30 Cancer Research Groups to Use Algorithms to Find Vaccines for Cancer

The Parker Institute for Cancer Immunotherapy, the company founded by Napster co-founder and first President of Facebook Sean Parker, announced that it has partnered with 30 of the world’s leading cancer research groups to find vaccines for cancer using algorithms.

The Parker Institute for Cancer Immunotherapy and the leading cancer research groups’ collaboration is called the Tumor neoantigEn SeLection Alliance (TESLA). The participating research groups include the Cancer Research Institute and Center for Human Immunology & Immunotherapy Programs at Washington University School of Medicine in St. Louis.

“Bringing together the world’s best neoantigen research organizations to accelerate the discovery of personalized cancer immunotherapies is exactly the type of bold research collaboration that I envisioned when launching the Parker Institute,” Sean Parker said. The Silicon Valley entrepreneur added, “This alliance will not only leverage the immense talents of each of the researchers but will also harness the power of bioinformatics, which I believe will be critical to driving breakthroughs.”

For this research endeavor, each participating research groups will receive genetic sequences from both cancerous and normal tissues. Each group, using each laboratory’s own algorithms, is expected to come up with a set of predicted neoantigens that are likely to be present in the tumor cells. Each group’s prediction will then be validated through a series of tests to determine which prediction is the most likely to be accurate and recognizable by T-cells. Each participating group will then be provided with data to further improve their algorithms and to ultimately come up with personalized vaccines for cancer.

Robert D. Schreiber, Ph.D., director of the Andrew M. and Jane M. Bursky Center for Human Immunology & Immunotherapy Programs at Washington University School of Medicine in St. Louis, said that this new collaboration is remarkable as it has the potential to precisely identify abnormal proteins in individual tumor that can be “used as targets for personalized cancer immunotherapy.”

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