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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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Logical modeling of COVID-19 intracellular infection: supporting therapies development

Develop a logical mathematical model of the intracellular pathways involved in the COVID-19 infection. The model can be used to study several drugs and...

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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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Developing a unified QSP platform for lysosomal storage disorders (LSDs)

Develop a unified modeling platform for LSDs to enhance the comprehension of Lysosomal storage disorders by highlighting differences and common properties...

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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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Investigating the inflammatory signaling characterizing lysosomal storage disorders (LSDs)

Develop a text-mining and systems biology framework to investigate the inflammatory signaling characterizing lysosomal storage disorders (LSDs). First...

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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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