Drug Selection

The oncologist of the future should have the possibility of identifying the most suitable drugs for an individual patient before the onset of the therapy, i.e. knowing which drugs will have the highest likelihood of response and absence of severe adverse reactions. This could be possible by investigating biomarkers for response and for severe adverse drug reactions.

Such Biomarker can be identified by analyzing DNA, RNA, proteins and metabolites of both the cancer tissue (tumor or hematologic malignancy) and the patient's organism. To this purpose there exist a number of technologies: Low- and middle-throughput technologies, such as qPCR, IHC, FISH, etc., as well as High-throughput DNA technologies such as Microarray Hybridization and Deep Sequencing / Next Generation Sequencing.

  • Niedrig- und Mitteldurchsatz-Technologien

    Low- and middle-throughput technologies

    Low- and middle-throughput technologies like qPCR, IHC, FISH, etc. With these technologies biomarkers are investigated in specialized centers or conventional laboratories with the aid of approved tests (In-vitro diagnostics). These technologies are already employed in the routine clinical diagnostics.

  • Hochdurchsatz-Technologien

    High-throughput DNA technologies

    High-throughput DNA technologies like microarray hybridization and deep sequencing/next generation sequencing. These technologies generate data, which are processed by bioinformatics resulting in DNA sequences useful as biomarkers, for instance as biomarkers for therapy response. In addition, by applying system biology approaches, these data could allow for the evaluation of the biochemical processes that determine response and adverse drug reactions in a particular patient. Furthermore, such data also have the potential to generate a molecular networking model for a representative tumor cell of the patient, which could highlight the targets for targeted drugs with minimal adverse reactions.