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Combined quantitative tuberculosis biomarker model for time-to-positivity and colony forming unit to support tuberculosis drug development
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 Pharmacy. Radboud Univ Nijmegen, Radboud Inst Hlth Sci, Dept Pharm, Med Ctr, Nijmegen, Netherlands..ORCID iD: 0000-0002-0093-6445
Univ St Andrews, Sch Med, Div Infect & Global Hlth, St Andrews, Scotland..
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2023 (English)In: Frontiers in Pharmacology, E-ISSN 1663-9812, Vol. 14, article id 1067295Article in journal (Refereed) Published
Abstract [en]

Biomarkers are quantifiable characteristics of biological processes. In Mycobacterium tuberculosis, common biomarkers used in clinical drug development are colony forming unit (CFU) and time-to-positivity (TTP) from sputum samples. This analysis aimed to develop a combined quantitative tuberculosis biomarker model for CFU and TTP biomarkers for assessing drug efficacy in early bactericidal activity studies. Daily CFU and TTP observations in 83 previously patients with uncomplicated pulmonary tuberculosis after 7 days of different rifampicin monotherapy treatments (10-40 mg/kg) from the HIGHRIF1 study were included in this analysis. The combined quantitative tuberculosis biomarker model employed the Multistate Tuberculosis Pharmacometric model linked to a rifampicin pharmacokinetic model in order to determine drug exposure-response relationships on three bacterial sub-states using both the CFU and TTP data simultaneously. CFU was predicted from the MTP model and TTP was predicted through a time-to-event approach from the TTP model, which was linked to the MTP model through the transfer of all bacterial sub-states in the MTP model to a one bacterial TTP model. The non-linear CFU-TTP relationship over time was well predicted by the final model. The combined quantitative tuberculosis biomarker model provides an efficient approach for assessing drug efficacy informed by both CFU and TTP data in early bactericidal activity studies and to describe the relationship between CFU and TTP over time.

Place, publisher, year, edition, pages
Frontiers Media S.A., 2023. Vol. 14, article id 1067295
Keywords [en]
rifampicin, TTP, CFU, tuberculosis, biomarker
National Category
Pharmacology and Toxicology Pharmaceutical Sciences
Identifiers
URN: urn:nbn:se:uu:diva-500588DOI: 10.3389/fphar.2023.1067295ISI: 000959380900001PubMedID: 36998606OAI: oai:DiVA.org:uu-500588DiVA, id: diva2:1752394
Available from: 2023-04-21 Created: 2023-04-21 Last updated: 2024-03-11Bibliographically approved
In thesis
1. Pharmacometric tools to support translational drug development
Open this publication in new window or tab >>Pharmacometric tools to support translational drug development
2024 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The use of model-informed drug development has been shown to save significant costs and improve decision making early in the drug development process. The work in this PhD thesis aimed to employ pharmacometric tools to support translational drug development from the preclinical to the late clinical stages.

Pharmacometric modeling was used to characterize the treatment-shortening potential of different anti tuberculosis regimens. The results provided additional evidence in favor of the treatment-shortening capacity of the BPaMZ regimen over BPaL and standard of care, HRZE.

Pharmacokinetic-pharmacodynamic (PKPD) modeling was used to enable the evaluation of the exposure-response of a new anti-tubercular drug, MPL-447, in C3HeB/FeJ mice, thought to be of a translational value in tuberculosis drug development. Model-based evaluation revealed a significant impact of necrotic lesion development in mice on both bacterial growth and sensitivity to treatment with MPL-447, highlighting the significance of accounting for the heterogenous lesion profile in the C3HeB/FeJ mouse model when evaluating drug efficacy.

Pharmacokinetic (PK) modeling was employed to perform interspecies PK scaling of the CB 4332 protein using information from three preclinical species. This approach accounted for the impact of immunogenicity and species-related differences in elimination. Simulations predicted the protein plasma concentrations in humans after different dosing regimens and suggested that a 7 mg/kg dose would be required to reach the target at steady-state.

Using combined biomarker data, PKPD modeling was employed to simultaneously analyze two tuberculosis efficacy biomarkers. The final biomarker model facilitated the prediction of the relationship between the two biomarkers over time. With this modeling framework, missing biomarker data can be predicted using information from the other biomarker.

Several model-based approaches were also explored to evaluate pediatric study power in rare diseases. These approaches were performed analyzing pediatric data alone or combined with the adult data. While Bayesian priors performed well when analyzing pediatric data alone, less technical modeling approaches proved sufficient when pediatric and adult data were combined.

In conclusion, the research presented in this thesis has addressed various challenges encountered in translational drug development. The work has contributed to the evaluation of new anti-tubercular drugs and regimens, the assessment of newly proposed animal models, and optimizing the utilization of biomarker information. Furthermore, this thesis has provided insights into the selection of First-in-Human dose for a protein, showcasing the applicability of model-based approaches in this critical decision-making process. The research has contributed to improving analysis approaches for pediatrics in rare diseases.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2024. p. 87
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 350
Keywords
drug development, pharmacometrics, pharmacokinetics, pharmacodynamics, non-linear mixed effect models, tuberculosis, dose selection, interspecies scaling, pediatric trials
National Category
Pharmaceutical Sciences
Research subject
Pharmaceutical Science
Identifiers
urn:nbn:se:uu:diva-524851 (URN)978-91-513-2068-7 (ISBN)
Public defence
2024-05-08, room A1:107a, Uppsala, 09:15 (English)
Opponent
Supervisors
Available from: 2024-04-15 Created: 2024-03-11 Last updated: 2024-04-15

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Ayoun Alsoud, RamiSvensson, Robin J.Svensson, ElinSimonsson, Ulrika S. H.

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