Welcome to the Competence Center Personalized Medicine in Zurich
DNA Sequencing has changed biomedical research. Now focus is on Medicine: Routine genetic analysis shall make patient-tailored therapies standard. With the new Competence Center Personalized Medicine the University Zurich and ETH Zurich aim for taking a leadership role in the field of Personalized Medicine.
Z-Met: The Zurich Metastasis Project
Metastases are the most common cause of cancer-related death. The Z-Met project is a collaborative effort among clinicians, basic biomedical researchers, and computational scientists to understand how the genomic heterogeneity of tumors drives cancer progression, metastasis formation, and therapeutic resistance. The project encompasses several cancer types, including melanoma, renal cell carcinoma, prostate, breast, and pancreatic cancer, and it involves the development and application of cutting edge technologies, such as single-cell genomics, genome engineering, and computational methods for large-scale clinical and genomic data integration. Patients will benefit from Z-Met not only through novel insights that lead to improved treatment in the future, but also through direct use of the genomic data for treatment decisions in the molecular tumor board. Z-Met aims at generating a unique data set that will be shared among researchers to decipher the genomic basis of metastasis formation and treatment response.
PH Info Lunch 20th September 2016
On 20 September 2016, a Personalized Health Info Lunch about the ZH-BS Alliance will be organized at 11:30am in the ETH main building in room HG E3.
Clinicians and researchers from UZH, ETH and the University Hospitals are invited to learn more about the planned alliance.
Congratulations to Prof. Ruedi Aebersold
The Lotte and Adolf Holtz-Sprenger Foundation supports the flagship project "Prostate Cancer Digital Biobanking" with a generous funding. This is an important start aid for the establishment of a digital biobank which will conserve clinical samples in a quality and quantity that had never been achieved before.
ETH Latsis Symposium 2016