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

World DNA Day and Genome Day, Dalian China 2011
"Possible Solution for Managing the Worlds Genetic Data" given by Alice Rathjen, Founder & President DNA Guide, Inc.
Proposes genetic tests be given a rating for quality of science, medical utility and viewing risk so as to facilitate the flow of genetic information in a responsible manner from the lab to the physician and patient. Explains how technology combined with public policy could enable both privacy and personalized medicine to thrive. Advocates individual ownership over personal genetic data and suggests the genome as a data format could provide the foundation for digital human rights.

tags: DNA, genetic testing, privacy, personalized medicine, FDA regulation

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

  1. 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
  2. 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. 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. 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. 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. 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. 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. 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. 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. 10. Government/NGO Regulation and Digital Human Rights 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. • View Information in “Thematic Map” format (direction/distance) Polygon (any Genetic Region) (in) (out)
  20. 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. 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. 22. T G C A Acknowledgements DNA Guide, Inc. Alice Rathjen President and Founder 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