A new population pharmacokinetic model for recombinant factor IX-Fc fusion concentrate including young children with

Sjoerd F Koopman1, Tine M H J Goedhart2, Laura H Bukkems1

  • 1Hospital Pharmacy-Clinical Pharmacology, Amsterdam University Medical Centers, Amsterdam, The Netherlands.

Insights

A new pharmacokinetic model for recombinant factor IX Fc fusion protein (rFIX-Fc) in haemophilia B patients accurately predicts FIX activity, especially in children. This improves treatment monitoring for extended half-life factor concentrates.

Area of Science:

  • Pharmacology
  • Hematology
  • Clinical Pharmacy

Background:

  • Recombinant factor IX Fc fusion protein (rFIX-Fc) is an extended half-life factor concentrate for haemophilia B.
  • Existing pharmacokinetic (PK) models for rFIX-Fc are limited to patients aged 12 years and older.

Purpose of the Study:

  • To externally evaluate the predictive performance of a published rFIX-Fc population PK model in patients of all ages.
  • To develop a new population PK model for rFIX-Fc using real-world data to better describe its pharmacokinetics across different age groups.

Main Methods:

  • Collected prospective and retrospective real-world data from 37 haemophilia B patients treated with rFIX-Fc.
  • Assessed predictive performance by comparing predicted versus observed FIX activity levels.
  • Constructed a new population PK model using nonlinear mixed-effects modeling.

Main Results:

  • The published model significantly underpredicted FIX activity (median prediction error: -48.8%).
  • The newly developed model demonstrated a substantially lower median prediction error (3.4%) and improved accuracy, particularly for children under 12 years.
  • Increased age correlated with decreased clearance (P < .01) in the new model.

Conclusions:

  • The published rFIX-Fc PK model is inadequate for predicting FIX activity across all age groups.
  • A new population PK model provides a more accurate description of rFIX-Fc pharmacokinetics, especially in pediatric populations.
  • Emphasizes the importance of developing representative PK models to avoid extrapolation and ensure accurate therapeutic monitoring.
Abstract

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