Clinical OMICS

MAR-APR 2019

Healthcare magazine for research scientists, labs, pathologists, hospitals, cancer centers, physicians and biopharma companies providing news articles, expert interviews and videos about molecular diagnostics in precision medicine

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Page 18 of 51 March/April 2019 Clinical OMICs 17 built could recapitulate the results of the last dozen clinical research studies of non-small cell lung cancer. Because the Foundation Medicine/Flatiron cohort consists of a broader, more representative population than the clinical research cohort, being able to recapitulate those results would be validating. "And if not, then that's interesting as well," Sin- gal said. In fact, the study using 2000 patients from the Foundation Medicine non-small cell lung can- cer dataset recapitulated every one of the known findings. "This was a land- mark moment for us," Sin- gal said. "It established that indeed a real-world data set created from rigorous genomics and rigorous data extraction can be of the same scientific merit as the approaches we are used to." Since the end of the study, the NSCLC dataset has now grown to 6000 patients. "Now we can ask the next level of questions," Sin- gal noted. Jintel Health recently announced a collaboration with Intermountain Healthcare's Precision Medicine Program. Jintel used a large cancer dataset (real-world data) and a literature-based knowledge base to train a variety of ML models for prognosis prediction and treatment ranking. Intermountain will apply these models to its clinical and genomic data with the aim of better understanding which targeted therapies work for specific groups of patients. The collaboration springs from earlier work in which Intermountain showed that genomics-based precision oncology improved survival and quality of life for 44 late- stage metastatic cancer patients at a lower cost than tra- ditional practices. In order to expand and speed up that work, Intermountain and Jintel collaborated on a pilot project to aggregate a cohort of colon cancer patients' clinical and genomic patient data from different sources within the Intermountain Healthcare system. They used a subset of that data to further train Jintel's models. When applied to a test set of patients (to validate the model), the trained model identified the most effective treatment for each patient. In the future, said Ping Zhang, CEO of Jintel, "We want to look at a large population and provide the tools for physicians to not only query but also do some simulation studies with real world data sets …. to enable novel discoveries and help physi- cians make more informed decisions in real time." A graphic display from AACR's Project Genie showing clinical actionability combined with OncoKB Precision Oncology Knowledge Base Chris Cournoyer, former CEO, N-of-One

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