model, respectively. The average factor IX dose for a target AUC of 800 IU·h/dL was 61, 60, and 63 IU/kg using the extensive (reference), LLSM and Bayesian model, respectively. Overall, the AUC, trough concentrations and individualized dosing of recombinant factor IX could be reasonably predicted using the LLSM and Bayesian model.

Routine clinical care data for population pharmacokinetic modeling: the case for Fanhdi/Alphanate in hemophilia A patients

Fanhdi/Alphanate is a plasma derived factor VIII concentrate used for treating hemophilia A, for which there has not been any dedicated model describing its pharmacokinetics (PK). A population PK model was developed using data extracted from the Web-Accessible Population Pharmacokinetic Service-Hemophilia (WAPPS-Hemo) project. WAPPS-Hemo provided individual PK profiles for hemophilia patients using sparse observations as provided in routine clinical care by hemophilia centers. Plasma factor activity measurements and covariate data from hemophilia A patients on Fanhdi/Alphanate were extracted from the WAPPS-Hemo database. A population PK model was developed using NONMEM and evaluated for suitability for Bayesian forecasting using prediction-corrected visual predictive check (pcVPC), cross validation, limited sampling analysis and external evaluation against a population PK model developed on rich sampling data. Plasma factor activity measurements from 92 patients from 12 centers were used to derive the model. The PK was best described by a 2-compartment model including between subject variability on clearance and central volume, fat free mass as a covariate on clearance, central and peripheral volumes, and age as covariate on clearance. Evaluations showed that the developed population PK model could predict the PK parameters of new individuals based on limited sampling analysis and cross and external evaluations with acceptable precision and bias. This study shows the feasibility of using real-world data for the development of a population PK model. Evaluation and comparison of the model for Bayesian forecasting resulted in similar results as a model developed using rich sampling data.

Population pharmacokinetics of factor IX in hemophilia B patients undergoing surgery

Essentials Factor IX (FIX) dosing using body weight frequently results in under and overdosing during surgery. We aimed to establish a population pharmacokinetic (PK) model describing the perioperative FIX levels. Population PK parameter values for clearance and V1 were 284 mL h-170 kg-1 and 5450 mL70 kg-1. Perioperative PK parameters differ from those during non-surgical prophylactic treatment. SUMMARY: Background Hemophilia B is a bleeding disorder characterized by a deficiency of coagulation factor IX (FIX). In the perioperative setting, patients receive FIX concentrates to ensure hemostasis. Although FIX is usually dosed according to bodyweight, under- and overdosing occurs frequently during surgery. Aim The objective was to quantify and explain the interpatient variability of perioperatively administered plasma-derived (pd) and recombinant (r) FIX concentrates. Methods Data were collected from 118 patients (median age, 40 years [range, 0.2-90]; weight, 79 kg [range, 5.3-132]) with moderate (28%) or severe hemophilia B (72%), undergoing 255 surgical procedures. Population pharmacokinetic (PK) parameters were estimated using nonlinear mixed-effect modeling in NONMEM. Results Measured perioperative FIX level vs. time profiles were adequately described using a three-compartment PK model. For a typical 34-year-old patient receiving rFIX, clearance (CL), intercompartmental clearance (Q2, Q3), distribution volume of the central compartment (V1) and peripheral compartments (V2, V3) plus interpatient variability (%CV) were: CL, 284 mL h-170 kg-1 (18%); V1, 5450 mL70 kg-1 (19%); Q2, 110 mL h-170 kg-1; V2, 4800 mL70 kg-1; Q3, 1610 mL h-170 kg-1; V3, 2040 mL70 kg-1. From 0.2 years, CL and V1 decreased 0.89% and 1.15% per year, respectively, until the age of 34 years. Patients receiving pdFIX exhibited a lower CL (11%) and V1 (17%) than patients receiving rFIX. Interpatient variability was successfully quantified and explained. Conclusions The estimated perioperative PK parameters of both pdFIX and rFIX are different from those reported for prophylactic treatment. The developed model may be used to apply PK-guided dosing of FIX concentrates during surgery.

Pharmacokinetics and the transition to extended half-life factor concentrates: communication from the SSC of the ISTH

Extended half-life proteins (EHL) are increasingly used in clinical practice, but there is no standardized approach to sampling, interpretation and implementation of pharmacokinetics (PK) data to maximize treatment benefit. The goal of EHL treatment is to attain a trough level sufficient to protect against spontaneous bleeds and reduce infusion frequency and limitations on individual activity and lifestyle. Performing classical PK assessments requires multiple blood samples, which is burdensome for patients and providers. Herein we review a population pharmacokinetic (popPK) approach to estimate individual PK parameters to transition patients from standard half-life (SHL) to EHL concentrates. We propose that a minimum of two to four post-infusion samples is sufficient to estimate individual PK profiles, with sufficient certainty to maintain factor levels above 1% and achieve bleed-free lifestyles. We also survey current PK use in patients transitioning to EHL, review key PK parameters and popPK models, and recommend an approach to using PK in patients initiating or switching to EHL.