This PhD opportunity is being offered as part of the LSTM and Lancaster University Doctoral Training Partnership. Find out more about the studentships and how to apply.
| Abstract | Tuberculosis (TB) remains a major global health burden with more than 1 million deaths every year. The causative agent Mycobacterium tuberculosis is the largest killer amongst bacterial infections. There is an urgent need to develop new drugs which can shorten therapy and treat drug-resistant infections. M. tuberculosis is highly adaptive and can survive in a wide variety of microenvironments including the acidic phagosome, the nutrient-poor granuloma, and the necrotic caseum within granulomas. The bacteria can also persist in the face of antibiotic treatment making therapy lengthy and complex. One common feature of these persistent organisms is a slow to non-existent replication rate. We hypothesize that this feature leads to reduced rates of antibiotic kill and that identifying new drugs with enhanced kill rates against mixed bacterial populations will lead to better and shorter TB treatment regimens. Pharmacodynamics describes how drug concentrations translate into drug efficacy and can be used to predict the best dose and timing of a drug to achieve clinical success. Pharmacodynamics studies in M. tuberculosis frequently use the minimum inhibitory concentration against replicating bacteria as the key measure to determine what drug levels are required for treatment. This may not be an accurate measure, since bacterial populations are heterogenous and may contain non-replicating and antibiotic tolerant organisms. We propose to develop a new approach to use the rate of kill against bacilli in different physiological states that are relevant to infections. We have already identified several new anti-tubercular agents with the potential for development as novel drugs with the ability to kill replicating bacteria. In this project we will determine whether these new agents can kill non-replicating bacteria generated by different environmental pressures, as well as mixed bacterial populations. These conditions will include replicating and non-replicating states, antibiotic sensitive and tolerant resistant bacteria, as well as extracellular and intracellular bacteria. We will use these data to select the best molecules to pursue further, and to predict the dose and exposure required to kill mixed populations. These data will be used to generate predictive models for in vivo pharmacodynamic predictions. The overall aims of this project are to (i) determine the in vitro pharmacodynamics of new anti-tubercular agents, (ii) determine the effect of non-replicating and tolerant bacteria on pharmacodynamics and (iii) develop a predictive model of in vivo pharmacodynamics. |
| Where does this project lie in the translational pathway? | T1 - Basic Research |
| Methodological Aspects | This project combines microbiology, pharmacological modelling, and quantitative data analysis to understand and predict drug efficacy. It includes the following
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| Expected Outputs | The expected outputs of this project include both scientific deliverables and translational impact. Scientific outputs:
Impact:
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| Training Opportunities | The student will receive training in microbiology, pharmacology, and quantitative data analysis, with a strong translational focus. They will receive training for M. tuberculosis culture (work within containment level 3 laboratories), microbial genetics, in vitro infection models, and drug efficacy assays. They will received training for the design and analysis of time–kill and dose–response experiments. Training will also include quantitative pharmacodynamic modelling, statistical analysis, and data visualization. The student will benefit from interdisciplinary supervision and collaboration with experts in microbiology, medicinal chemistry, and pharmacology. They will participate in lab meetings, journal clubs, and research seminars, and have opportunities to attend specialist workshops on pharmacometrics, modelling, and bioinformatics. Professional development will include training for presentation of research at conferences, preparation of scientific manuscripts, research ethics, project management, and science communication. |
| Skills Required | A background in biomedical or biological sciences, such as microbiology, pharmacology, biochemistry, or a related discipline. Prior experience with laboratory techniques such as microbial culture, or basic molecular biology is desirable. A background in antimicrobials or infectious disease biology would be advantageous, as would familiarity with data analysis and quantitative thinking. A strong interest in modelling or pharmacodynamics would also be beneficial, as would experience with data analysis software. The student should demonstrate analytical and problem-solving abilities, attention to detail, and enthusiasm for experimental work in a containment laboratory. Good communication and teamwork skills, along with motivation to learn interdisciplinary methods and engage in translational research, will be essential for success in this project. |
| Subject Areas | Neglected tropical diseases. Drug Discovery and Development. |
| Key Publications associated with this project |
https://pubmed.ncbi.nlm.nih.gov/40832552/ https://pubmed.ncbi.nlm.nih.gov/40827527/ https://pubmed.ncbi.nlm.nih.gov/37708378/ |