Laura Bukkems

Population pharmacokinetic modelling of perioperative dosing of Haemate P describing the interaction between factor VIII and Von Willebrand Factor levels in patients von Willebrand Disease

L.H. Bukkems (1), J.M. Heijdra (2), H.C.A.M. Hazendonk (2), N.C.B de Jager (1), C.J. Fijnvandraat (2), K. Meijer (4), F.W.G. Leebeek (5), M.H. Cnossen (2), R.A.A. Mathôt (1) for the “OPTI-CLOT” study group.

(1) Hospital Pharmacy-Clinical Pharmacology, Amsterdam University Medical Centers, the Netherlands, (2) Department of Pediatric Hematology, Erasmus University Medical Center - Sophia Children’s Hospital Rotterdam, the Netherlands, (3) Department of Pediatric Hematology, Amsterdam University Medical Centers, Amsterdam, the Netherlands, (4)Department of Hematology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands, (5) Department of Hematology, Erasmus University Medical Center Rotterdam, the Netherlands.

Objectives: Previous studies indicate that 65 to 91% of patients with von Willebrand Disease (VWD) treated with a von Willebrand Factor (VWF)/factor VIII (FVII) concentrate (ratio 2.4:1, Haemate® P/Humate P®) during surgery present with VWF and/or FVIII levels outside predetermined target levels.1 This may result in higher treatment costs and increase the risk of possible adverse events. Recently, a population pharmacokinetic (PK) model was developed describing FVIII PK after Haemate® P administration, enabling perioperative PK-guided dosing based on FVIII target levels.2 However, as several guidelines describe perioperative target levels for both FVIII and VWF to ensure hemostasis, application of an integrated population PK model describing FVIII as well as VWF activity (VWF:Act) levels may further optimize perioperative dosing and improve quality of care.3,4

Methods: Patients with VWD undergoing surgery in one of five different hemophilia treatment centers in the Netherlands between 2000-2018 treated with Haemate P® were included in this study. The VWF and FVIII activity data were analyzed using nonlinear mixed-effect modelling software (NONMEM). VWF:Act time profiles were described with a one-compartment model with first-order elimination. Baseline VWF:Act levels were subtracted from the observed levels. When the pre-dose VWF:Act levels were higher than the lowest VWF:Act level ever measured (baseline VWF) a ‘virtual’ dose with a bioavailability term was incorporated to correct for this difference. The change in endogenous and exogenous FVIII amount over time was described with a turnover model with a zero-order production rate kin and a 1st order elimination rate kout. Since, VWF acts as a chaperone for FVIII protecting it from early proteolytic degradation and cellular uptake, the inhibitory effect of VWF on FVIII clearance was described with an Emax relationship.5

Results: The dataset consisted of 118 patients with different types of VWD (n type 1= 57; 2A = 32; 2B = 9; 2M = 11; 2N = 3; 3 = 6), aged 1 to 82 years, weighing 8.8 to 118 kg, undergoing 174 surgeries. Patients received a median of 5 doses (median dose FVIII: 20.8 IU/kg) per surgery and a total of 894 FVIII and 695 VWF:Act levels were included. Baseline and pre-dose VWF:Act values were 0.15 IU/ml [range: 0.00-0.58] and 0.28 IU/ml [range: 0.01-3.74], respectively. Typical values for VWF clearance and volume of distribution with corresponding interindividual variability values (IIV %) were 150 ml/h (85.0%) and 4910 ml (29.3%) for a patient of 70 kg, respectively. The PK parameters of VWF were not influenced by FVIII levels.
After the first perioperative dose the median FVIII level was 1.30 IU/ml [range 0.41 – 3.64 IU/ml] which cumulated further to a median FVIII level of 1.80 IU/ml [range: 0.59-4.21 IU/ml] on day 5. Using the turnover model typical values for FVIII clearance and volume of distribution were 353 ml/h (68.8%) and 4330 ml (17.7%), respectively. These values reflect the theoretical situation where VWF is not present. VWF inhibited FVIII clearance with an IC50 value of 3.13 IU/mL (IIV: 73.4%). Imax and gamma were fixed on 1. Pre-dose (baseline) FVIII level was estimated on 0.931 IU/mL (IIV: 35.1%). An average perioperative VWF:Act level of 1.23 IU/ml decreased the FVIII clearance from a typical value of 353 ml/h to 253 ml/h and increased FVIII elimination half-life from 8.5 to 11.9 hour. Clearly, when VWF was present the clearance of FVIII decreased and the half-life of FVIII increased, explaining the cumulative FVIII levels seen in the perioperative period after dosing with this concentrate.

Conclusions: FVIII and VWF:Act levels after perioperative Haemate® P dosing were adequately described by this novel integrated population PK model. Application of this model could facilitate more accurate PK-guided perioperative dosing with this specific concentrate based on both FVIII and VWF:Act targets, potentially leading to improvement of quality and cost-effectiveness of care.

References:
[1] H. C. A. M. Hazendonk et al., “Analysis of current perioperative management with Haemate® P/Humate P® in von Willebrand disease: Identifying the need for personalized treatment,” Haemophilia, vol. 24, no. 3, pp. 460–470, 2018.
[2] N. C. B. de Jager et al., “One piece of the puzzle: Population pharmacokinetics of FVIII during perioperative Haemate P®/Humate P® treatment in von Willebrand disease patients,” J. Thromb. Haemost., vol. 18, no. 2, pp. 295–305, 2020.
[3] Nederlandse Vereniging van Hemofiliebehandelaars (NVHB), Richtlijn: Diagnostiek en behandeling van hemofilie en aanverwante hemostasestoornissen. Alphen aan den Rijn: Van Zuiden Communications B.V., 2009.
[4] W. L. Nichols et al., “von Willebrand disease (VWD): Evidence-based diagnosis and management guidelines, the National Heart, Lung, and Blood Institute (NHLBI) expert panel report (USA),” Haemophilia, vol. 14, no. 2, pp. 171–232, 2008.
[5] W. Miesbach and E. Berntorp, “Interaction between VWF and FVIII in treating VWD,” Eur. J. Haematol., vol. 95, no. 5, pp. 449–454, 2015.

Reference: PAGE () Abstr 9365 [www.page-meeting.org/?abstract=9365]

Poster: Oral: Drug/Disease Modelling