Medical doctors can chose from a variety of available medical drugs for specific types of cancer. However, the American Society of Cancer published in 2012 that three out of four applied chemotherapies do not work as expected. The challenge for medical experts in course of personalized medicine is to select the combination of medical drugs, which works best for an individual patient.
To predict the drug’s effect for a concrete tumor and patient, it is possible to extract the tumor and test various therapies in parallel in laboratories and document the outcome. Today, this is a time-consuming process requiring excessive wet-lab work and time-consuming manual data analysis.
With the help of our in-memory technology, we were able to improve the analysis process from weeks of manual data analysis to minutes of interactive data exploration. With a growing library of experiment results for a drugs applied to a certain type of cancer, we are now able to predict the drug response for new tumors minimizing the drugs to test. Furthermore, we enable researchers to discover correlations between genetic variants and drug response interactively. Thus, researchers are able to verify hypothesis in a couple of minutes for the first time and deriving new indicators to select a concrete drug and therapy combination per patient.
You can find a detailed overview of the process and our findings in the poster attached to this webpage and selected application screenshots in the gallery below.
You might also be interested in
The following links provide additional content-related information.
- Analyze Genomes: In-memory Apps supporting Precision Medicine (Slides)
- 2016 Healthcare Information and Management Systems Society Conference (Slides)
- 2015 Future Convention (Slides)
- Join us at 2015 Future Convention in Frankfurt
- Symposium on Big Data in Medicine (German Video Footage)
- 2015 Personalized Medicine Award
- Join us for 2015 Personalized Medicine Convention in Cologne
- Join us at 2014 SAP d-code in Las Vegas and Berlin
- 2014 World Health Summit
- Best Paper Award for “An Optimized Research Process for Real-time Drug Response Analysis”