Personalization & Precision Medicine
Current medical practice relies on a catalogue of diseases, each defined by pathophysiology, symptoms and outcomes. In case of strict causality a specific diagnosis has one clinical consequence and this “action-reaction” scheme then applies for all subjects affected. Inter-individual variance in disease progression and response to treatment is fairly limited. For many, especially chronic and age-associated diseases however the situation is more intricate. While symptoms, treatment and outcome still hold true for a cohort, we observe individual heterogeneity in disease progression as well as response to therapy. In this scenario precision in diagnosis and treatment needs improvement by fostering stratification and personalization, particularly if different treatment options are available.
The latter is the aim of the collaborative R&D initiative DC-ren in an extremely relevant disorder: Diabetic Kidney Disease (DKD). DC-ren, the abbreviation for “Drug combinations for rewriting trajectories of renal pathologies in type II diabetes”, has started in 2020 with a runtime of 5 years. DC-ren has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 848011.
”The good physician treats the disease; the great physician treats the patient who has the disease.Sir William Osler, 1903
Disease & treatment: a dynamical system
Guidelines recommend regular monitoring of renal excretory function in T2DM by a laboratory parameter called “eGFR”. Of note, not all patients with T2DM develop DKD, and those who do loose eGFR with a remarkable inter-, but also intra-individual variability over many years. This is due to the complex interaction of genetic predisposition and environmental factors that results in a personalized trajectory of development and progression of DKD.
Formally DKD evolves as a sequence of pathophysiological states being causally linked by action-reaction. Certain trajectories resemble a fast decline of eGFR while others result in a fairly stable situation. Inter-individual heterogeneity is further complicated by intra-individual variability. Some states may result in stable or even improving renal function, others in rapid decline and some may see rapid transition while others are stable for years. A state is defined by its underlying pathophysiology, and we have to keep in mind that this is the point of action of drugs. Therefore drugs exhibit beneficial effects only in certain states, while they fail in others. When applying such a state model we can capture inter-, but also intra-individual variance in drug response.
DC-ren follows the concept of individualized trajectories of state transitions with state-specific drug response according to underlying pathophysiology. Such a setting is conceptually well established in the scientific domain of dynamical systems research.
According to a dynamical systems approach (individualized trajectories of state evolution combined with state-specific drug response) the DC-ren work plan takes care of three central R&D aspects:
The translational focus of DC-ren is to establish and validate a decision support software application for optimizing combination drug therapy in patients with DKD on a personalized level in a “technology readiness level 6” prototype (i.e. allowing practical demonstration in a relevant environment).
For implementation a validation study, leveraging on existing clinical trial repositories and realized as a “virtual trial”, will test if technology-mediated decisions add in precision in personalized drug response prediction when compared to present clinical guidelines. This validation is pivotal for moving the decision support solution in higher technology readiness levels, and ultimately in clinical settings.
On top, we test the decision support solution in two relevant application scenarios, namely in DKD drug R&D and compound recovery:
Contemporary clinical research critically depends on interdisciplinary teams, and DC-ren balances theoretical, experimental and clinical expertise. The DC-ren analytical concept routes in applied Category Theory, a framework providing concepts and tools for modeling dynamical systems. Its specific strength is the representation of composite function, in DC-ren being distinct DKD pathologies at interference with drug mechanism of action. Translating the concept via combining statistics and simulation on the basis of a rich clinical and molecular data space allows taking a novel perspective for assessing personalized drug response as hybrid AI solution. We leverage on extensive biobanks and clinical data repositories readily capturing personalized response to various drugs approved for DKD.
We complement clinical phenotyping with top-level molecular profiling, going for multiplexed assays and proteomics. This will provide us with a targeted data matrix for capturing disease mechanisms and drug impact at the effector level of molecular processes: A System-of-Systems. All analytical and experimental work is embedded in strong clinical research for assuring technology development right in focus of patient needs. Practical implementation follows agile software development tailored at reaching a prototype decision support platform, finally evaluated in dedicated validation and DKD drug application studies. With this setting DC-ren bridges from a novel concept to a clinical solution with substantial technology readiness level.
We are committed to collaborative R&D, and cordially invite stakeholders to open discussions eventually leading to joint initiatives.
Personalization, be it novel methods for patient stratification or adaptive design of clinical studies imposes challenges on regulatory procedures. We actively link with regulatory agencies together with experts in health technology assessment for moving personalization strategies to a next level of implementation.
You are in basic science disciplines as listed above and want to explore translation opportunities? Link with us! The DC-ren team covers a wide range of academic disciplines, including applied computer science, statistics & simulation, omics & biomarkers, all embedded in clinical research and complemented by software architecture design and implementation.
The collaborative research project DC-ren is coordinated by Univ. Prof. Dr. Gert Mayer, Medical University of Innsbruck, Austria.
Please use the following means for interacting with DC-ren:
Department of Internal Medicine IV (Nephrology and Hypertension)
Medical University Innsbruck
6020 Innsbruck / Austria