Best in the world to detect cancer mutations

The Center for Genomic Medicine has been awarded the gold medal in genetic variant detection from genomic data in cancer diagnostics. The challenge was organised by the American Food and Drug Administration (FDA) and counted participants from throughout the world.

Frederik Otzen Bagger, head of bioinformatics, explained:

- We competed in a challenge to see who was best at identifying the variants in a cancer tumour. We carry out this procedure every day at the centre to help identify the specific type of cancer in cancer patients, so that physicians can tailor their treatment accordingly.

Participants in the challenge came from universities and private companies throughout the world.

- The FDA sent the same files with DNA sequencing from a cancer patient to all of the participants in the challenge. It was then up to us participants to discover the variants in the DNA file that could be significant for a specific cancer disease, Frederik Otzen Bagger explained.

He stressed that the gold medal is the result of collaborative efforts by the many specialist functions at the centre.

 - We work closely together every day with physicians and molecular biologists, and these joint efforts are the secret behind our success at the Center for Genomic Medicine. We make sure that our code and algorithms are accurate, so that we detect what is technically relevant. However, our work with the analytical and therapeutic teams is where we detect what is actually relevant for the specific patient, said Frederik Otzen Bagger. ​

About the Center for Genomic Medicine​

The Center for Genomic Medicine works in the field of genomic analysis and bioinformatics for patient diagnosis and treatment.  Work in this area is based on research into genome sequencing and the structure of genomes and it developed on the heels of the Human Genome Project.

The Center for Genomic Medicine gives the clinical departments at Rigshospitalet and other hospitals access to new technologies that enable whole-genome analyses in work to develop personalised medicine.

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