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Clinical Forecasting of Response to Tuberculosis Therapy Using Translational Multistate Tuberculosis Pharmacometric and General Pharmacodynamic Interaction Model Framework
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. (Pharmacometrics)
2018 (English)Independent thesis Advanced level (degree of Master (Two Years)), 30 credits / 45 HE creditsStudent thesis
Abstract [en]

A gap between pre-clinical and clinical phase is still exist in Tuberculosis (TB) drug development. The tools to bridge that gap are needed to proceed the drug development in more efficient way. The aim of this study was to combine Multistate Tuberculosis Pharmacometric (MTP) and General Pharmacodynamic Interaction (GPDI) model as a tool to aid translational predictions of drug effect in TB combination therapy from pre-clinical in vitro study into drug effect in early bactericidal activity (EBA) study. Pharmacodynamics models were built using MTP-GPDI model based on in vitro static time-kill curve of Mycobacterium tuberculosis H37Rv of isoniazid monotherapy and isoniazid-rifampicin combination data. These models were implemented in translational model by linked them with translational factors including post-antibiotic effects (PAE), mycobacterial susceptibility, inoculum effect and bacterial growth phase. To account for the change in drug concentration in human and target site concentration, population pharmacokinetics and epithelial lining fluid (ELF) parameters that have been developed for rifampicin and isoniazid were incorporated into the model prediction. The result showed that our translational models were able to predict the EBA observations from different EBA studies of isoniazid monotherapy and isoniazid-rifampicin combination. In addition, our model identified the strong antagonism of rifampicin to isoniazid. The simulation indicated that increasing the rifampicin dose will most likely improve the EBA. In contrast, increasing isoniazid dose will not give significant improvement for the EBA. These results suggest that our translational model could be potentially implemented in dose selection for early TB clinical trial as well as to optimize current TB treatment.

Place, publisher, year, edition, pages
2018.
Keywords [en]
pharmacometric, tuberculosis, translational model
National Category
Pharmaceutical Sciences
Identifiers
URN: urn:nbn:se:uu:diva-356429OAI: oai:DiVA.org:uu-356429DiVA, id: diva2:1235725
Subject / course
Pharmaceutical Biosciences
Educational program
Master Programme in Drug Discovery and Development
Presentation
2018-05-30, 15:45 (English)
Supervisors
Examiners
Available from: 2018-08-21 Created: 2018-07-27 Last updated: 2018-08-21Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association
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Language
  • de-DE
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  • en-US
  • fi-FI
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Output format
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