A discovery-driven project utilising access to dialysis effluent specimens from patients with peritoneal dialysis-associated peritonitis to elucidate the breadth, diversity and relative contribution of factors associated with susceptibility to, and early development of, serious infections in sterile body sites. The project aims to improve outcomes for high-risk patients by identifying novel risk factors, biomarkers predictive of poor outcomes following infection and novel avenues of intervention.
Serious infections are time-crucial emergencies in which every hour without appropriate antimicrobial therapy can increase the risk of severe adverse outcomes (including death) by up to 6.9%. Existing microbiology workflows can take as much as two to five days to return actionable data to clinicians treating patients with serious infection.
This project aims to demonstrate the potential benefits to both individual patients, and the health system, by implementing novel rapid diagnostic tests that can detect the presence of infection and predict the appropriate antimicrobial for treatment within hours and not days.
Sepsis is a life-threatening condition that requires timely and targeted treatment to reduce the risk of death and long-term complications. Diagnosis and treatment often rely on antimicrobial susceptibility testing (AST), which can take several days to return results. This delay contributes to poorer outcomes and increases the use of broad-spectrum antibiotics, a key driver of antimicrobial resistance. New rapid AST technologies may improve care, but there is limited evidence on their potential impact compared to current practice.
This project aims to map the typical clinical pathway of patients undergoing AST in Western Australian public hospitals and estimate the potential clinical and economic benefits of faster diagnosis. The student will examine
- the average time to diagnosis using standard AST
- the relationship between diagnostic timing, antibiotic treatment and outcomes such as length of stay and mortality
- the potential cost savings of earlier treatment.
The student will work under supervision to extract clinical data from medical records, hospital databases (e.g. iSoft and BOSSnet), and microbiology reports in the PathWest Laboratory Information System. This includes information on time of presentation, timing of AST results, antibiotic administration, discharge or death, and hospital costing data (e.g. diagnosis-related group codes). The student will then assist in data cleaning, descriptive analysis, and basic statistical modelling to identify patterns and potential opportunities for earlier intervention. The findings will inform future implementation of rapid diagnostic technologies in sepsis care and antimicrobial stewardship.
There are 5 million deaths associated with antibiotic resistant infections every year: this is projected to accelerate and eclipse all other causes of death combined by 2050. The rates of antibiotic resistance are increasing rapidly with current levels already greater than expected until well into the next decade. An analysis of severe infection in Australia showed that the total financial burden to the healthcare system likely to exceed approximately AUD$1.5 billion each year. The dwindling supply of effective antibiotic treatments, combined with the lack of new antibiotic drugs being developed, has led to a resurgence in interest in bacteriophages as an option for treatment of serious infections.
Bacteriophages (or phages) are viruses that can infect and kill bacteria. In a clinical setting, they can be used to treat bacterial infections. However, before they can be used, a pathology laboratory must first identify the specific phage that can target the specific bacteria causing the infection. This process is called bacteriophage typing – and currently takes more than five days to perform with existing technology – in some cases even weeks. There are approved programs enabling the use of phages for serious infections already underway, but the lack of rapidity and precision in phage typing remains a significant unsolved barrier to impact, with less than 6% of requests for use being fulfilled due to these limitations.
We have developed Phlow, a methodology for bacteriophage typing that delivers results in hours, rather than days. Utilising an ultra-rapid flow cytometry-assisted screening tool we will demonstrate that we can provide actionable pathology information to meet the clinical need for evidence to guide phage therapy.
Heteroresistance is a phenomenon where a subpopulation of bacterial cells within an isolate exhibits significantly higher antibiotic resistance than the majority. It is an increasingly recognised but underdiagnosed form of antimicrobial resistance (AMR) and poses a major clinical challenge, often leading to treatment failure. The limitations of current diagnostic methods mean that heteroresistance goes undetected in routine clinical practice, contributing to poor patient outcomes and the continued evolution of resistance.
The current gold standard for heteroresistance detection, population analysis profiling with area under the curve (PAP-AUC), is highly sensitive but labour-intensive, slow and impractical for widespread clinical implementation. Genomic analyses have identified some mechanisms underlying heteroresistance. However, in many cases, no genomic changes are detected. We have developed a complementary, flow cytometry-based phenotyping assay as a rapid alternative for heteroresistance detection. This project aims to address gaps in current knowledge and capability by systematically characterising heteroresistance using a large repository of clinical bacterial isolates. We will:
- determine heteroresistance prevalence across key pathogens using PAP-AUC
- evaluate the accuracy and speed of our novel flow-based heteroresistance detection assay
- investigate genomic drivers of heteroresistance to uncover molecular mechanisms
- integrate clinical data to assess the impact of heteroresistance on patient outcomes, including treatment success, recurrence, and mortality.
By combining phenotypic, molecular, and clinical data, this study will provide a unique comprehensive understanding of heteroresistance and its clinical significance. If validated our flow-based assay could provide a rapid, scalable diagnostic tool, enabling earlier detection and more effective treatment strategies to combat AMR.
Chronic Kidney Disease (CKD) is one of the leading contributors to premature death in Australia and worldwide, and access to care for end-stage disease is becoming more difficult as health systems struggle to meet demand. Identifying opportunities for early intervention is crucial to halt the progression of the disease. This project will address this unmet need by modelling CKD through a unique population-wide dataset of linked pathology and hospital data in Western Australia. The project will:
- Generate new insights on the incidence, prevalence and rates of progression of CKD across WA.
- Assess utilisation of guideline-based care for CKD.
- Examine the cost and effectiveness of current and evolving strategies to prevent and treat CKD across the severity of CKD disease.
Autoimmune and autoinflammatory diseases (AADs) are systemic illnesses that are chronic, lifelong and result in cumulative morbidity as a consequence of delayed diagnosis and variable treatment efficacy. AADs adversely impact life expectancy with a four-fold increase in mortality and often afflict young adults, impacting their most productive years and life trajectories. AADs affect 10% of the population worldwide with up to 18% of the US population having significant autoantibodies. The incidence and prevalence of AADs are rising, with some increasing by 3-4% per annum over the last 30 years. AADs are a major burden on Australian health, accounting for 13% of total Australian disease burden and incurring the highest spending for any category of disease in Australian healthcare at AUD$14 billion per annum (10.3% of annual budget).
This project will involve clinical and immunological phenotyping of patients with autoimmune diseases referred to tertiary referral services in Western Australia, who will be recruited for omics analysis as part of the ACORN collaborative, led by Professor Simon Jiang at the ANU.
