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

The Problem.. Inadequate Infrastructure

Genetic Data Explosion Huge investment in

Sequencing Technologies

and Molecular Diagnostics

Personalized Medicine

R&D

Pharma /

Clinical

Trials

Consumers/

Patients IN

SU

RA

NC

E

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.

Anxiety and Fear of Genetic Data

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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.

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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.

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.

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.

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.

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)

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.

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.

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.

Genetic Information Marketplace

Discovery Ecosystem Research Feeds

Personalized Medicine Patients Feed Research

R&D

Pharma /

Clinical

Trials

Consumers/

Patients IN

SU

RA

NC

E

Government & 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.

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

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.

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.

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.

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.

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

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)

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.

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.

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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