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In silico evaluation of limited blood sampling strategies for individualized recombinant factor IX prophylaxis in hemophilia B patients.
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In silico evaluation of limited blood sampling strategies for individualized recombinant factor IX prophylaxis in hemophilia B patients.

J Thromb Haemost. 2017 Jul 08;:

Authors: Preijers T, Hazendonk HCAM, Fijnvandraat K, Leebeek FWG, Cnossen MH, Mathôt RAA

Abstract
BACKGROUND: Patients with severe hemophilia B regularly administer prophylactic intravenous doses of clotting factor IX (FIX) concentrate to maintain a trough level of at least 0.01 IUmL(-1) in order to prevent joint bleeds. Assessment of individual pharmacokinetic (PK) parameters allows individualization of the recombinant FIX (rFIX) dose.
AIM: This in silico study aims to evaluate the predictive performance of limited sampling strategies (LSSs) with 1 to 3 samples to estimate individual PK parameters of rFIX.
METHODS: Monte Carlo simulations were performed to obtain 5000 concentration-time profiles using population PK parameters for rFIX from literature. Eleven LSSs were developed with 1, 2 or 3 samples taken within an 80-hour interval following administration of 100 IUkg(-1) rFIX. Clearance (CL), half-life (t½ ), time to 1% and steady-state distribution volume (Vss) were estimated for each simulated individual using Bayesian analysis.
RESULTS: For each LSS, average bias was small for CL (range -1.5% to 1.4%), t½ (range -4.5% to -0.7%), time to 1% (range -2.9% to 0%) and Vss (range -3.7% to 0.3%). Imprecision for these parameters ranged from 6.4% to 11.9%, from 10.3% to 15.6%, from 7.3% to 10.9% and from 9% to 20.1%, respectively. Best predictive performance was achieved using one sample taken between 10 minutes and 3 hours and two samples between 48 and 56 hours after administration of rFIX.
CONCLUSIONS: This study demonstrates that limited sampling strategies, used for individualized dosing of rFIX in hemophilia B patients, can be developed and evaluated by in silico simulation. This article is protected by copyright. All rights reserved.

PMID: 28688133 [PubMed - as supplied by publisher]

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