New Statistical Algorithms for the Analysis of Mass - FU Berlin, FB MI ...

172 CHAPTER 8. CONCLUSION AND FUTURE DIRECTIONS
these judgements, should be replaced by multi-source (or multi-dimensional)
biomarkers that combine informations from different sources in a reasonable
way.
What we call a bioprint is the multi-dimensional extension of the biomarker
concept. Using many different data sources (-omics) and different analyzing
techniques, bioprints can be created that not only rely on a single change but
mathematically and biologically meaningful combine many different relevant
elements. These potentially complex models require not only sophisticated
data-mining algorithms for the analysis but also large amounts of computing
power.
The ultimate goal should be to find disease specific bioprints using data
from all available kinds of sources and examine the relationships between clinical
symptoms and genetic, biochemical, immunological and cellular biomarkers.
This and perhaps only this would facilitate an area of personalized
medicine: “Although they are certainly related, the only way to really achieve
personalized medicine is to be able to create an information base that lets you
say what is it about an individual that I need to know in order to define what
the right treatment is.” (Carol Kovac, General Manager Healthcare and Life
Sciences at IBM interviewed by (McDonald, 2006).)
The Next Steps
We feel that the there are four main steps that have to be taken in order to
come closer to the aim of providing such an information base:
1. Evaluate available data: Collect, classify and analyze publicly available
biobank data and data available in “unofficial biobanks” such as
hospitals or institutes.
2. Consolidate compatible data on a disease level: Based on the
analysis in the previous step, data clusters are created that are related to
the focused cancer types. Subsequently, sub-clusters are extracted that
contain compatible data, that is, data that can reasonably be compared
with respect to biology.
3. Data Mining: Develop algorithms to analyze and mine this data.
4. Web-based community access: Build and provide an “out-of-thebox”
web-based platform for researchers across disciplines and medical
staff to access this data and perform individual analyses.
The ultimate goal: Value for Healthcare
By developing new ways to identify major diseases at the molecular level and
provide appropriate (personalized) diagnosis and therapeutics. This means
shorter duration of therapy, increased healing chances and therefore increases
life quality.