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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
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.
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.
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.
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
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.
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.
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

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Possible Solution for Managing the Worlds Personal Genetic Data - DNA Guide, Inc.

  • 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

Editor's Notes

  1. DNA Guide is a California based start-up – focusing on the security and visualization of genetic data on mobile platforms - the idea being other entities would create genetic data and provide the interpretation for it and we help distribute it. Today I would like to propose a possible solution for managing the worlds personal genetic data – one that may be able to help us all navigate the areas of genetic regulation, privacy and ease of use.
  2. 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. Personal genetic information is highly sensitive data touching on the areas of identity, paternity, self worth, and privacy. The problem that really needs to solved is how to cultivate a sense of trust between physicians and patients and how to structure information transfer in such a way that patients can participate in the management of their health data as their bodies become increasingly digital.
  4. 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.
  5. 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 acquires significant liabilities over time with regards to consent disputes and potential loss of anonymity. It’s also difficult tracking individuals or improving data collection over long stretches of time.
  6. In the new model a person submits a DNA sample kit that contains a user account and password which in turn provides the foundation for their electronic medical record. They long on, set up access for their doctor, or other entity to their genome and over time /or other personal information. Written consent evolves into real time consent. Ideally people would have the option to only do business with those entities that agree to third party audits to prove authorized use. If their password is compromised – the person submits a new sample to re-establish ownership over the dataset. T
  7. What you see here is a example of all the chromosomes in a persons genome that a user would see when logged on. DNA Guide then adds layers to this map so that a person sequence and/or SNP information lies beneath this image that has a coordinate system associated to it with the full pan and zoom of a type of Google earth for the cell. On top of this platform we then provide tools for managing the flow of information from the lab, to any health services environment, ability to engage physician patient or consumer at home.
  8. At the zoom in level each base pair is a programmable object – allowing DNA Guide to automate many of the processes involved in the interpretation of genetic data. DNA Guide can open up the application programming interface for a whole series of molecular diagnostics and recreational applications to be built that interact with the individuals DNA as manage interpretation and access down to the base pair level. (trigger counseling at the moment information is accessed). We can open up the application programming interface for a whole series of molecular diagnostics and recreational applications to be built that interact with the individuals DNA as well as apply organizational
  9. 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.
  10. One way of regulating the genetic information sector is for there to be a process where a commercial interpretation could be submitted and receive an identifier along with 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 with their providing a rating which would then be applied to each genetic marker involved in the test.
  11. By applying a rating system for quality of science, medical utility and viewing risk – personal genetic data will be able to enter the market place with the various players able to monetize and while refining the deployment of personalized medicine. For example, a health service provider would formulate policies such as delivering tests with a science score of A and medical utility rating of 5 stars or higher and have the application built such that the proper level of patient counseling was triggered the moment the patient went to access their genetic information.
  12. This diagram here outlines the needs regarding the flow of genetic information between patient, payers, the lab, and any research and health services setting.
  13. The symbols above 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 and detect variation. Here we see how complex ranges of information across multiple locations could be placed into a format that would make genetic informaiton available to non-scientific audiences.
  14. Here we did a query on breast cancer and are showing some of his higher risk markers. We’re looking for funding to scale this application to include an entire genome. By placing the data in this format we’ll be able to show insertions, deletions, copy number variants as well as incorporate gene expression data into a single map. Current browsers show just one chromosome at a time and aren’t able to do this.
  15. Here we did a query on breast cancer and are showing some of his higher risk markers. We’re looking for funding to scale this application to include an entire genome. By placing the data in this format we’ll be able to show insertions, deletions, copy number variants as well as incorporate gene expression data into a single map. Current browsers show just one chromosome at a time and aren’t able to do this.
  16. This slide explains some of the benefits of using geographic information systems technology on a genetic dataset. Genetic markers are converted into a point, line or polygon that can be spatially analyzed in relation to each other.
  17. What DNA Guide has done is swap out the earth for the cell. 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. The current bioinformatics tools aren’t able to do this.
  18. Special thanks to Saw Yu Wai for her work on getting the full extents of the genome working on the various mobile platforms for us and the rest of DNA Guide’s team.