The Dahlem Centre for Genome Research and Medical Systems Biology
A novel approach to diagnosing and treating human diseases
Human beings are individuals and so are their diseases.
At the DCGMS we are seeking to understand how differences in an individual's genetic make-up affects disease susceptibility and progression, and response to therapy. Currently, our major focus is the use of virtual tumour models to improve the success of cancer patient treatment.
We use the detailed molecular imprint of an individual tumour as the basis for mathematical modelling that can predict individual outcomes following virtual treatment.
DCGMS uses this virtual 'patient' technology to direct more tailored therapies, with the potential to improve disease prognosis, diminish side effects, improve patient quality of life and, ultimately, help to save lives.
Matching the 'right' patient to the 'right' drug
The future of medicine is personal
DCGMS founder, Prof. Hans Lehrach, talks about novel approaches to cancer care based on genomics:
The 'Fight against cancer' using Virtual Patient technology in Tomorrow Today (In English).
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Patient stratification based on a more complete description of the tumour will facilitate the selection of accurately tailored therapies, i.e. matching the ‘right’ patient to the ‘right’ drug. Ultimately, this will improve the likelihood of a positive prognosis, reduce healthcare costs and, most importantly, help to save lives.
In tandem, application of the virtual 'patient' model also has the prospect of accelerating the drug approval process, further helping patients to find the right therapy. At present more than 90% of drugs tested fail during development, therefore pharmaceutical companies are focusing efforts on repurposing previously tested drugs, reducing the significant costs associated with approving new drugs. The virtual 'patient' model could represent a robust and reliable drug testing framework, expediting the drug approval pipeline in an affordable and timely manner.
Translating data into therapeutic strategy