Genomic sequencing has been a driving force for enabling Personalized and Precision Medicine in certain care contexts, such as cancer treatment, rare disease diagnostics, and effective drug prescriptions. These early successes lay the foundation for accelerated progress in healthcare, and translational research is a key component in getting potential cures from the lab to the bedside. In this session, Dr. Paul Avillach discusses implementing HIPAA and FISMA compliant methods and techniques for the integration of multiple heterogeneous clinic cohorts, electronic health records data, and multiple types of genomics data to encompass biological observations. He is PI and Co-Investigator on several large projects at Harvard Medical School's Department of Biomedical Informatics, including the BD2K PIC-SURE Center of Excellence, the Global Rare Diseases Registry project, the PCORI ARCH project, and the PCORI Phelan-Mcdermid Syndrome project. Technologies discussed will be Amazon EC2, Amazon RDS, Amazon EMR, and others. Paul's talk will be augmented with a short talk on using DevOps to ensure security compliance.

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Paul Avillach, MD, PhD
Assistant Professor, Department of Biomedical Informatics, Harvard University
194317
Towards Precision Medicine:
Building Patient Centric Information
Commons on Common
and Rare Diseases Using AWS

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Humorism
phlegmatic choleric
sanguine melancholicTreatment:
Bloodletting
Diagnosis of Leukemia During 18th Century?

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For each subtype:
- Diagnosis
- Prognosis
- Potential treatment
Diagnosis of Leukemia
Chronic
myelogenous
leukemia
Acute
lymphoblastic
leukemia
Chronic
lymphocytic
leukemia
Acute
myelogenous
leukemia
sanguine

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?? ? ?
Autism

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Toward Precision Medicine: Building a Knowledge Network for
Biomedical Research and a New Taxonomy of Disease
Report from National Academy of Science, USA, 2011

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https://nhanes.hms.harvard.edu

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Gold standard resource for phenotypes and exposure
information: National Health and Nutrition Examination Survey
since the 1960s
now biannual: 1999 onwards
5000 participants per year
1 http://www.cdc.gov/nchs/nhanes.htm
1999-2000:
N=41,474
1,181 total measurements!
>250 exposures (serum + urine)
>85 quantitative clinical traits
(e.g., serum glucose, lipids,
body mass index)
nutritional and health status interviews

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Gold standard for breadth of exposure & behavior data:
National Health and Nutrition Examination Survey
Nutrients and Vitamins
vitamin D, carotenes
Infectious Agents
hepatitis, HIV, Staph. aureus
Plastics and consumables
phthalates, bisphenol A Physical Activity
e.g., stepsPesticides and pollutants
atrazine; cadmium; hydrocarbons
Drugs
statins; aspirin

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Live demo
https://nhanes.hms.Harvard.edu

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https://grdr.hms.harvard.edu

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Rare Disease Registry Patient count Variables
Clinical Registry Investigating Bardet-Biedl Syndrome 180 708
International Pachyonychia Congenita Research Registry 569 496
International Plastic Bronchitis registry 66 63
Intracranial Hypertension Registry 963 77
North American Malignant Hyperthermia Registry 2,107 162
Wolfram Syndrome International Registry 124 580
Coordination of Rare Diseases at Sanford Registry 1,218 46
including: including:
Additional
data:
National Ataxia Foundation 487 16
International WAGR syndrome association 50 380
Cornelia De Lange Syndrome Registry 61 486
Total 5,227 3,014
Rare Cancer Registry (soon) 800 1,800
https://grdr.hms.harvard.edu

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UDN Patient Centric Information Commons
• Demographics
• Online registration Form
• PhenoTips
• HPO clinical terms
• Ethnicity
• Diagnosis OMIM
• Knowledge extracted from
referral letters (via NLP)
• Type of sequencing
• Candidate genes
• Candidate variants
• Full Annotated VCF
• 524 Whole genomes
• 616 Whole exomes
• 343 probands
• 259 trios
• + ….
i2b2/tranSMART/gNOME
ALL UDN Data Available

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RESTful API
Source code: https://github.com/hms-dbmi
Play with API: https://bd2k-picsure.hms.harvard.edu
Patient Centric Information Commons (PIC)

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Harvard IRB security levels:
• Level 5 - Extremely sensitive information
• Level 4 – Very sensitive information
• Level 3 – Sensitive or confidential information
• Level 2 - Benign information to be held
confidentially
• Level 1 - Non-confidential research information

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AWS Enables HIPAA Compliance
AWS enables customers to build HIPAA-compliant applications that store,
process, or transmit Protected Health Information (PHI)
 Business Associate Agreement (BAA) addendum available
 HIPAA-eligible services from AWS for a broad range of applications
Compute Storage Database Managed Big
Data
Archiving Data
Warehousing
Networking

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HIPPA Compliance on AWS

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Secured Access Control
1. Authentication
Who are you?
2. Authorization
What are you allowed to do?
Level 0 : Authenticated BUT no access to data
Level 1 : Aggregated data
Level 2 : patient level data

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RedOctober

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1. Authentication

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Monitoring EVERYTHING
Deployment of a new project (EC2, RDS, S3,
CloudFormation)
System activity on EC2 and RDS
Application business activity on EC2
• Tomcat
• Jboss / Wildfly
• Httpd
• Solr

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Monitoring EVERYTHING
Authentication via Auth0 API
User activity
• What do users do on the service?
API activity
• What is being accessed and by whom?
AWS console and API activity
• Who is accessing AWS console or API and doing what?

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Monitoring EVERYTHING
• Dashboards sent by email every morning
• Alerts trigger events in Slack

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1 2
Modular Open Source Research Service

33. Previous published
example using
Jupyter notebook
Everyone has
FULL access
to all the code
to reproduce
analysis

34. https://tinyurl.com/DCPPC-APIs-overview

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• Play with i2b2/tranSMART UI:
• https://grdr.hms.harvard.edu
• https://nhanes.hms.harvard.edu
• https://demo-ngs.hms.harvard.edu
• Play with BD2K PIC-SURE RESTful API
• http://bd2k-picsure.hms.harvard.edu
• http://exac.hms.harvard.edu

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Thank you!