POTENTIAL IMPACT AND EXPLOITATION OF EXPECTED PROJECT RESULTS
The proposed project employs risk and therapy response prediction in a recently not well understood and managed disease to avoid a potential deadly outcome (ESRD) by an innovative, recently not employed fashion. By using a biological integral of risk and therapy response prediction (the urine proteomic profile) without having investigated single pathophysiological pathways, we make use of a system-biological approach in a disease that withstands conventional risk estimation and therapy prediction. If successful, we expect a direct impact of the project results on patient management, also since no novel therapeutic approach has to be implemented. The interactions with regulators and patient organisations are expected to further ease and expedite implementation.
Given the very high cost of CKD, it is expect that a successful approach will also present a health economic benefit, which is expected to be demonstrated in the models developed in this project. The demonstration of a health-economic benefit will further support implementation (and consequently delivering a clear and measurable impact), especially in the discussions with payers (public health insurance). It is further expected that this or a similar approach will be of high interest to the pharmaceutical industry. This is especially the case in clinical trials where a major issue is identifying patients that will benefit from treatment.
If successful, this approach is expected to serve as a proof-of-principle towards guiding therapy and management decision in other diseases as well. Examples may be characterised by interaction of acute inflammatory phenomena with long-term processes of cellular dedetermination, function loss and scarring, e.g. the inflammation initiation of liver cirrhosis after hepatitis or the myocardial scarring in ischemic congestive heart failure.
The proposed two-stage investigational process combining retrotransfer to other diseases and the urinary proteomic approach (with alternative patterns) can be used as a unifying model at least in kidney diseases. In principal, urine proteomics is well suitable for high-throughput analyses that can be made available on a mass scale. However, currently such a scalable approach is hampered by missing high-significant results in particular diseases which pave the way to routine application. Such deficits will be addressed by the current project.