Personalized Medicine for Acute Kidney Injury: Patient Recruitment and Clinical Analyses
Post Details: Applications are invited for an SEUPB funded PhD studentship, tenable in Ulster University (UU), Magee campus in collaboration with Altnagelvin Hospital at L/Derry and Letterkenny General Hospital in Donegal. This studentship is part of our €8.6 million cross-border research project, led by Ulster University’s Northern Ireland Centre for Stratified Medicine funded by the EU’s INTERREG VA programme, managed by the Special EU Programmes Body.
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Acute Kidney Injury (AKI) is a significant condition associated with adverse outcomes for patients, and has important health economic implications. Often associated with multi-morbid conditions, its occurrence is associated with increased risk of complications including cardiovascular events, residual renal damage leading to chronic kidney disease, risks of long term dialysis dependence, and increased mortality. It is also associated with prolonged length of stay and hospitalization leading to increase risk of hospital acquired complications. The introduction of electronic alerts has improved the identification of patients with acute kidney injury, however, there remain significant uncertainties with regards to the optimal way of managing these patients. Strategies that have been centered on early intervention have had mixed results including complications of therapy. Acute kidney injury can be the outcome of many diverse pathological processes. To address the question with respect to optimal pathways of management, a better model for stratifying those who are at greatest risk for long-term morbidity or mortality will assist in therapeutic decision-making. Biomarkers have been suggested as having potential utility for allowing this. However, the best biomarker, or combination of biomarkers, remains uncertain. The role of different genotypes and susceptibility to developing an event such as AKI is also uncertain.
This project aims to recruit patients, collect and analyze clinical data such as urinary and blood-based biomarkers, genotypes, lifestyle, medical history, and diagnoses, correlating it with significant clinical outcomes. This will result in large amount of data available to be analyzed. Advanced computational techniques will then be used to develop a risk stratification model for AKI. The project will be highly multidisciplinary, combining the computational and laboratory processing expertise at UU and clinical expertise in management of AKI at Altnagelvin Hospital and Letterkenny General Hospital on a cross-border basis.
In collaboration with our enterprise partners, we aim to develop a risk stratification model that is based on measurement of biomarkers of AKI as well as relevant clinical information of patients (including, age, gender, comorbid conditions, socioeconomic class, postal code and diagnoses). Samples will also be collected to see if there are specific genotypes of patients that are more susceptible to the development of AKI. The development of an appropriate risk stratification model will assist with earlier introduction of targeted therapy, including dialysis to appropriate patients.
In collaboration with our enterprise partners, there is potential for developing Clinical Decision tools for greater accuracy in risk stratification, utilizing some or all of the identified clinical and biomarker parameters in the models developed. It may allow redesign of care pathways and earlier identification of patients with susceptible risk factors for those in Primary care. It is anticipated that this would translate into improved outcomes for patients with AKI.
Deliverables: It is expected that project will lead to a greater understanding with regards to modeling risk for a diverse group of patients with AKI. The combination and utilization of a relevant panel of biomarkers, with advanced computational tools, will allow for development of a better diagnostic pathway. This will support clinical decisions on level of intervention for patients with AKI. The students will be trained across methods designed to assess the merits of different biomarkers and expected to have co-authorship on high impact papers. The PhD students will be trained across multiple disciplines, including laboratory and clinical processes that will advance the future of AKI.
Clinical PhD-Project: Personalized Medicine for Acute Kidney Injury: Patient Recruitment and Clinical Analyses.
The project involves the recruitment of patients and acquisition of clinical data and biological samples that will be subjected to a range of tests. Patients will be consented into the project based on their fulfillment of relevant biochemical parameter for development of AKI, amongst those admitted as inpatients. We would expect an average number of 900-1000 patients per year with AKI to be available for recruitment. A quarter of such patients at Altnagelvin and Letterkenny University Hospital would have severe AKI. The project will involve patient recruitment and longitudinal follow up with respect to both short term and longer-term outcomes, specifically with regards to renal function recovery, dialysis dependency or mortality. The project will involve undertaking additional biochemical or genetic tests including the use of point of care devices.
Applicants should hold a first or upper second class honours degree in Biomedical Sciences, Stratified Medicine, Medicine or a cognate area, and be able to demonstrate strong cross-disciplinary interest. Applications will be considered on a competitive basis with regard to the candidate’s qualifications, skills experience and interests. Successful candidates will enroll as of 1 October 2017 or 1st January 2018, on a full-time programme of research studies leading to the award of the degree of Doctor of Philosophy. The studentship will comprise fees together with an annual stipend awarded for a period of up to 3 years subject to satisfactory progress.
Additional Information & Application Process: If you wish to discuss your proposal or receive advice on this project please contact:- Professor Bjourson (email@example.com), Professor Liam Maguire (firstname.lastname@example.org), Dr. Ying Kuan (Ying.Kuan@westerntrust.hscni.net) or Dr. Anne-Marie Moran (AnneMarie.Moran@hse.ie). Interested parties can visit the web sites for the Intelligent Systems Research Centre Ulster University: http:// http://isrc.ulster.ac.uk/ or Altnagelvin Area Hospital: http://www.westerntrust.hscni.net/AltnagelvinHospital.htm. For more information on applying go to ulster.ac.uk/research and apply online ulster.ac.uk/applyonline.
Deadline: August 14, 2017