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Model-based relationship between the molecular bacterial load assay and time-to-positivity in liquid culture
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. (Farmakometri)
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(English)Manuscript (preprint) (Other academic)
Abstract [en]

The molecular bacterial load (MBL) assay is a new tuberculosis biomarker, a substantially faster, contamination-free alternative to the current standard assay of time-to-positivity (TTP) in liquid culture. The MBL-TTP relationship has not been thoroughly studied. We aimed to develop a semi-mechanistic model for MBL and identify the MBL-TTP relationship in patients. The model was developed on data from 105 tuberculosis patients with joint MBL and TTP observations collected for 12 weeks. Treatment consisted of isoniazid, pyrazinamide and ethambutol in standard doses together with rifampicin 10 or 35 mg/kg. The developed MBL-TTP model was semi-mechanistic, including several linked sub-models; a sputum sub-model describing decline of bacterial load in sputum,  a mycobacterial growth model describing growth in liquid culture and a hazard model translating bacterial growth in liquid culture to the probability of a positive TTP signal. Additional components for contaminated and negative TTP samples were included in the final model. The model gave good fit to the observed data. The model predicted greater total sample loss for TTP than MBL due to contamination and negative samples. The model detected an increase in bacterial killing for 35 versus 10 mg/kg rifampicin (p=0.002). In conclusion, a semi-mechanistic combined model for MBL and TTP was developed that described the MBL-TTP relationship. The MBL-TTP model can distinguish regimen efficacy in clinical trials, as a full MBL-TTP model or each sub-model used separately. Secondly, the model can be used to predict biomarker response for MBL given TTP data or vice versa in historical or future trials.

Keywords [en]
Pharmacometrics, Pharmacodynamics, Modelling, Biomarker, Tuberculosis
National Category
Pharmaceutical Sciences
Research subject
Pharmaceutical Science
Identifiers
URN: urn:nbn:se:uu:diva-379314OAI: oai:DiVA.org:uu-379314DiVA, id: diva2:1296386
Available from: 2019-03-15 Created: 2019-03-15 Last updated: 2019-03-15
In thesis
1. Pharmacometric Models to Improve the Treatment and Development of Drugs against Tuberculosis
Open this publication in new window or tab >>Pharmacometric Models to Improve the Treatment and Development of Drugs against Tuberculosis
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

With 10 million new infections yearly, tuberculosis has a major impact on the human well-being of the world. Most patients have infections susceptible to a first-line treatment with a treatment success rate of 80%, a number that can potentially be improved by optimising the first-line treatment. Besides susceptible disease, each year half a million patients are infected by tuberculosis with resistance to first-line treatment where only 50% of patients get cured. Thus, new drugs against resistant tuberculosis are desperately needed but given the inefficiency of developing new anti-tuberculosis drugs, enough new drugs will not reach patients in time. The aim of this thesis was to develop pharmacometric models to optimise the development and use of current and future drugs for treating tuberculosis.

A population pharmacokinetic model for rifampicin, the most prominent first-line drug, was developed and later used for developing exposure-response models followed by clinical trial simulations. The developed exposure-response models were based on liquid culture data and were expanded to describe the relationship between liquid culture results and a new biomarker, the molecular bacterial load assay which is a quicker alternative to liquid culture and is also contamination-free.

The in vitro-derived semi-mechanistic Multistate Tuberculosis Pharmacometric (MTP) model was applied to clinical rifampicin and clofazimine colony forming unit datasets. This novel application of the MTP model allowed detection of statistically significant exposure-response relationships between rifampicin and clofazimine for the specific killing of non-multiplying, persister bacteria. Furthermore, the MTP model was compared to conventional statistical analyses for detecting drug effects in Phase IIa. If designing and analysing Phase IIa using the MTP model, the required sample size for detecting drug effects can be lowered. An improved design and analysis of pre-clinical treatment outcome assessments was developed which increased the information gain compared to a conventional design yet kept the animal use at a minimum. Lastly, a therapeutic drug monitoring approach was suggested based on updated targets for rifampicin, a framework easily expandable to second-line drugs.

In conclusion this thesis presents the development of pharmacometric models which will streamline both the development and use of drugs against tuberculosis.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2019. p. 77
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 267
Keywords
Pharmacokinetics, Pharmacodynamics, Biomarkers, Rifampicin, Clofazimine, Therapeutic drug monitoring, Time-to-event, Time-to-positivity, Molecular bacterial load assay
National Category
Pharmaceutical Sciences
Research subject
Pharmaceutical Science
Identifiers
urn:nbn:se:uu:diva-379359 (URN)978-91-513-0598-1 (ISBN)
Public defence
2019-05-03, B21, BMC, Husargatan 3, Uppsala, 09:15 (English)
Opponent
Supervisors
Available from: 2019-04-12 Created: 2019-03-15 Last updated: 2019-05-07

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Svensson, Robin J.Simonsson, Ulrika S H

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