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Systems Pharmacology

Building computational frameworks to support drug discovery and personalized medicine

We combine molecular, cellular, preclinical, and clinical data from different sources to build a systems view of biological processes in healthy and disease condition, setting the basis for mechanistic models and mathematical descriptions of both complex and rare disorders. By integrating preclinical with clinical data, our models enable to identify new targets and biomarkers, simulate disease progression, identify patient subgroups and predict drug efficacy, guiding the advance of small molecules and biological agents through the various phases of their development.

Our focus

Case Studies

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A QSP approach based on a graphical model to improve mRNA vaccine platforms

Analyzing and integrating multi-source knowledge and data, with the goal of clarifying the intricate biological processes involved in the mechanism of...

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Modeling Neurofilament trafficking in neurodegenerative disorders

Develop a Quantitative System Pharmacology (QSP) model to evaluate the potential of neurofilaments as early biomarkers of disease onset and treatment...

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Developing a QSP model for prostate cancer immunotherapy

Develop a Quantitative System Pharmacology (QSP) model to evaluate the effect of different immunotherapies in prostate cancer and provide a computational...

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Computational analysis of cytokine release following bispecific T-cell engager therapy

Develop a logical model describing the interplay between Bispecific T-cell engager antibodies (BiAbs) the immune system, and tumor cells. Perform in silico...

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Extracting knowledge from literature to inform Tuberculosis drug and vaccine development

Develop a TB Knowledgebase, that interactively aggregates, organizes, and analyzes publicly available literature and clinical trial documentation to support...

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A new computational method for drug repurposing

Develop a systems pharmacology workflow that integrates different data types such as genomics, transcriptomics, and literature to identify in silico drug...

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