Abstract
Individualized treatment selection based on scientific results is set to be the future of healthcare. It will not only have a significant favorable impact on the health of patients suffering from various diseases, but also on how drug discovery is performed. Previously unobserved information will be generated, facilitating much deeper disease insight on an individual level than was feasible before. Without a doubt, this will also lead to major consequences for informatics as it is necessary to deal with numerous novel and constantly changing information types and requirements. One central concern will be addressing the scale of data flooding in, but much more important will be bringing together the complexity of available data enabling scientists to successfully generate meaningful hypotheses and results. This will then help in aiming for an understanding of disease phenomena as a whole, and not only fragments within drug discovery. Informatics needs to be the key enabler for the entire process. This contribution aims to show a possible route for approaching this in a future-proof way, leveraging and adapting knowledge-sharing approaches.
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