Derivation of a Pharmacokinetic Model to Include a Plasma-Derived, von Willebrand Factor-Containing Factor VIII (Koate®-DVI) Concentrate and its Low-Dose Use. (November 2021)

• Record Type: Journal Article
• Authors: Hajducek, Dagmar M.; Primacakti, Fitri; Chozie, Novie; Mir, Roser; McEneny-King, Alanna; Iorio, Alfonso; Edginton, Andrea
• Is Part Of: Plasmatology. Volume 15(2021)
• Publication Date: 2021-11
• Subjects: Population pharmacokinetics -- hemophilia A -- WAPPS-Hemo; Blood plasma -- Periodicals; Hematology -- Periodicals; Blood -- Diseases -- Periodicals; 612.116
• DOI: 10.1177/26348535211062229
• Languages: English
• ISSNs: 2634-8535

Abstract

Background: Population pharmacokinetics (popPK) has been reliably leveraged to generate individual PK in hemophilia patients. Specific popPK models are suited to predict individual PK under a variety of scenarios that may not be captured by clinical trials, allowing for individualized prophylactic treatment. The Web-Accessible Population Pharmacokinetic Service-Hemophilia (WAPPS-Hemo) project generates individually predicted pharmacokinetic profiles relying on concentrate-specific popPK models used for Bayesian forecasting. Objective: Specification of a popPK model for the plasma-derived factor VIII (FVIII) concentrate Koate-DVI and its suitability for pharmacokinetic estimation in low-dose scenarios. Methods: A popPK model was developed for Koate-DVI WAPPS-Hemo PK data in combination with the existing WAPPS-Hemo Fanhdi/Alphanate model derivation dataset using nonlinear mixed effects modelling, and was validated via cross-validation and prediction-corrected Visual Predictive Checks (pcVPC). Bootstrap and PK outcomes between the Fanhdi/Alphanate and the Fanhdi/Alphanate/Koate models were compared, and the relative error distributions from a limited sampling analysis (LSA) under the latter model for low and normal doses (10 vs 50 IU/kg) and inclusion/exclusion of pre-dose measurements. Results: A Fanhdi/Alphanate/Koate model was derived (126 patients, ages 1–71 years) after deeming a Koate-brand covariate not clinically significant, resulting in similar parameter estimates than the Fanhdi/Alphanate model with satisfactory goodness of fit, cross-validation and pcVPC results. Low-dose predictions resulted in a higher accuracy and slightly lower precision of half-life (β -phase) and time to 2% trough (TAT2%) estimates than normal dose (median absolute bias for half-life: 0.12 vs 0.5%; median interquartile range, IQR: 11.79% vs 9.95%). Precision improved under pre-dose designs by 2 to 3% and remained similar between 5- and 2-sample designs (IQR reduction<1.8%). Conclusions: The Fanhdi/Alphanate/Koate model is appropriate for Bayesian forecasting in the WAPPS-Hemo platform, providing a comparable prediction capability for low and normal dosing regimens (10 vs 50 IU/Kg).