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Reduced and optimized trial designs for drugs described by a target mediated drug disposition model
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.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.ORCID iD: 0000-0003-1258-8297
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.ORCID iD: 0000-0002-2676-5912
2018 (English)In: Journal of Pharmacokinetics and Pharmacodynamics, ISSN 1567-567X, E-ISSN 1573-8744, Vol. 45, no 4, p. 637-647Article in journal (Refereed) Published
Abstract [en]

Monoclonal antibodies against soluble targets are often rich and include the sampling of multiple analytes over a lengthy period of time. Predictive models built on data obtained in such studies can be useful in all drug development phases. If adequate model predictions can be maintained with a reduced design (e.g. fewer samples or shorter duration) the use of such designs may be advocated. The effect of reducing and optimizing a rich design based on a published study for Omalizumab (OMA) was evaluated as an example. OMA pharmacokinetics were characterized using a target-mediated drug disposition model considering the binding of OMA to free IgE and the subsequent formation of an OMA-IgE complex. The performance of the reduced and optimized designs was evaluated with respect to: efficiency, parameter uncertainty and predictions of free target. It was possible to reduce the number of samples in the study by 30% while still maintaining an efficiency of almost 90%. A reduction in sampling duration by two-thirds resulted in an efficiency of 75%. Omission of any analyte measurement or a reduction of the number of dose levels was detrimental to the efficiency of the designs (efficiency ae<currency> 51%). However, other metrics were, in some cases, relatively unaffected, showing that multiple metrics may be needed to obtain balanced assessments of design performance.

Place, publisher, year, edition, pages
SPRINGER/PLENUM PUBLISHERS , 2018. Vol. 45, no 4, p. 637-647
Keywords [en]
Optimal design, Target mediated drug disposition, Monoclonal antibodies, Sampling time optimization, Model-based
National Category
Pharmaceutical Sciences
Identifiers
URN: urn:nbn:se:uu:diva-361677DOI: 10.1007/s10928-018-9594-9ISI: 000438685100008PubMedID: 29948794OAI: oai:DiVA.org:uu-361677DiVA, id: diva2:1253618
Available from: 2018-10-05 Created: 2018-10-05 Last updated: 2019-04-11Bibliographically 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, SivKarlsson, Mats OHooker, Andrew

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