PERSONALIZED MEDICINE WITH IBM-WATSON: FUTURE OF CANCER CARESOFIA DARD

CANCER CARE NOW:• Patient’s samples sequenced.• Bioinformatics pipeline• Molecular Tumor Board (MTB).

Reviews patient cases that are not responding to standard care. • This approach of personalized

medicine takes weeks.

EMERGING METHOD: WATSON FOR GENOMICS• After sequencing data is available,

oncologists will have Watson cull through existing knowledge for clinical trial and drug suggestions. • IBM Watson…answers you in minutes.• Finalizing algorithm and testing in clinical

trials.

HOW IT WORKS: • Cognitive computing that draws from unstructured data and relies on natural

language = COMPLEX• governed by grammar, context, and culture• not like speech recognition. • breaks sentence down into parts to understand it and infer users intent (Pai, 2014)• Other researchers (ImageCLEF dataset, 2012): optimized query language but vocab gap.

• Corpus of Knowledge:• Collection of knowledge for that domain. • Uploaded by users• Includes journal articles, patient health information, medical records.• Format of materials: voice recordings, images, PDFs, etc. • Curated by users

HOW IT WORKS:• Ingestion of corpus• Machine learning with experts:• Question/ answer pairs uploaded to establish ground truth.

• More about learning grammar semantics.

• Watson learns but is periodically reviewed by experts.• Receives a question• Creates hypotheses and finds evidence to support each one• Weighted Evidence Scores: establishes Watson’s confidence

in itself. • Better with time and knowledge.

EVALUATING WATSON

• Saves time, money, and decreases health professionals workload. • Could potentially substitute/ replace

MTB once proper algorithm is established. • Resource poor hospitals.• Challenges: algorithm & acquiring data

sets.

Explorys Data Set = 50 million patient records.

ENDLESS POSSIBILITIES WITH WATSON

• Save drug developers lots of money by enhancing patient recruitment.• Population data from IBM Watson

Health Cloud can reveal new patterns. • Ex: gene mutation patterns by

patient location > underlying environmental factor?

REFERENCES1. http://www.jop.ascopubs.org/content/9/3/155.short# 2. https://

scholar.google.com/scholar?start=10&q=ibm+watson+cancer&hl=en&as_sdt=0,34 3. Pai VM, et al. J Am Med Inform Assoc 2014;21:e2–e5. doi:10.1136/amiajnl-2013-0018964. http://jamia.oxfordjournals.org/content/early/2016/03/28/jamia.ocw022 5. http://jamia.oxfordjournals.org/content/19/5/8516. http://

www.businessinsider.com/sc/ibm-watson-and-personalized-healthcare-for-cancer-2016-17. http://

www.ibm.com/smarterplanet/us/en/wild-ducks-podcast/episode-7-personalized-medicine-podcast.html

8. http://www.iconplc.com/news-events/news/icon-and-ibm-to-revolutio/index.xml 9. http://ij-healthgeographics.biomedcentral.com/articles/10.1186/1476-072X-4-29 10.DOI: http://dx.doi.org/10.1136/amiajnl-2011-000293 851-858 First published online: 1

September 2012