1.
Navigating Genetic Data
Regulation, Privacy and Ease of Use
Presentation @ BIT World DNA Day and Genome Day, Dalian, China 2011
DNA Guide, Inc. All rights reserved 2011
Alice Rathjen, President, Founder
alice@dnaguide.com

2.
The Problem..
Inadequate Infrastructure
Genetic Data Explosion
Huge investment in
Sequencing Technologies
and Molecular Diagnostics
Personalized Medicine
R&D
Pharma /
Clinical
Trials
Consumers/
Patients
INSURANCE
Government & NGO Regulations
Health
Services
The amount of genetic data is about to explode. However, there’s currently inadequate infrastructure for leveraging the value
of genetic data in health care: current software is designed for researchers, there’s a shortage of genetically trained health care
professionals and people fear their genetic data could be used against them. These issues need to be addressed for
personalized medicine to succeed.

3.
Anxiety and Fear of Genetic Data
TA T
G C
T
A
C
G
A
Personal genetic information is highly sensitive data touching on the areas of identity, paternity, self worth, and privacy. The
problem that really needs to be solved is how to cultivate a sense of trust between physicians and patients and how to
structure health information transfer in such a way that patients can participate in the management of their data as their bodies
become increasingly digital.

4.
T
G
C
A
How Can Personalized Medicine Grow?
Physician as Guide
With Cost Effective,
Real Time Delivery
of Personalized
Information
Patients Increasing
Participation in
Management of their
Genome and Medical
Information
With proper tools we can provide physicians and patients a sense of mastery and control over genetic and health
datasets. This will help facilitate higher patient engagement and opt-in rates for participation in studies - which in turn
will speed up the process of discovery, approval and market adoption of personalized medicine.

5.
Traditional Patient/Research Model
• Patient Gets Sick –
Provides Sample
• Small Patient Sample Sizes
• Written Consent?
• Patient/ Data Separated
• Data Quality Over Time?
• Data Liability Over Time?
In the current typical health information system a person gets sick, signs away their rights to their tissues and/or
information, and receives no benefit in return. This model results in small, expensive, research studies and it acquires
significant liabilities over time with regards to consent disputes and potential loss of anonymity. It also makes
tracking individuals, or improving data collection over long stretches of time, difficult.

6.
Exponential/Disruptive Model
• “Brown Bag” DNA Sample Submission
(includes user account and password)
• People Own Their Own Genome
• Written Consent Evolves Into
Real Time Consent
• Dynamic Communication With Patient
• Participatory Medicine
• Self-Organizing Genetic Research
In the new model a person submits a DNA sample from a kit that contains a user account and password. Values from
their DNA are used to convert them into a node on the network. Thereafter, they can log on, setting up access for their
doctor, or others, to their genetic or other personal data. Written consent evolves into real time consent. If their password
is compromised, the person submits a new sample to re-establish ownership over the dataset. Self-organizing genomes
drive research. Third parties perform audits to prove authorized use.

7.
Personalized Medicine Genome Browser
What you see here is a
example of all the
chromosomes in a person’s
genome that a user would see
when logged on.
DNA Guide then adds layers to
this map so that a person’s
genetic data lies beneath this
image. This image has a
coordinate system associated
to it with full pan and zoom
functionality, like a type of
Google earth for the cell.
On top of this platform we
provide tools for managing the
flow of information from the
lab to any research or health
services setting with the ability
to engage the patient at home.

8.
Personalized Medicine Genome Browser
In a typical use case
scenario, a physician could
perform a search based on a
term such as “breast cancer”
and immediately view only
those markers out of a
massive dataset that are
relevant for a particular
patient.
A genome browser such as
this could help provide
genetic counselors and
health service providers a
tool to review genetic
information with their
patients.
By placing the data in this
format, we’ll be able to show
structural variants for full
genomes. Current browsers
show just one chromosome
at a time and aren’t able to do
this.
(Mitochondria)

9.
At Zoom in Level Each Base Pair Is A
Programmable Object
At the zoom in level each base pair
is a programmable object, allowing
DNA Guide to automate many of the
processes involved in interpreting
genetic data. This programming
interface can be opened up to allow
third parties to develop a whole
series of molecular diagnostic and
recreational applications to be built
that interact with the individuals
DNA.

10.
Government/NGO Regulation and
Digital Human Rights
www.DNAguide.com
Different government and NGO’s will have different regulations with regards to genetic data access. In addition,
issues around privacy and the abuse of genetic data may give rise to various forms of digital human rights. Any
entity working with personal genetic data will no doubt face the scenario where different types of base pairs and
different combinations of base pairs will be regulated differently for different users. Hence, the need for software
that manages interpretation and access down to the base pair level will be critical for transmitting genetic
information from the lab to the physician and patient consistent with regulations.

11.
Three Points of Dynamic Regulation
Quality of Science
Medical Utility
Viewing Risk
(Graded) A,B,C,D,F
W = Withdrawn
I = Incomplete
(by Scientific Community)
(by Health Care Providers/ Payors)
E = Everyone,
PG = Physician Guidance
R = Restricted
(Genetic Counselors, Ethics)
Category Rating
(Five Star Rating)
(Movie Rating)
The genetic information sector could be dynamically regulated by a process where an interpretation could be submitted
and receive a rating in three areas: quality of science, medical utility and viewing risk. Each category could be the domain
expertise of the entities indicated above by their providing rating standards which would then be applied to each genetic
marker involved in a test.

12.
Genetic Information Marketplace
Discovery Ecosystem
Research Feeds
Personalized Medicine
Patients Feed Research
R&D
Pharma /
Clinical
Trials
Consumers/
Patients
INSURANCEGovernment & NGO Regulations
Health
Services
With a rating system for quality of science, medical utility and viewing risk, genetic interpretation will have a clearer path to
market. For example, a health service provider or insurer could formulate policies such as delivering tests with a science score
of A and medical utility rating of five stars with the proper level of counseling triggered the moment the patient accessed their
genetic information.

13.
Example of Genetic Information Flow
PATIENT
Seeks Health Services
Submits DNA Sample
Views interpretation of results
from physician
Participation in Clinical Trials
Receives Drugs Info from
Pharma
Health Services Payer Entities
Require DNA tests for reimbursement of Rx and determine which genetic tests qualify for reimbursement
LAB
Process sample and results
Provide raw DNA data to
database storage for
interpretation
PHARMA/BIOTECH/R&D
INDUSTRY
Provide sample collection kits
and information regarding
personalized medicine
Interface with physician and
patients in clinical trials
Provide lab with new products
and services
Provide patient with retail
outlet for personalized
medicine products
PHYSICIAN,
PATHOLOGIST,
GENETIC COUNSELOR
Assess Patient
Interact with insurance to
determine eligibility
Prescribe test
Collect patient DNA sample
Submit DNA sample to lab
View lab information and
interpret results
Provide analysis and
recommendation to patient
Prescribe course of action.
Interface with pharma
regarding personalized
medicine
Interact with pharma with
clinical trial information
DNA Guide
Genome Management
Software Information Flow

14.
The symbols below are an example of how we could convert SNPs information into a graph form to help explain
genetic variation. Using these symbols it’s possible to stack 1,000s of genomes on top of each other in a map and see
variation.
Mobile Platform Symbols
For Ease of Use
Highest Risk
Slightly Higher
Risk
Normal
Lower Risk
Low Magnitude High Magnitude
Below we see how complex ranges of information across multiple locations could be converted to symbols to
make genetic information more easily understood by non-scientific audiences. For example, a red symbol
indicates higher risk and green lower risk. The larger the dot – the more significant the association between
high, normal or low risk.

15.
High Risk, Low Risk Assessment
Fast and Affordable
Here’s an example of what
the diagnostic results for a
high risk genome could
look like
By using a simple symbol
classification, DNA Guide
is able to provide a quick
assessment for the entire
genome.
More detailed information
could be available by
selecting the objects in the
map to generate a report.

16.
Converting the $1,000 Genome into the
Two Minute Genome
Here’s an example of a low risk
genome result.
Complex molecular diagnostic
information can be delivered in
a format that is fast and
affordable on a mobile device.
DNA Guide’s software is able
to convert the $1,000 genome
into the two minute genome –
bringing personalized
medicine to the point of care.

17.
DNA Guide Toolkit
DNA Security
Token DNA Compass DNA Body
DNA Guide uses values within the DNA
sample to uniquely identify every dataset.
This token can serve as a dynamic or
static IP address - allowing every
organism to become a node on the
network.
DNA Guide provides dynamic maps of entire
genomes available on all mobile platforms. DNA
Guide’s Compass can perform spatial analysis
across multiple layers of different types of genetic
data. Current browser solutions on the
marketplace are limited to single chromosomes
with one dimensional analysis.
DNA Guide’s DNA Body will provide
expression data, medical records, and
images to be linked to a map of the human
body and to genomic location.
DNA Guide’s solution has three core modules : a security component and map linking genetic data to 2d
and 3d representation of the cell or body. The total solution offers genetic data interoperability for all
users involved in personalized medicine.

18.
DNA Guide Security Token
DNA Guide selects about two hundred values
within each DNA sample to uniquely identify
one in a trillion persons. This DNA token
provides the foundation for further security
and a mechanism for providing privacy over
the dataset.
• Uniquely identify each dataset
• Store and retrieve genetic data anonymously
• Perform audits, merge data
• Re-associate information throughout a person’s lifetime
• Have variations for different uses
Raw DNA Values
DNA Security Token

19.
Mapping the Human Genome With
Geographic Information Systems (GIS)
DNA Guide Novel Approach:
Physical (or biological) data with annotation information is
mapped to point, line or polygon object(s) with coordinates to
enable the spatial query and analysis of information.
Line (mRNA, siRNA, indels,
translocations)
(x,y,z)
Point (alleles, SNPs, genes,
Methylation, Expression Data each
as a separate layer in the map)
• Data is optimized for spatial comparisons with ability to utilize
raster to vector conversion techniques.
• Re-project genetic data on the fly for comparison of different
alignments.
• Find the “Needle in the Haystack” (layers optimized by spatial
query).
• Leverage existing mapping tools such as buffer, cluster and
network topology analysis for discovery.
http://en.wikipedia.org/wiki/Geographic_information_system
• View Information in “Thematic Map” format
http://en.wikipedia.org/wiki/Thematic_map
(direction/distance)
Polygon (any Genetic Region)
(in) (out)

20.
Mapping From DNA, mRNA, to
Proteins, to Pathways and Beyond
Using Mapping Software to Map the Genome
GIS (Geographic Information Systems)
DNA Guide genome navigation applications use
Geographic Information Systems (GIS)
technology. The graphic objects have “topology”
which allows symbols from different layers in the
map (i.e. genes, SNPs, insertions, deletions, copy
number variations, gene expression data) to know
where they are in relation to each other. Objects
can be queried within the same layer or in relation
to different layers.
Each node in the map can have a 2 or 3D position
and direction associated with it. In the case of
genome data we treat chromosomes as
continents, SNPs as if they're towns on a map,
and genes can be treated like a State (a polygon),
highways (a line) or cities (a point) depending on
how we want to study the information. The
standard GIS data output is a thematic map, an
icon-driven format well suited for mobile
platforms.
By using mapping coordinates, users will be able
to move between layers of genetic information -
all the way from DNA to MRNA to proteins, to
pathways to the function of physiology to body
systems.
From a technology standpoint we’ve redeployed
existing mapping software and swapped out the
sphere of the earth for the cell.

21.
DNA Body Slide
The following images were
taken from Google Body
yet represent DNA Guide’s
plans to implement
mapping software to
include a representation of
the human form linked to
genetic data as part of our
solution.
We anticipate users will be
able to click on the body to
generate queries for
information, with our
eventually showing how
their genes are expressed
in their body.
DNA Guide is working
towards a future where a
person’s medical
information is linked to a
representation of their
human form with their
electronic medical record
user account information
being derived from the
values within their DNA.

22.
T
G
C
A
Acknowledgements
DNA Guide, Inc.
http://www.DNAguide.com
Alice Rathjen
President and Founder
alice@dnaguide.com
Deborah Kessler, CEO
William Kimmerly, Ph.D.
Chief Scientific Officer
Xavier Thomas
Product Development Dir.
Saw Yu Wai
Platform Architect
Mark Boguski, MD. Ph.D,
Advisor