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Dose tailoring of human cell line‐derived recombinant factor VIII simoctocog alfa: Using a limited sampling strategy in patients with severe haemophilia A
Author(s) -
Delavenne Xavier,
Dargaud Yesim,
Ollier Edouard,
Négrier Claude
Publication year - 2019
Publication title -
british journal of clinical pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.216
H-Index - 146
eISSN - 1365-2125
pISSN - 0306-5251
DOI - 10.1111/bcp.13858
Subject(s) - haemophilia , medicine , haemophilia a , population , bayesian probability , pharmacokinetics , statistics , surgery , mathematics , environmental health
Aims The use of factor VIII (FVIII) prophylaxis in haemophilia A is considered the standard of care, particularly in children. Despite adjustment of doses for body weight and/or age, a large pharmacokinetic (PK) variability between patients has been observed. PK‐tailored prophylaxis may help clinicians adjust coagulation factor FVIII activity (FVIII:C) to the desired level, which may differ in individual patients. The objective was to develop a population PK model for simoctocog alfa based on pooled clinical trial data and to develop a Bayesian estimator to allow PK parameters in individual patients to be estimated using a reduced number of blood samples. Methods PK data from 86 adults and 29 children/adolescents with severe haemophilia A were analysed. The FVIII data measured using 2 different assays (chromogenic and the 1‐stage clotting assay) were fit to separate develop population PK models using nonlinear mixed‐effect models. A Bayesian estimator was then developed to estimate the time above the threshold of 1%. Results The PK data for chromogenic and the 1‐stage clotting assays were both best described by a 2‐compartment models. Simulations demonstrated good predictive capacity. The limited sampling strategy using blood sample at 3 and 24 hours allowed an accurate estimation of the time above the threshold of 1% FVIII:C (mean bias 0.01 and 0.11, mean precision 0.18 and 0.45 for 2 assay methods). Conclusion In this study, we demonstrated that a Bayesian approach can help to reduce the number of samples required to estimate the time above the threshold of 1% FVIII:C with good accuracy.