Computational approaches for drug safety

As new data sources have emerged, the data space which drug safety operations can use has significantly expanded. The use of “intelligent” technical paradigms (e.g. Machine Learning - ML, Knowledge Engineering – KE etc.) outline promises yet to be fully realized. Computational methods for drug safety (CMDS) services provided by CERTH focus on improving the data upon which drug-safety related decisions are made, and provide guidance on relevant technical tools deployment, in order to optimize the use of resources and most importantly improve outcomes. The objective is to design and deploy services which could significantly improve the already established products, or facilitate the development of disrupting ideas for tools aiming to support clinical healthcare, e-prescription, pharmacovigilance, clinical trials etc. CERTH can provide the necessary know-how to bridge the gaps along the full spectrum, from needs definition to real-world testing and deployment.