Clinical OMICS

MAY-JUN 2018

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 46 of 51 May/June 2018 Clinical OMICs 45 using AI to say a person with a certain condition has a 97% chance of having an ADE versus a 42% chance in the absence of the co-existing condition." Other data leveraged in this pro- cess—in real time—include those from the electronic medical records, insurance claims, pharmacy data, genomic data, and information from the National Committee for Quality Assurance (NCQA). Rare Disease Diagnosis Whole-genome sequencing has made significant inroads to help doctors sniff out and treat Mendelian diseases quickly in neo-natal care. While the high-mortality rate cases will get the press, AI is also making inroads in the diagnosis of rare diseases that may not be a matter of life and death, and can significantly shorten the diagnostic odyssey that awaits so many patients and families. Facial analysis company FDNA is leveraging AI for facial patterns, essentially automating the task that geneticists have used for years of look- ing for specific facial traits as clues to the basis of rare genetic diseases. What FDNA does via its facial recognition engine is to effectively broaden the base of available facial images used to reach a diagnosis. "Geneticists would look at tell-tale signs in patients' faces and would take pictures of them, to help them reach a differential, or suspected diagnosis," said Dekel Gelbman, CEO of FDNA. "We are able to use de-identified pho- tos of patients, classify them into syn- dromes based on the common patterns in the face—much the way a geneticist would. But we are bringing a much broader set of data and different pat- terns that they might not have seen in their professional experience." The technology, when combined with the genomic data from patients, can also help tie variants of unknown significance (VUSes) to specific rare diseases, essentially linking the phe- notype with the genotype. "As we look into the future AI will change the role of the geneticist and instead of being a diagnostician, they will become a treating physician, more involved in therapeutics and clinical development, and I think that is what geneticists want too," Gelbman added. New Diagnostics At AI-powered genomic diagnostic company Freenome, company CEO Gabriel Otte sees the potential of AI to upend how diseases are diag- nosed. He points out that most clini- cal diagnostics that have been on the market for years experience signifi- cant declines in accuracy, a function of the stripped-down approach often taken by companies developing these low-margin tests. Freenome, which is developing blood-based diagnostics and is cur- rently working to attain premarket approval for its colorectal cancer test, has taken an approach to identify as many biomarkers as possible in the blood and then apply these signatures using AI to the diagnosis of disease. "We have affected artificial intelli- gence on the software side to hone in on the signals that are relevant for a specific test," Otte said. "We do this in the software as opposed to in the labo- ratory. What this enables is, as we pick up on novel signatures that others haven't, it allows us to change the test. It is about picking up all the signals in first place to make this a software problem and not a lab problem." Hurdles for AI While AI is beginning to make an impact in clinical diagnosis and care, there still exist roadblocks to adoption. The biggest of these involve availabil- ity and accuracy of the data used to help train these systems. "There is inherently a small data problem in AI applied to genom- (continued on next page) MF3d / Getty Images

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