How can we enable drug discovery informatics for personalized healthcare?

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.

Longitudinal pharmacometabonomics for predicting patient responses to therapy: drug metabolism, toxicity and efficacy

“…Although it is unlikely that a drug that is suitable only for a few individuals (truly personalised medicine) will be developed, it is now clear that stratified medicine, that is, tailoring a therapy to selected groups of patients based on some prognostic measure of how they will respond, is a major goal today. This requires systems to predict i) how a given patient will metabolise any administered drugs, ii) whether there will be any adverse side effects and iii) whether the drugs will be efficacious [1]. This approach extends beyond drug therapy and is also relevant to surgical and other interventions such as radiotherapy in cancer treatment, to nutritional and nutraceutical studies, or sports training regimes, for example.…”