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Sub-studies can be added for newly discovered biomarkers and treatment approaches, so the field can learn which patients will most benefit from these new developments, and get new, effective treatments to patients sooner. Precision Promise is an opportunity to change the landscape of how we conduct pancreatic clinical trials, said Victoria Manax Rutson, MD , chief medical officer at the Pancreatic Cancer Action Network. We will be able to offer options to patients based on the molecular profile of their tumor, rather than trying to fit them into a clinical trial that may not suit the needs of their disease.” Starting in the spring of 2017, participating patients will enroll in Precision Promise at a local Clinical Trial Consortium site. Each patient will undergo advanced molecular profiling to determine their tumors unique molecular features, which will inform which Precision Promise sub-study will best match their individual needs. Once on treatment, patients will be monitored closely and follow-up analyses will be conducted to provide important clues to help researchers quickly understand the effectiveness of each treatment in real time. Currently, important genetic data and clinical trial results are fragmented across various institutions and drug developers, and some important results may never be shared publicly for researchers to learn from these findings. Through Precision Promise, all data from the initial 12 Clinical Trial Consortium sites will be analyzed together so scientific findings are gathered and disseminated to the research community in a timely manner, said Lynn Matrisian, PhD, MBA , chief research officer at the Pancreatic Cancer Action Network. http://ur.my/consultantinterviewcourse65164This model ensures that data and information are shared as quickly as possible for patient benefit. Precision Promise will partner with health-tech company, Tempus, to utilize their cutting edge genomic sequencing and analysis methods. Tempus collects and analyzes large amounts of genomic data using statistical analysis, machine learning, and proprietary algorithms to help physicians make real-time, data-driven decisions for their patients.
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