Development and evaluation of the population pharmacokinetic models for FVIII and FIX concentrates of the WAPPS-Hemo project.


Journal

Haemophilia : the official journal of the World Federation of Hemophilia
ISSN: 1365-2516
Titre abrégé: Haemophilia
Pays: England
ID NLM: 9442916

Informations de publication

Date de publication:
May 2020
Historique:
received: 22 12 2019
revised: 14 02 2020
accepted: 05 03 2020
pubmed: 14 4 2020
medline: 15 12 2020
entrez: 14 4 2020
Statut: ppublish

Résumé

The Web-Accessible Population Pharmacokinetic Service (WAPPS) project generates individually predicted pharmacokinetic (PK) profiles and tailored prophylactic treatment regimens for haemophilic patients, which rely on a set of population PK (PopPK) models providing concentrate-specific priors for the Bayesian forecasting methodology. To describe the predictive performance of the WAPPS PopPK models in use on the WAPPS-Hemo platform. Data for modelling include dense PK data obtained from industry sponsored and independent PK studies, and dense and sparse data accumulated through WAPPS-Hemo. WAPPS PopPK models were developed via non-linear mixed-effect modelling taking into account the effects of covariates and between-individual-and sometimes between-occasion-variability. Model evaluation consisted of (a) prediction-corrected Visual Predictive Check (pcVPC), (b) Limited Sampling Analysis (LSA) and (c) repeated hold-out cross-validation. Thirty-three WAPPS PopPK models built on data from 3188 patients (ages 1-78 years) under treatment by factor VIII or IX products (FVIII, FIX) were evaluated. Overall, models exhibit excellent performance characteristics. The pcVPC shows that the observed PK data fall within acceptable 90% interpercentile predictive bands. A slight overprediction beyond the expected half-life, an anticipated result of using sparse data, occurs for some models. The LSA results in lower than 3% of relative error for FVIII and FIX products and 16% for engineered FIX products. Cross-Validation analysis yields relative errors lower than 1.5% and 1.4% in estimates of half-life and time to 0.02 IU/mL, respectively. The WAPPS-Hemo models consistently showed excellent performance characteristics for the intended use for Bayesian forecasting of individual PK profiles.

Sections du résumé

BACKGROUND BACKGROUND
The Web-Accessible Population Pharmacokinetic Service (WAPPS) project generates individually predicted pharmacokinetic (PK) profiles and tailored prophylactic treatment regimens for haemophilic patients, which rely on a set of population PK (PopPK) models providing concentrate-specific priors for the Bayesian forecasting methodology.
AIM OBJECTIVE
To describe the predictive performance of the WAPPS PopPK models in use on the WAPPS-Hemo platform.
METHODS METHODS
Data for modelling include dense PK data obtained from industry sponsored and independent PK studies, and dense and sparse data accumulated through WAPPS-Hemo. WAPPS PopPK models were developed via non-linear mixed-effect modelling taking into account the effects of covariates and between-individual-and sometimes between-occasion-variability. Model evaluation consisted of (a) prediction-corrected Visual Predictive Check (pcVPC), (b) Limited Sampling Analysis (LSA) and (c) repeated hold-out cross-validation.
RESULTS RESULTS
Thirty-three WAPPS PopPK models built on data from 3188 patients (ages 1-78 years) under treatment by factor VIII or IX products (FVIII, FIX) were evaluated. Overall, models exhibit excellent performance characteristics. The pcVPC shows that the observed PK data fall within acceptable 90% interpercentile predictive bands. A slight overprediction beyond the expected half-life, an anticipated result of using sparse data, occurs for some models. The LSA results in lower than 3% of relative error for FVIII and FIX products and 16% for engineered FIX products. Cross-Validation analysis yields relative errors lower than 1.5% and 1.4% in estimates of half-life and time to 0.02 IU/mL, respectively.
CONCLUSION CONCLUSIONS
The WAPPS-Hemo models consistently showed excellent performance characteristics for the intended use for Bayesian forecasting of individual PK profiles.

Identifiants

pubmed: 32281726
doi: 10.1111/hae.13977
doi:

Substances chimiques

F8 protein, human 839MOZ74GK
Factor VIII 9001-27-8
Factor IX 9001-28-9

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

384-400

Subventions

Organisme : Pfizer Canada

Informations de copyright

© 2020 John Wiley & Sons Ltd.

Références

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Auteurs

Dagmar M Hajducek (DM)

School of Pharmacy, University of Waterloo, Waterloo, ON, Canada.

Pierre Chelle (P)

School of Pharmacy, University of Waterloo, Waterloo, ON, Canada.

Cedric Hermans (C)

Haemostasis and Thrombosis Unit, Division of Haematology, Cliniques universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium.

Alfonso Iorio (A)

McMaster-Bayer Endowed Research Chair for Clinical Epidemiology of Congenital Bleeding Disorders, Department of Medicine, Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, ON, Canada.

Alanna McEneny-King (A)

School of Pharmacy, University of Waterloo, Waterloo, ON, Canada.

Jacky Yu (J)

School of Pharmacy, University of Waterloo, Waterloo, ON, Canada.

Andrea Edginton (A)

School of Pharmacy, University of Waterloo, Waterloo, ON, Canada.

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Classifications MeSH