DC-ren

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Drug combinations for rewriting trajectories of renal pathologies in type II diabetes

From the project website: 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. Individual variance in disease progression and response to treatment is considered limited. For many and especially chronic and age-associated diseases however the situation is more intricate. While the sequence of symptoms, pathophysiology, treatment and outcome still holds true for a cohort, we observe clinically inter-individual and longitudinal intra-individual heterogeneity in disease progression as well as response to therapy. In this scenario, precision in diagnosis and treatment needs improvement by fostering repeated 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.

DC-ren focuses on DKD, a severe long–term complication of type II diabetes mellitus (T2DM), which is characterized by alterations in glucose metabolism caused by insulin resistance. DKD, a gradual loss of renal function leading to end stage renal failure, is per se a complex disorder, which is further modulated by a high burden of co-morbidities. Complexity is also evident on the level of pathophysiology and guidelines recommend drug combination therapy. In recent years, treatment choices have increased, with several novel drugs with proven renal as well as cardiovascular benefit entering the market. Patients with DKD display remarkable inter-, and longitudinal intra-individual variability in disease progression and response to certain drug combinations. Thus, there is an evident clinical need for adding precision in treatment via personalization. The central objective of DC-ren is to provide a decision support technology for selecting the optimal drug combination treatment to improve the prognosis on the level of individual patients with DKD.

While pursuing a clear focus on DKD, we are confident that our novel methodological approaches have the potential for serving as blueprint for adding precision in treatment of complex chronic disorders in general.

Alessandro Torcinovich
Alessandro Torcinovich
Passionate machine (meta) learner

Passionate machine (meta) learner