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Introduction: Damoctocog alfa pegol (BAY 94-9027, Jivi®) is an extended half-life recombinant factor (F)VIII replacement, indicated for the treatment of haemophilia A in patients aged ≥12 years. Following introduction of damoctocog alfa pegol in Canada in 2020, there have been no reports on routine clinical effectiveness and satisfaction, when switching from a previous FVIII product in Canada., Aim: To report changes in pharmacokinetics, effectiveness, utilization and patient satisfaction when switching to damoctocog alfa pegol prophylaxis from previous standard half-life octocog alfa (BAY 81-8973, Kovaltry®) treatment., Methods: A single-centre, intra-patient comparison of pharmacokinetics and clinical outcomes was performed. Blood samples drawn once pre-dose and ≥2 times post-dose were measured by a one-stage assay to assess pharmacokinetic parameters including area under the curve (AUC, primary endpoint). Patient-reported outcomes data were collected using the Patient-Reported Outcomes, Burdens and Experiences questionnaire (PROBE). Clinical outcomes included annualized bleeding rate (ABR) and factor utilization., Results: Dose-normalized AUC was significantly increased after switch to damoctocog alfa pegol from octocog alfa. Median (quartile [Q]1; Q3) annualized bleeding rates were 0.67 (0.00; 1.33) with damoctocog alfa pegol and 1.33 (0.00; 2.67) with octocog alfa. Half of the patients receiving damoctocog alfa pegol prophylaxis experienced zero bleeds (n = 9, 50.0%) versus 38.9% (n = 7) of patients treated with octocog alfa. Patients' good quality of life was maintained., Conclusion: This study provides routine clinical evidence supporting the benefits of switching from octocog alfa to damoctocog alfa pegol for patients with severe haemophilia A., (© 2024 The Authors. Haemophilia published by John Wiley & Sons Ltd.)

Introduction: The use of pharmacokinetic assessment for optimal prophylactic dosing of factor concentrates in haemophilia has gained increasing enthusiasm over the last decade. However, blood sampling on several occasions is burdensome and limited sampling using population-based PK is appealing., Aim: To compare the pharmacokinetics and dosing recommendations for prophylaxis using six-point single subject versus population-based method (WAPPS-Hemo) for simoctocog alfa (Nuwiq ® )., Methods: Twelve adult patients with severe haemophilia A received a factor VIII (FVIII) dose of ≈50 IU/kg, and the activity was measured pre-infusion and at 30 min, 6, 9, 24 and 48 h post-infusion. Half-life (t 1 / 2 ), weight-normalized AUC and time to troughs of 5%, 3% and 1% were calculated. The correlation between the PK algorithms was assessed using intraclass correlations (ICC) and dosing estimations were provided., Results: WAPPS-Hemo yielded a slightly longer mean t 1 / 2 , but the overall correlation between the methods was good (ICC ≥0.79) The time to troughs of 5%, 3% and 1% showed ICCs ≥0.86. For all variables, the most converging limited time point was 6+48 h. Additional time points did not improve the correlation. Despite similar pharmacokinetics, the mean estimated dose for a specific trough level varied from 60% less to 20% more using the population-based approach. The time to 1% and the corresponding dose was sensitive to the baseline assumption., Conclusion: Our data support the use of population-based PK for patients on simoctocog alfa prophylaxis but also indicates differences, stressing the importance of the sampling scheme and monitoring actual FVIII levels achieved., (© 2021 The Authors. Haemophilia published by John Wiley & Sons Ltd.)

Background: The Web-Accessible Population Pharmacokinetic Service (WAPPS) project generates individually predicted pharmacokinetic (PK) profiles and tailored prophylactic treatment regimens for haemophilic patients, which rely on a set of population PK (PopPK) models providing concentrate-specific priors for the Bayesian forecasting methodology., Aim: To describe the predictive performance of the WAPPS PopPK models in use on the WAPPS-Hemo platform., Methods: Data for modelling include dense PK data obtained from industry sponsored and independent PK studies, and dense and sparse data accumulated through WAPPS-Hemo. WAPPS PopPK models were developed via non-linear mixed-effect modelling taking into account the effects of covariates and between-individual-and sometimes between-occasion-variability. Model evaluation consisted of (a) prediction-corrected Visual Predictive Check (pcVPC), (b) Limited Sampling Analysis (LSA) and (c) repeated hold-out cross-validation., Results: Thirty-three WAPPS PopPK models built on data from 3188 patients (ages 1-78 years) under treatment by factor VIII or IX products (FVIII, FIX) were evaluated. Overall, models exhibit excellent performance characteristics. The pcVPC shows that the observed PK data fall within acceptable 90% interpercentile predictive bands. A slight overprediction beyond the expected half-life, an anticipated result of using sparse data, occurs for some models. The LSA results in lower than 3% of relative error for FVIII and FIX products and 16% for engineered FIX products. Cross-Validation analysis yields relative errors lower than 1.5% and 1.4% in estimates of half-life and time to 0.02 IU/mL, respectively., Conclusion: The WAPPS-Hemo models consistently showed excellent performance characteristics for the intended use for Bayesian forecasting of individual PK profiles., (© 2020 John Wiley & Sons Ltd.)

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.

Introduction: This study proposes a method to predict individual pharmacokinetics of a future product by using the individual pharmacokinetic profile on the current product and the PopPK models of the current and future product., Methods: Individual dense data was collected from two PK crossover studies, one enrolling 29 patients switching from Advate to Eloctate and one enrolling 15 patients switching from Advate to Novoeight. Three methods were designed to predict the second product's individual PK parameters (CL, V1, Q, and V2). Method 1 used the second product's typical population value of PK parameters from its PopPK model. Method 2 used the second product's calculated PK parameters based on individual covariates and its PopPK model. Method 3 used method 2, along with the predicted η-values of CL and V1 from the first product and its PopPK model. Each method was used to assess PK prediction during switching from Advate to Novoeight, Novoeight to Advate, and Advate to Eloctate., Results: The three methods produced different outcomes. The mean absolute relative errors for half-life were lowest for method 3 for each study (11.6%, 13.1%, 13.6%). The regression line between predicted and observed half-life for method 3 was closest to the line of identity for each study (0.84, 0.67, 0.66)., Conclusion: Taking into account individual PK from a previous clotting factor product was shown to provide better means of estimating individual PK for a new product. This may improve regimen design across switches and reduce the time to tailor optimal dose of FVIII products., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Hemophilia A is a rare bleeding disorder resulting from a lack of functional factor VIII (FVIII). Therapy consists of replacement with exogenous FVIII, but is complicated by high inter-patient variability. A population pharmacokinetics (PopPK) approach can facilitate the uptake of an individualized approach to hemophilia therapy. We developed a PopPK model using data from seven brands of standard half-life FVIII products. The final model consists of a 2-compartment structure, with a proportional residual error model and between-subject variability on clearance and central volume. Fat-free mass, age, and brand were found to significantly affect pharmacokinetic (PK) parameters. Internal and external evaluations found that the model is fit for Bayesian forecasting and capable of predicting PK for brands not included in the modelling dataset, and useful for determining individualized prophylaxis regimens for 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.

Essentials The PK parameters of Eloctate vs Adynovate were compared using one-stage and chromogenic assays in 25 boys (12-18 years). The FVIII levels were taken at 3, 24, 48, and 72 hours following a dose of either FVIII; levels analyzed by WAPPS PK program. The PK profiles (half-life, clearance, and time to 5%, 3%, and 1%) were not statistically different for the two EHL FVIIIs. The significant interpatient variability in PK is mainly related to VWF levels (and blood group)., Background: A head-to-head comparison of the pharmokinetcs (PK) of extended half-life (EHL) factor VIII (FVIII) concentrates in the same subjects has not been reported. Recently, boys (ages 12-18 years) with hemophilia A in Canada were required to switch from Eloctate to Adynovate., Objectives: Compare the PK profiles of Eloctate vs Adynovate in the same boys., Methods: Boys switching from Eloctate to Adynovate prophylaxis had FVIII levels sampled at 3, 24, 48, and 72 hours following a regular prophylactic infusion of Eloctate and then 1-3 months later, of Adynovate. Testing was done by one-stage assay (OSA) and chromogenic assay (CA). The PK parameters were determined with the Web Accessible Population Pharmacokinetic Service (WAPPS)-Hemo PK tool., Results: Twenty-five boys (mean age 15.3 years; range: 12.1-18.4; 9 O blood group) underwent switching. Mean (range) terminal half-lives with the OSA were 16.1 hours (10.4 to 23.4; Eloctate) and 16.7 hours (11.0 to 23.6; Adynovate) (NS). With the CA, these were 18.0 hours (12.0 to 25.5; Eloctate) and 16.0 hours (10.3 to 22.9; Adynovate) (P = 0.001). There were no significant differences between the two EHL-FVIIIs in clearance, area under the concentration vs time curve (AUC), Vss, or time for FVIII levels to drop to 5%, 3%, and 1%. At the 72-h time point, mean observed FVIII levels following a mean dose of 39.3 IU/kg of Eloctate were 4.4% (OSA) and 4.4% (CA). For Adynovate, these were 5.1% (OSA) and 5.3% (CA) following similar doses. There was considerable interpatient variation in PK, mainly explained by differences in blood group/von Willebrand factor (VWF) levels., Conclusions: Eloctate and Adynovate have almost identical PK parameters. When switching from one to another no prophylaxis regimen change is needed., (© 2019 International Society on Thrombosis and Haemostasis.)

Introduction: Web‐Accessible Population–Pharmacokinetic Service–Haemophilia (WAPPS‐Hemo) data are available to study factor‐concentrate usage, defined as the required weekly dose to achieve a 3% trough (WD3T), across standard and extended half‐life (SHL/EHL) products. Aim: To provide baseline usage data including (i) differences across plasma‐derived (pdSHL) versus recombinant (rSHL) products, (ii) SHL versus EHL, and (iii) effect of age and positive inhibitor history. Methods: PK profiles (n = 14,416 patients, 0.3–85.2 years) and linear mixed effects models were used to estimate usage versus age, controlling for significant factors, using 95% confidence intervals to perform comparisons across all ages and posthoc tests to assess the differences. Results: Average usage was significantly higher for pdSHL versus rSHL in patients with a positive inhibitor history (PIH; 1.9–2.5 times higher), for SHL versus EHL (4–10 times), and was significantly associated with age. Conclusion: Baseline usage patterns from 2017 to early 2023 provide a benchmark for assessing the impact of emerging technologies in haemophilia. [ABSTRACT FROM AUTHOR]

Background: Extended half‐life (EHL) factor VIII (FVIII) products may decrease the burden of prophylactic treatment in haemophilia A by reducing infusion frequency. However, these products still exhibit wide inter‐patient variability and benefit from pharmacokinetic (PK) tailoring. Objective: Identify limited sampling strategies for rFVIIIFc, an EHL FVIII product, that produce accurate estimates of PK parameters and relevant troughs. Methods: We performed a limited sampling analysis on simulated populations of adults, adolescents, and children based on published population PK data. Sampling strategies were evaluated by comparing the error in estimates of half‐life, clearance, and trough levels, to a full 6‐sample design. Furthermore, we assessed the impact of incorporating knowledge about prior doses, and the day of the PK study within the regimen. We also evaluated the potential inappropriate dose adjustment rate (IDAR) among the modelled sampling strategies. Results: Many sampling strategies, including several 2‐sample designs, accurately predicted the PK and exposure measures (median absolute error <10%). When samples are only collected during a single visit (i.e., predose + peak), inclusion of prior dose information reduces median half‐life error from >20% to ~5% for adults/adolescents. In this same scenario, appropriate scheduling of the PK study decreases likelihood of unmeasurable predose samples, reducing median error on the 72‐h trough from 25% to <12% in the youngest population. Conclusions: The PK of rFVIIIFc can be accurately estimated using only peak and trough samples, provided that knowledge of prior doses is incorporated and the PK study is planned on an appropriate day within the dosing regimen. [ABSTRACT FROM AUTHOR]