Digital Patients

"Smart Patients and other online communities are demonstrating that patients can learn a tremendous amount from one another"
― Robert Wachter, The Digital Doctor: Hope, Hype, and Harm at the Dawn of Medicine’s Computer Age

Development of personalized model of a patient for diagnostics, prediction of disease progression and therapy outcome, will play a key role in the medicine of the future. This requires sophisticated integration of mechanistic and ML models trained by heterogeneous data sources. To this end, the SDL will integrate HPC resources with ML algorithms and simulations to develop model-based medical applications, ranging from molecular modeling of disease mechanisms up to patient scale system medicine models. The SDL will provide the full range of expertise from simulations of biochemical processes on a molecular scale, integration of heterogeneous data sources from genomics to clinical monitoring data with biomedical knowledge into hybrid models up to integrated image analysis on the patient scale.

Fundings

Digital Patients

Our projects:

SDL DIGITAL PATIENT & SDL FLUIDS: 'BLOOD CLOTTING'
Towards Ligand Design Against Pathological Blood Clotting: A Multiscale Simulation Approach

Digital Patients

Understanding how thrombus forms as a physicochemical process is fundamental for our ability to predict and control pathological states caused by dysfunctional blood coagulation systems. A key molecular determinant of blood coagulation is the partition between open and closed conformations of the prothrombin protein. Here, we will develop a multiscale approach by computational fluid dynamics, molecular simulations and machine-learning to investigate how molecular perturbations such as mutations and small-molecule impact on the protein’s open/close conformation ratio. Eventually, this computational scheme will lead to the design of new ligands affecting the latter, with beneficial effects in pathologies associated with aberrant blood clotting.

People involved

  • Institute for Advanced Simulation (IAS)
  • Institute of Neurosciences and Medicine (INM)
  • Computational Biomedicine (IAS-5 / INM-9)
Building 16.15 /
Room 3009
+49 2461 61 85197
E-Mail
  • Institute for Advanced Simulation (IAS)
  • Computational Biomedicine (IAS-5 / INM-9)
Building 16.15 /
Room R 3010
+49 2461/61-8941
E-Mail

Prof. Dr. Giulia Rossetti

Group leader of Drug Design Hub for Digital Neuropharmacology

  • Institute for Advanced Simulation (IAS)
  • Computational Biomedicine (IAS-5 / INM-9)
Building 16.15 /
Room 3001
+49 2461/61-8933
E-Mail

Collaborators

DIGITAL PATIENT ‘PAIN’
Understanding the Role of Sodium Channel in Pain Pathologies

Digital Patients

Specific mutation on voltage gated sodium channel can impact on pain perception mechanisms; within paroxysmal pain disorder, primary erythromelalgia has been shown to be caused by gain of function mutation on sodium channel nav1.7 isoform. As digital patient division, our group looks at the molecular understanding of a disease process in order to further characterize biomarker for a pathological state. 

People involved

  • Institute for Advanced Simulation (IAS)
  • Institute of Neurosciences and Medicine (INM)
  • Computational Biomedicine (IAS-5 / INM-9)
Building 16.15 /
Room 3009
+49 2461 61 85197
E-Mail

Prof. Dr. Giulia Rossetti

Group leader of Drug Design Hub for Digital Neuropharmacology

  • Institute for Advanced Simulation (IAS)
  • Computational Biomedicine (IAS-5 / INM-9)
Building 16.15 /
Room 3001
+49 2461/61-8933
E-Mail

Collaborators

Last Modified: 06.04.2024