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Using Big Data to Personalize the Healthcare Experience in Cancer, Genomics and Mobile

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StrataRx Webinar presented by @DrBonnie360

Publicada em: Saúde e medicina, Negócios
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Using Big Data to Personalize the Healthcare Experience in Cancer, Genomics and Mobile

  1. 1. Big Data Personalizing The Healthcare Experience
  2. 2. Using Big Data to Personalize the Healthcare Experience
  3. 3. Personal Medicine: Making Medicine Work for You • The idea has been around for over a decade • Three ways Big Data is being used to Personalize the Healthcare experience 1. Genomics 2. Cancer/ Clinical Trials 3. Mobile Health (mHealth)
  4. 4. 1. Genomics What is it? • Genomics is the study of the human genome • Sequence the Human Genome • Analyze the Human Genome • Application of the analysis in a medical setting
  5. 5. 1955 1965 1995 20051975 1985 2015 1956 Watson and Crick created the first model of a DNA molecule and discovered that genes determine heredity 1963 F. Sanger of Britain developed the first procedure to sequence DNA The Genetic Code is cracked: scientists begin to predict characteristics by studying DNA 1987 The DOE begins talk of a 15 years plan to sequence the human genome 1990: Researchers begin research on the Human Genome Project 1999 The Human Genome Project completely sequenced the first human chromosome 2000 J. Craig Venter and Francis Collins, jointly announce the sequencing of the entire human genome 2003 The successful completion of the human genome project Human Genomics Timeline 2007: GWAS to link genomics to diseases
  6. 6. The Human Genome Project The Human Genome Project was a project sponsored by the US Department of Energy and the NIH that developed the technology to identify, analyze, and sequence all 20,000-25,000 genes in human DNA. The project took 13 years, but it revolutionized the way DNA was sequenced.
  7. 7. The Cost of Sequencing the Human Genome $95,263,072 $61,448,422 $40,157,554 $18,519,312 $13,801,124 $10,474,556 $7,147,571 $343,502 $70,333 $29,092 $10,497 $7,950 $5,000 $0 $10,000,000 $20,000,000 $30,000,000 $40,000,000 $50,000,000 $60,000,000 $70,000,000 $80,000,000 $90,000,000 $100,000,000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
  8. 8. The $1000 Genome
  9. 9. Why Big Data in Genomics Now? Big Data in Genomics More rapid IT development Better analytic tools Need to personalize healthcare New data streams
  10. 10. Companies using Big Data to Analyze the Genome • Bina Technologies • Portable Genomics • NextBio
  11. 11. Summary Table of the Companies Bina Technologies Portable Genomics NextBio What · Genomic data analysis and sharing platform · System has components focused on secondary analysis and tertiary analysis that will allow companies like NextBio and others to build on top. · Mobile genomics visualization platform · Apps will aggregate genomic and epigenomic data · Similar to iTunes for genomic data · One Stop Shop: Platform that sits on top of existing system aggregating hospital data · Aggregate and analyze data on both a population and individual level Where · ALL Diseases (agnostic platform) · Chronic Diseases · Oncology, Metabolic Disease and Autoimmune Diseases How · Modifies Hadoop to make it more accurate · Builds the infrastructure for analysis of genomic data (doesn’t do the actual sequencing or analysis) · Mobile Apps: they incorporate geolocalization of healthcare specialists · Nutrigenomics: effect food has on genetic or visa versa · NextBio allows it’s customers to integrate NextBio within their application and access it from outside For Whom · Have good reviews by academic institutions · Patients · Providers · Translational research and medicine · Academic medical centers · Cancer centers Growth Trend Customers seem to be healthcare professionals and patients Trend: Started with Pharma then academic and then bigger and more pharma
  12. 12. 2. Cancer and Clinical Trials
  13. 13. Average percent of patient population for whom Cancer drugs are ineffective
  14. 14. Average percent of patient population for whom a particular drug in a class is ineffective Asthma Drugs Arthritis Drugs Cancer Drugs Antidepressants Diabetes Drugs Alzheimer’s Drugs
  15. 15. Companies Using Big Data to Personalize Cancer Treatments • Ayasdi • GNS Healthcare • Explorys
  16. 16. Explorys Ayasdi GNS Healthcare What · A cloud based platform for storage and analysis from multiple sources · Partner with different healthcare systems, aggregate data into the platform, standardize and normalize data · Topological data analysis (the math of shapes) to uncover new patterns data sets · Data analysis to identify population health and clinical trial design · Deliver causal simulations models “in a jar” that allow for a bottom up prediction · Predict costs and drivers and show optimal interventions through simulations of multiple “what if” conditions Diseases · Not specific: Research on MRSA, clinical trials, cost of care, readmissions · Their work in Cancer is most evolved: The Ayasdi Cancer Genome Atlas · Other projects include PTSD, BTI, drug toxicity, and clinical trials · Oncology How · Health data gateways (HDG): a server that sits within the healthcare system firewall collecting clinical, financial and operational data · Use topological models to find correlation in the data · Using Causal Models – “If-Then” Simulations For Whom: · Hospitals · University Hospitals/ Teaching Hospitals · Biotech companies · Pharma · Government Health departments · International Research Centers · Pharma · Providers: Research Hospitals Growth Trend · Mostly in Healthcare facilities · Mostly Research groups except their partnership with Medicaid in 2013 Summary Table of the Companies
  17. 17. 3. Mobile Health
  18. 18. • Mobile is ubiquitous with 46% of Americans owning smartphones • Crowdsourcing and Social Media Use • Gaming: the gaming community has moved their efforts to mobile Why Mobile Health Now?
  19. 19. Click Here Interview With Eric Topol
  20. 20. Companies using Big Data to Develop Apps for mHealth • Brain Resource • AchieveMint • Aetna CarePass, Ginger.io , OneHealth
  21. 21. Bottleneck There are three main bottlenecks that are slowing down the progress of genomics, cancer and clinical trial research, and mobile health in their pursuit to personalize the healthcare experience. 1) interoperability 2) data sharing 3) privacy concerns Genomics Cancer and Clinical Trials mHealth
  22. 22. Data Sharing
  23. 23. • “Citizen science can take a small area where there are hundreds of patients and there is very little known, and do the equivalent of a night science raid on nature. They can grab something and come back with results.” – Stephen Friend White House Champion of Change and President, Co- Founder & Director of Sage Bionetworks
  25. 25. Thank you • @DrBonnie360 • www.drbonnie360.com • drbonnie360@gmail.com