PK-guided switch between standard half-life and extended half-life factor VII products

P117 Introduction: Extended half-life (EHL) factor VIII (FVIII) requires improvements in half-life (t1/2) & area under the curve (AUC) of 1.3 & 1.25 times compared to standard half-life (SHL) products. The aim of this study is compare pharmacokinetics (PK) after the switch from SHL to EHL in patients with hemophilia A (HA). Methods: Multicenter comparative, cross-sectional, prospective study analyzing PK differences after switch from SHL to EHL (ef-moroctocog alfa [rFVIII-Fc] & rurioctocog alfa pegol [PEG-rFVIII]). WAPPS- Hemo® was used to analyze PK parameters with 2-3 samples: t1/2; AUC, peak level (PL); trough level at 24, 48 & 72 hours (TL24, TL48, TL72); & time to reach FVIII levels of 1, 2, 5% (T1%, T2%, T5%). Ratio of t1/2 & AUC, the number of weekly doses & the dose/kg/week before & after the switch were compared. Wilcoxon & Kruskal-Wallis tests (SPSS®) were used to compare the PK parameters. Results: Eightythree patients from 8 Spanish hospitals were analyzed (62 rFVIII-Fc; 21 PEG-rFVIII), 79 had severe HA & 4 moderate HA. Median age was 30 years (range = 3-64) & no differences in weight were observed between both periods.Dose/kg/week & weekly infusion frequency were reduced after the switch to EHL, & significant improvements were observed in all PK parameters after the change from SHL to EHL (Table 1). The median ratios of t1/2 & AUC were 1.3 (IQR:1.2-1.6) and 1.6 (IQR:1.3-2.2) in the entire cohort. In patients with =12 years ratios of t1/2 & AUC were 1.4 (IQR:1.3-1.6) & 1.7 (IQR:1.3-2.3), and in the cohort of 16 patients <12 years treated with rFVIII-Fc were 1.3 (IQR:0.9-1.5) and 1.4 (IQR:1.1- 2.1).After the switch to EHL, median weekly dose frequency (30%, IQR:0-33.3%) & dose/kg/week (16.9%, IQR:8.7-32.8%) were reduced. In a small subset of 15 younger patients the dose/kg/week was increased a median of 28.6% (IQR:11.7-40-7%). No differences were observed in any of the PK parameters & median ratios of t1/2 & AUC in patients aged =12 years treated with rFVIII-Fc vs. PEG-rFVIII (46 rFVIII-Fc; 21 PEG-rFVIII). Discussion/Conclusion: EHL FVIII have shown significant PK improvements in clinical real practice, allowing to reduce weekly infusion number & dose/kg/week. Outside the clinical trial setting, we have observed an increase in t1/2 & AUC ratios accordingly to EHL definition. Comparisons regarding clinical outcomes (bleeding rate after switch) will be performed after a follow-up of 1 year with EHL for the full cohort

Análisis del switch guiado por farmacocinética de factores VIII de semivida estándar a factores de semivida extendida

CO-170 Introducción y objetivos: Los factores VIII (FVIII) de semivida extendida (EHL) han mostrado en los ensayos clínicos mejoras de al menos 1, 3 veces la semivida plasmática (t1/2) y 1, 25 veces el área bajo la curva (AUC) respecto a los FVIII estándar (SHL). Herramientas basadas en modelos farmacocinéticos (PK) poblacionales permiten estimar los parámetros PK individuales y ajustar la profilaxis. El objetivo de este estudio es analizar el switch PK-guiado de SHL a EHL en pacientes con hemofilia A (HA). Métodos: Estudio multicéntrico comparativo, cruzado, prospectivo que analiza las diferencias PK tras el cambio de factores SHL a EHL (Elocta® y Adynovi®) en pacientes con HA grave/moderada en profilaxis. Se ha empleado el PopPK WAPPS-Hemo® con 2-3 muestras para realizar un perfil PK individualizado de los valores de FVIII. Los parámetros PK analizados son: t1/2, AUC, nivel pico (NP), nivel valle a las 24, 48 y/o 72 h (NV24/NV48/NV72) y tiempo para alcanzar niveles de FVIII del 5%, 2% y 1% (T5%/T2%/T1%). También analizamos los ratios de t1/2 y AUC, el nº dosis semanales y la dosis/kg/semana. Para comparar los parámetros PK entre ambos periodos empleamos los test de Wilcoxon y Kruskal-Wallis (SPSS®). Los resultados se expresaron con la mediana y el rango o rango intercuartílico (RIC). Resultados: Se han analizado 64 pacientes procedentes de 8 hospitales españoles (48 switch a Elocta® y 16 a Adynovi®), 62 con HA grave y 2 con HA moderada, con una mediana de edad de 32 años (rango=5-64) y sin diferencias en el peso entre ambos periodo [71, 0 (rango=12-116) vs 72, 0 (16, 9- 116) kg; p=0, 156]. La dosis/kg/semana se redujo tras el switch a EHL [74, 5 (RIC:59, 2-108, 1) vs 69, 2 (RIC:46, 2-96, 7) UI/kg/semana; p<0, 0001], así como ..

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.4642743