My research aims to understand how human immune cells respond to complex microenvironments. I analyse genomics data and apply a wide range of data science techniques such as Bayesian statistics, clustering, and machine learning. A key application of my research is to help design effective drug combinations to treat inflammatory diseases.
IAS fellowship (March–June 2018, January–March 2019)
Antimicrobial resistance (AMR) is the ability of microorganism to stop the action of antimicrobial drugs such as antibiotics. As a result, standard treatments become ineffective and infections persist causing a serious threat to the life of infected patients. With an increasing use of antibiotics and antivirals, the risk of AMR is becoming a major health concern, especially in countries with weaker health systems.
During my fellowship, I will join an interdisciplinary team to investigate the biological and socio-economic mechanisms that drive AMR at different levels (global, national, regional).
Current involvement with IAS
Antonio Cappuccio is currently as an external researcher still affiliated to the IAS as part of the team working on Complexity thinking for antimicrobial resistance.