gms | German Medical Science

29. Jahrestagung der Retinologischen Gesellschaft

Retinologische Gesellschaft

17. - 18.06.2016, Berlin

System Medicine – Translation from Tumorbiology to Ophthalmology

Meeting Abstract

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  • Hans Lehrach - Max-Planck-Institut für Molekulare Genetik, Berlin

Retinologische Gesellschaft. 29. Jahrestagung der Retinologischen Gesellschaft. Berlin, 17.-18.06.2016. Düsseldorf: German Medical Science GMS Publishing House; 2016. Doc16rg45

doi: 10.3205/16rg45, urn:nbn:de:0183-16rg453

Veröffentlicht: 16. Juni 2016

© 2016 Lehrach.
Dieser Artikel ist ein Open-Access-Artikel und steht unter den Lizenzbedingungen der Creative Commons Attribution 4.0 License (Namensnennung). Lizenz-Angaben siehe



We are in the middle of a revolution in Biology and Medicine, triggered primarily by the enormous increase in sequencing power (and concomitant decrease in sequencing cost) due to next generation sequencing techniques. While it took us in an international consortium more than ten years and between 1 and 3 billion US-Dollars to sequence the first human genome, we are now embarking on projects to sequence the genome of every cancer patients, as well as the genome and transcriptome of their tumors.

To be able to use this flood of data we can generate on every patient to provide every patient with individually optimised medical care, we can use these data to model the patient (and, in oncology, his/her tumor) as interacting molecular models, which can be virtually ‘treated’ with ‘virtual drugs’ to be able to predict the effect and the side effects of ever possible therapy on the individual, and to develop individually optimised therapies for every individual patient. For this, we basically need three components: sufficient computing power, detailed information on the molecular mechanisms involved in the disease and the drug therapies and a detailed molecular characterisation of the disease process in the individual patient. While, especially in oncology, the first two requirements have been fulfilled for quite some time, it has only very recently become feasible to characterise every individual patient sufficiently, mostly due to the enormous progress in next generation sequencing techniques. Oncology is an obvious first example for this new strategy, due to the wealth of information on the basic biological mechanisms underlying this disease, the relatively straightforward access to the diseases tissue, and the dramatic changes, which can often be observed in tumors. We do however expect this strategy to extend far beyond oncology to many other medical areas, helping both to define disease mechanisms, but also to translate these into concrete predictions on effects and side effects of different therapy options.

The development of such computer models of individual patients does however also offer new, revolutionary possibilities for virtualising drug development, increasing the number of drugs reaching the market, accelerating development, cutting costs, and cutting risk in the drug development, in turn, increasing the treatment options for patients.