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The research leading to these results has received funding from the Swedish Research Council (grant number 521-2011-3442) in addition to the Innovative Medicines Initiative Joint Undertaking (www.imi.europe.eu) under grant agreement no. 115337, resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007–2013) and European Federation of Pharmaceutical Industries and Associations (EFPIA) companies' in kind contribution. ; Background : The demand for new anti-TB drugs is high, but development programmes are long and costly. Consequently there is a need for new strategies capable of accelerating this process. Objectives : To explore the power to find statistically significant drug effects using a model-based pharmacokinetic–pharmacodynamic approach in comparison with the methods commonly used for analysing TB Phase IIa trials. Methods : Phase IIa studies of four hypothetical anti-TB drugs (labelled A, B, C and D), each with a different mechanism of action, were simulated using the multistate TB pharmacometric (MTP) model. cfu data were simulated over 14 days for patients taking once-daily monotherapy at four different doses per drug and a reference (10 mg/kg rifampicin). The simulated data were analysed using t-test, ANOVA, mono- and bi-exponential models and a pharmacokinetic–pharmacodynamic model approach (MTP model) to establish their respective power to find a drug effect at the 5% significance level. Results : For the pharmacokinetic–pharmacodynamic model approach, t-test, ANOVA, mono-exponential model and bi-exponential model, the sample sizes needed to achieve 90% power were: 10, 30, 75, 20 and 30 (drug A); 30, 75, 245, 75 and 105 (drug B); 70, >1250, 315, >1250 and >1250 (drug C); and 30, 110, 710, 170 and 185 (drug D), respectively. Conclusions : A model-based design and analysis using a pharmacokinetic–pharmacodynamic approach can reduce the number of patients required to determine a drug effect at least 2-fold compared with current methodologies. This could significantly accelerate early-phase TB drug development. ; Publisher PDF ; Peer reviewed

This work was supported by the Medical Research Council [grant number MR/P014704/1] and the PreDiCT-TB consortium (IMI Joint undertaking grant agreement number 115337, resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007-2013) and EFPIA companies' in kind contribution. ; If improvements are to be made in tuberculosis (TB) treatment, an increased understanding of disease in the lung is needed. Studies have shown that bacteria in a less metabolically active state, associated with the presence of lipid bodies, are less susceptible to antibiotics, and recent results have highlighted the disparity in concentration of different compounds into lesions. Treatment success therefore depends critically on the responses of the individual bacteria that constitute the infection. We propose a hybrid, individual-based approach that analyses spatio-temporal dynamics at the cellular level, linking the behaviour of individual bacteria and host cells with the macroscopic behaviour of the microenvironment. The individual elements (bacteria, macrophages and T cells) are modelled using cellular automaton (CA) rules, and the evolution of oxygen, drugs and chemokine dynamics are incorporated in order to study the effects of the microenvironment in the pathological lesion. We allow bacteria to switch states depending on oxygen concentration, which affects how they respond to treatment. This is the first multiscale model of its type to consider both oxygen-driven phenotypic switching of the Mycobacterium tuberculosis and antibiotic treatment. Using this model, we investigate the role of bacterial cell state and of initial bacterial location on treatment outcome. We demonstrate that when bacteria are located further away from blood vessels, less favourable outcomes are more likely, i.e. longer time before infection is contained/cleared, treatment failure or later relapse. We also show that in cases where bacteria remain at the end of simulations, the organisms tend to be slower-growing and are often located within granulomas, surrounded by caseous material. ; Publisher PDF ; Peer reviewed

Funding: UK Engineering and Physical Sciences Research Council for funding through grant EP/P030017/1 and fellowship EP/L025035/1. This work was also supported by the PreDiCT-TB consortium [IMI Joint undertaking grant agreement number 115337, resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007–2013) and EFPIA companies' in kind contribution (www.imi.europa.eu)] and the PanACEA consortium [funded by the European & Developing Countries Clinical Trials Partnership (EDCTP); grant agreement: TRIA-2015-1102] ; Tuberculosis (TB) remains a leading cause of death worldwide. Lipid rich, phenotypically antibiotic tolerant, bacteria are more resistant to antibiotics and may be responsible for relapse and the need for long-term TB treatment. We present a microfluidic system that acoustically traps live mycobacteria, M. smegmatis, a model organism for M. tuberculosis. We then perform optical analysis in the form of wavelength modulated Raman spectroscopy (WMRS) on the trapped M. smegmatis for up to eight hours, and also in the presence of isoniazid (INH). The Raman fingerprints of M. smegmatis exposed to INH change substantially in comparison to the unstressed condition. Our work provides a real-time assessment of the impact of INH on the increase of lipids in these mycobacteria, which could render the cells more tolerant to antibiotics. This microfluidic platform may be used to study any microorganism and to dynamically monitor its response to different conditions and stimuli. ; Publisher PDF ; Peer reviewed

This work was funded by: The Swedish Research Council (grant number 521‐2011‐3442) and the Innovative Medicines Initiative Joint Undertaking (www.imi.europe.eu) under grant agreement 115337, resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007‐2013) and EFPIA companies' in kind contribution. ; A crucial step for accelerating tuberculosis drug development is bridging the gap between pre‐clinical and clinical trials. In this study, we developed a pre‐clinical model‐informed translational approach to predict drug effects across pre‐clinical systems and early clinical trials using the in vitro‐based Multistate Tuberculosis Pharmacometric (MTP) model using rifampicin as an example. The MTP model predicted rifampicin biomarker response observed in (i) a hollow‐fiber infection model, (ii) a murine study to determine PK/PD indices, and (iii) several clinical phase IIa early bactericidal activity (EBA) studies. In addition, we predicted rifampicin biomarker response at high doses of up to 50 mg/kg, leading to an increased median EBA0‐2 days (90% prediction interval) of 0.513 log CFU/mL/day (0.310; 0.701) compared to the standard dose of 10 mg/kg of 0.181 log/CFU/mL/day (0.076; 0.483). These results suggest that the translational approach could assist in the selection of drugs and doses in early‐phase clinical tuberculosis trials. ; Publisher PDF ; Peer reviewed

The research leading to these results has received funding from the Swedish Research Council in addition to the Innovative Medicines Initiative Joint Undertaking (www.imi.europe.eu) under grant agreement n°115337, resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007-2013) and EFPIA companies' in kind contribution. ; Accumulating evidence suggest that increasing doses of rifampicin may shorten tuberculosis treatment. The PanACEA HIGHRIF1 trial assessed safety, pharmacokinetics and anti-mycobacterial activity of rifampicin at doses up to 40 mg/kg. Eighty-three pulmonary tuberculosis patients received 10, 20, 25, 30, 35 or 40 mg/kg rifampicin daily over 2 weeks, supplemented with standard doses of isoniazid, pyrazinamide and ethambutol in the second week. This study aimed at characterizing rifampicin pharmacokinetics observed in HIGHRIF1 using non-linear mixed effects modeling. The final population pharmacokinetic model included an enzyme turn-over model accounting for time-dependent elimination due to auto-induction, concentration-dependent clearance and dose-dependent bioavailability. The relationship between clearance and concentration was characterized by a Michaelis-Menten relationship. The relationship between bioavailability and dose was described using an Emax relationship. The model will be key in determining exposure-response relationships for rifampicin and should be considered when designing future trials and when treating future patients with high dose rifampicin. ; Publisher PDF ; Peer reviewed

The Holistic Approach to Unravel Antibacterial Resistance in East Africa is a 3-year Global Context Consortia Award (MR/S004785/1) funded by the National Institute for Health Research, Medical Research Council and the Department of Health and Social Care. The award is also part of the EDCTP2 programme supported by the European Union. This work is supported in part by the Makerere University-Uganda Virus Research Institute Centre of Excellence for Infection and Immunity Research and Training (MUII). MUII is supported through the DELTAS Africa Initiative (grant number 107743). The DELTAS Africa Initiative is an independent funding scheme of the African Academy of Sciences and Alliance for Accelerating Excellence in Science in Africa, and is supported by the New Partnership for Africa's Development Planning and Coordinating Agency with funding from the Wellcome Trust (grant number 107743) and the UK Government. This paper was funded in part by a grant from the National Institutes of Health (grant number U01CA207167). ; Introduction Antimicrobial resistance (AMR) is a global health threat that requires urgent research using a multidisciplinary approach. The biological drivers of AMR are well understood, but factors related to treatment seeking and the social contexts of antibiotic (AB) use behaviours are less understood. Here we describe the Holistic Approach to Unravel Antibacterial Resistance in East Africa, a multicentre consortium that investigates the diverse drivers of drug resistance in urinary tract infections (UTIs) in East Africa. Methods and analysis This study will take place in Uganda, Kenya and Tanzania. We will conduct geospatial mapping of AB sellers, and conduct mystery client studies and in-depth interviews (IDIs) with drug sellers to investigate AB provision practices. In parallel, we will conduct IDIs with doctors, alongside community focus groups. Clinically diagnosed patients with UTI will be recruited from healthcare centres, provide urine samples and complete a questionnaire capturing retrospective treatment pathways, sociodemographic characteristics, attitudes and knowledge. Bacterial isolates from urine and stool samples will be subject to culture and antibiotic sensitivity testing. Genomic DNA from bacterial isolates will be extracted with a subset being sequenced. A follow-up household interview will be conducted with 1800 UTI-positive patients, where further environmental samples will be collected. A subsample of patients will be interviewed using qualitative tools. Questionnaire data, microbiological analysis and qualitative data will be linked at the individual level. Quantitative data will be analysed using statistical modelling, including Bayesian network analysis, and all forms of qualitative data analysed through iterative thematic content analysis. ; Publisher PDF ; Peer reviewed

The Holistic Approach to Unravel Antibacterial Resistance in East Africa is a 3-year Global Context Consortia Award (MR/S004785/1) funded by the National Institute for Health Research, Medical Research Council and the Department of Health and Social Care. The award is also part of the EDCTP2 programme supported by the European Union. This work is supported in part by the Makerere University-Uganda Virus Research Institute Centre of Excellence for Infection and Immunity Research and Training (MUII). MUII is supported through the DELTAS Africa Initiative (grant number 107743). The DELTAS Africa Initiative is an independent funding scheme of the African Academy of Sciences and Alliance for Accelerating Excellence in Science in Africa, and is supported by the New Partnership for Africa's Development Planning and Coordinating Agency with funding from the Wellcome Trust (grant number 107743) and the UK Government. This paper was funded in part by a grant from the National Institutes of Health (grant number U01CA207167). ; Introduction Antimicrobial resistance (AMR) is a global health threat that requires urgent research using a multidisciplinary approach. The biological drivers of AMR are well understood, but factors related to treatment seeking and the social contexts of antibiotic (AB) use behaviours are less understood. Here we describe the Holistic Approach to Unravel Antibacterial Resistance in East Africa, a multicentre consortium that investigates the diverse drivers of drug resistance in urinary tract infections (UTIs) in East Africa. Methods and analysis This study will take place in Uganda, Kenya and Tanzania. We will conduct geospatial mapping of AB sellers, and conduct mystery client studies and in-depth interviews (IDIs) with drug sellers to investigate AB provision practices. In parallel, we will conduct IDIs with doctors, alongside community focus groups. Clinically diagnosed patients with UTI will be recruited from healthcare centres, provide urine samples and complete a questionnaire capturing retrospective treatment pathways, sociodemographic characteristics, attitudes and knowledge. Bacterial isolates from urine and stool samples will be subject to culture and antibiotic sensitivity testing. Genomic DNA from bacterial isolates will be extracted with a subset being sequenced. A follow-up household interview will be conducted with 1800 UTI-positive patients, where further environmental samples will be collected. A subsample of patients will be interviewed using qualitative tools. Questionnaire data, microbiological analysis and qualitative data will be linked at the individual level. Quantitative data will be analysed using statistical modelling, including Bayesian network analysis, and all forms of qualitative data analysed through iterative thematic content analysis. Ethics and dissemination Approvals have been obtained from all national and local ethical review bodies in East Africa and the UK. Results will be disseminated in communities, with local and global policy stakeholders, and in academic circles. They will have great potential to inform policy, improve clinical practice and build regional pathogen surveillance capacity. ; Publisher PDF ; Peer reviewed