Founded in 2005 by Microsoft Research and The University of Trento, COSBI is an almost unique research centre which exploits a comprehensive systems biology pipeline starting from the integration of experimental data with knowledge extraction and the identification of biomarker signatures, to network/pathway analysis and modelling and simulation. Our mission is to turn heterogeneous biomedical data into mechanistic insight and predictive tools for R&D. The team is particularly strong in systems biology (including target and biomarker identification, drug repurposing) and systems pharmacology, in particular in mathematical modelling (including Quantitative Systems Pharmacology and PBPK). COSBI has developed advanced pipelines for modeling and simulation, exploiting mechanistic and AI-based approached, allowing for Model Informed Drug Discovery approaches (in silico hypothesis testing, dose/regimen optimization, and efficacy/safety assessment). Application areas include neurodegeneration, oncology, immune-mediated and metabolic diseases, anti-infectives and and vaccines, with a strong track record of collaborations with pharma, biotech, and academic partners, to promote personalized medicine and nutrition.
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Representatives
Group Leader
Fondazione The Microsoft Research -University of Trento Centre for Computational and Systems Biology
Mechanistic Quantitative Systems Pharmacology, models, virtual populations and in silico trial simulations for target validation, combination assessment and translational R&D decisions.
Partner seeks Consortium/Coordinator
Destination 3: HORIZON-HLTH-2027-02-DISEASE-01-two-stage: Innovative healthcare interventions for non-communicable diseases
Destination 3: HORIZON-HLTH-2027-01-DISEASE-08: Development of innovative antimicrobials against pathogens resistant to antimicrobials
Destination 3: HORIZON-HLTH-2027-02-DISEASE-14-two-stage: Clinical trials for advancing innovative interventions for neurodegenerative
Destination 5: HORIZON-HLTH-2027-03-TOOL-04: Virtual Human Twins (VHTs) for integrated clinical decision support in prevention and diagnosis
Destination 4: HORIZON-HLTH-2027-01-CARE-02: Personalised approaches to reduce risks from Adverse Drug Reactions due to administration of multiple medications
Destination 5: HORIZON-HLTH-2027-02-TOOL-01-two-stage: Development of predictive biomarkers of disease progression and treatment response by using AI methodologies for chronic non-communicable diseases
Author
Group Leader at Fondazione The Microsoft Research -University of Trento Centre for Computational and Systems Biology
AI-based extraction of traceable biomedical knowledge from literature, clinical trials and databases for target discovery, mechanism mapping and evidence synthesis.
Partner seeks Consortium/Coordinator
Destination 3: HORIZON-HLTH-2027-02-DISEASE-01-two-stage: Innovative healthcare interventions for non-communicable diseases
Destination 5: HORIZON-HLTH-2027-03-TOOL-08: Towards the next generation of frontier Artificial Intelligence models for healthcare
Destination 3: HORIZON-HLTH-2027-01-DISEASE-06: Development of monoclonal antibodies to prevent and treat infections from Flaviviruses
Destination 3: HORIZON-HLTH-2027-01-DISEASE-08: Development of innovative antimicrobials against pathogens resistant to antimicrobials
Destination 3: HORIZON-HLTH-2027-02-DISEASE-14-two-stage: Clinical trials for advancing innovative interventions for neurodegenerative
Destination 5: HORIZON-HLTH-2027-03-TOOL-04: Virtual Human Twins (VHTs) for integrated clinical decision support in prevention and diagnosis
Destination 3: HORIZON-HLTH-2027-01-DISEASE-05: Development of novel small molecule antiviral therapeutics for pathogens with epidemic potential
Destination 4: HORIZON-HLTH-2027-01-CARE-02: Personalised approaches to reduce risks from Adverse Drug Reactions due to administration of multiple medications
Destination 2: HORIZON-HLTH-2027-01-ENVHLTH-02: Integrating climate-related exposures into the human exposome and characterising its changes in response to climate change
Destination 3: HORIZON-HLTH-2027-01-DISEASE-07: Development of monoclonal antibodies to prevent and treat infections from Filo-, Nairo-, Phenui-, Picorna- and Toga viruses
Destination 5: HORIZON-HLTH-2027-02-TOOL-01-two-stage: Development of predictive biomarkers of disease progression and treatment response by using AI methodologies for chronic non-communicable diseases
Author
Group Leader at Fondazione The Microsoft Research -University of Trento Centre for Computational and Systems Biology
Integration of GWAS, transcriptomics, single-cell, proteomics and metabolomics to identify targets, pathways, patient subgroups and robust biomarker signatures.
Partner seeks Consortium/Coordinator
Destination 2: HORIZON-HLTH-2027-01-ENVHLTH-MISSCLIMA-03: Tools and technologies to support health adaptation to climate change
Destination 3: HORIZON-HLTH-2027-01-DISEASE-06: Development of monoclonal antibodies to prevent and treat infections from Flaviviruses
Destination 3: HORIZON-HLTH-2027-01-DISEASE-08: Development of innovative antimicrobials against pathogens resistant to antimicrobials
Destination 3: HORIZON-HLTH-2027-01-DISEASE-05: Development of novel small molecule antiviral therapeutics for pathogens with epidemic potential
Destination 4: HORIZON-HLTH-2027-01-CARE-02: Personalised approaches to reduce risks from Adverse Drug Reactions due to administration of multiple medications
Destination 2: HORIZON-HLTH-2027-01-ENVHLTH-02: Integrating climate-related exposures into the human exposome and characterising its changes in response to climate change
Destination 3: HORIZON-HLTH-2027-01-DISEASE-07: Development of monoclonal antibodies to prevent and treat infections from Filo-, Nairo-, Phenui-, Picorna- and Toga viruses
Destination 5: HORIZON-HLTH-2027-02-TOOL-01-two-stage: Development of predictive biomarkers of disease progression and treatment response by using AI methodologies for chronic non-communicable diseases
Author
Group Leader at Fondazione The Microsoft Research -University of Trento Centre for Computational and Systems Biology
Computational biology partner for R&D consortia requiring QSP, PBPK, multi-omics, knowledge extraction, target discovery or drug repurposing capabilities.
Partner seeks Consortium/Coordinator
Destination 3: HORIZON-HLTH-2027-02-DISEASE-01-two-stage: Innovative healthcare interventions for non-communicable diseases
Destination 2: HORIZON-HLTH-2027-01-ENVHLTH-MISSCLIMA-03: Tools and technologies to support health adaptation to climate change
Destination 5: HORIZON-HLTH-2027-03-TOOL-08: Towards the next generation of frontier Artificial Intelligence models for healthcare
Destination 3: HORIZON-HLTH-2027-01-DISEASE-06: Development of monoclonal antibodies to prevent and treat infections from Flaviviruses
Destination 3: HORIZON-HLTH-2027-01-DISEASE-08: Development of innovative antimicrobials against pathogens resistant to antimicrobials
Destination 3: HORIZON-HLTH-2027-02-DISEASE-14-two-stage: Clinical trials for advancing innovative interventions for neurodegenerative
Destination 1: HORIZON-HLTH-2027-01-STAYHLTH-01: Addressing disabilities through the life course to support independent living and inclusion
Destination 5: HORIZON-HLTH-2027-03-TOOL-04: Virtual Human Twins (VHTs) for integrated clinical decision support in prevention and diagnosis
Destination 3: HORIZON-HLTH-2027-01-DISEASE-05: Development of novel small molecule antiviral therapeutics for pathogens with epidemic potential
Destination 4: HORIZON-HLTH-2027-01-CARE-02: Personalised approaches to reduce risks from Adverse Drug Reactions due to administration of multiple medications
Destination 3: HORIZON-HLTH-2027-01-DISEASE-07: Development of monoclonal antibodies to prevent and treat infections from Filo-, Nairo-, Phenui-, Picorna- and Toga viruses
Destination 5: HORIZON-HLTH-2027-02-TOOL-01-two-stage: Development of predictive biomarkers of disease progression and treatment response by using AI methodologies for chronic non-communicable diseases
Author
Group Leader at Fondazione The Microsoft Research -University of Trento Centre for Computational and Systems Biology