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Model-based evaluation of low dose factor VIII prophylaxis in haemophilia A
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. (Pharmacometrics)ORCID iD: 0000-0002-8109-3426
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
2019 (English)In: Haemophilia, ISSN 1351-8216, E-ISSN 1365-2516, Vol. 25, no 3, p. 408-415Article in journal (Refereed) Published
Abstract [en]

Introduction The optimal treatment modality for haemophilia A is lifelong prophylaxis which is expensive and may not be implementable everywhere where factor VIII (FVIII) availability is limited. A less costly alternative to prophylaxis is low-dose prophylaxis (LDP) which was compared to conventional prophylaxis in this model-based simulation study. Aim To explore whether LDP is motivated where standard prophylaxis is not implementable, including evaluating LDP efficacy compared to high-dose prophylaxis and investigating the potential economic benefit of individualized dosing. Methods For a virtual adult haemophilia A population, FVIII activity levels were simulated following alternative treatment regimens, based on a published population PK model. The regimens included very LDP, LDP and conventional prophylaxis twice and thrice weekly. The annual probability of bleeding was predicted based on the weekly time spent below 1 IU/dL, using a previously published relationship. Additionally, PK-based dose individualization was evaluated to determine FVIII savings using Bayesian forecasting. Results A treatment regimen of 10 IU/kg administered thrice weekly cost 75% less than a standard high-dose regimen and was predicted to have a 5% higher median probability of annual bleeds. PK-based dose individualization may result in further cost-savings, but implementation needs benefit versus feasibility consideration. Conclusion Based on simulations, a promising LDP regimen was identified that decreased treatment costs compared with standard high-dose prophylaxis at a small increase in bleeding risk. The results indicate that LDP is advocated where the standard-of-care is on-demand treatment; however, the results should be considered in the context of any limitations of the applied models.

Place, publisher, year, edition, pages
John Wiley & Sons, 2019. Vol. 25, no 3, p. 408-415
Keywords [en]
factor VIII prophylaxis, low‐dose prophylaxis, model simulations, population PK analysis
National Category
Hematology
Identifiers
URN: urn:nbn:se:uu:diva-381430DOI: 10.1111/hae.13753ISI: 000470929100026PubMedID: 31050134OAI: oai:DiVA.org:uu-381430DiVA, id: diva2:1303343
Available from: 2019-04-09 Created: 2019-04-09 Last updated: 2019-07-31Bibliographically approved
In thesis
1. Pharmacometric models in the development of biological medicinal products
Open this publication in new window or tab >>Pharmacometric models in the development of biological medicinal products
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Biological medicinal products (BMPs) are a successful class of drugs that are indicated in numerous diseases.  Common among them is that complexities associated with their manufacture and analysis lead to a high cost compared to small-molecular weight drugs.  If the development cost can be brought down and the use of BMPs optimized, these drugs may reach more patients at more affordable prices. Further, there are a number of knowledge gaps related to the characterization of their disposition, immunogenicity and use which can be filled through the development and application of novel methods for data analysis. In this thesis work, pharmacometric models and methods were developed and applied to aid BMP development and clinical use.

Model-based optimal design (OD) methodology was employed to reduce and optimize a published sampling schedule for a monoclonal antibody (mAb) displaying target-mediated drug disposition. Thus, illustrating that current sampling strategies for mAbs can be excessive from an economic and patient burden perspective.

A novel hidden-Markov model was developed to characterize anti-drug antibody (ADA) response which can plague many biologics throughout clinical development and post-approval. The developed model accounted for ADA assay inaccuracies by utilizing information from the assay and the pharmacokinetics (PK) of the therapeutic in question and allowed for an objective assessment of immunogenicity.

Model-based dose individualization and evaluation of low-dose prophylaxis (LDP) for coagulation factors were investigated in this work to improve treatment and lower costs. Individual doses were found to outperform standard-of-care while LDP was indicated as a viable treatment option in countries with limited coagulation factor access.

Biosimilar development is yet another method to reduce the costs of biologics. The development of a PKPD model for a pegylated granulocyte colony stimulating factor (GCSF) allowed for model simulations to demonstrate PK sensitivity to small differences in delivered dose between a reference and potential biosimilar product. The sensitivity of the system may be one of the reasons for difficulties associated with the development of biosimilar pegylated GCSFs.

In conclusion, the pharmacometric methods developed and applied in this thesis work can be used to improve BMP development.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2019. p. 80
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 271
Keywords
Pharmacometrics, model-based analysis, NONMEM, population modelling.
National Category
Pharmaceutical Sciences
Identifiers
urn:nbn:se:uu:diva-381441 (URN)978-91-513-0644-5 (ISBN)
Public defence
2019-06-05, B41, BMC, Husargatan, 75237, Uppsala, 09:15 (English)
Opponent
Supervisors
Available from: 2019-05-13 Created: 2019-04-11 Last updated: 2019-06-17

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Brekkan, AriJönsson, Siv

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