SlideShare ist ein Scribd-Unternehmen logo
1 von 17
GENOMICS: WHERE SCIENCE FICTION 
MEETS REALITY 
Francis 
deSouza 
Illumina
Genomics: Where Science Fiction 
Meets Reality 
Francis de Souza 
President, Illumina 
@fdesouza
Genetic Code: 
‣ Defines your traits & uniqueness 
‣ Carries the blueprints that run the body and its functions 
‣ Can change or be modified by environment
Reproductive Health 
Family Planning Pregnancy Newborn Screening Inherited Disease 
Carrier Screening, 
IVF/Pre-implantation 
screening
Cancer 
Theragnostics 
Targeted treatment mix 
Predisposition 
Risk 
Early Detection 
Before the tumor 
Monitoring 
Treatment effectiveness 
& recurrence
The Sequencing Pipeline
Source: U.S. National Human Genome Research Institute, Nature
The Data Challenges 
‣ Lots of Data 
‣ Unstructured 
‣ Across silos 
‣ It all needs to be secure…
Unstructured Data 
OBSERVATION TEST 
GENOMIC 
ASSAY 
IMAGE 
SYNTHESIS 
COMPLEXITY
Anonymity 
SECURITY 
Informed 
Consent 
Patient 
Identifiers 
PRIVACY 
HIPAA
1.Sequencing begins to directly save lives 
2.Tumor samples routinely sequenced/Standard of Care 
3.Nations begin sequencing their populations 
4.Sequences accessible in electronic medical record 
5.Infants routinely sequenced at birth 
6.Cancer managed as chronic disease 
Time Frame 
(years) 
0 10 
0 10 
0 10 
0 10 
0 10 
0 10
Genomics: Where Science Fiction 
Meets Reality 
17 
Francis de Souza 
President, Illumina 
@fdesouza

Weitere ähnliche Inhalte

Andere mochten auch

BACK TO THE FUTURE: DATAFLOW FINALLY COMES OF AGE from Structure 2012
BACK TO THE FUTURE: DATAFLOW FINALLY COMES OF AGE from Structure 2012BACK TO THE FUTURE: DATAFLOW FINALLY COMES OF AGE from Structure 2012
BACK TO THE FUTURE: DATAFLOW FINALLY COMES OF AGE from Structure 2012Gigaom
 
Structure 2014 - The future of cloud computing survey results
Structure 2014 - The future of cloud computing survey resultsStructure 2014 - The future of cloud computing survey results
Structure 2014 - The future of cloud computing survey resultsGigaom
 
Structure 2014 - Launchpad Competition
Structure 2014 - Launchpad CompetitionStructure 2014 - Launchpad Competition
Structure 2014 - Launchpad CompetitionGigaom
 
Structure 2014 - The right and wrong way to scale - Rackspace
Structure 2014 - The right and wrong way to scale - RackspaceStructure 2014 - The right and wrong way to scale - Rackspace
Structure 2014 - The right and wrong way to scale - RackspaceGigaom
 
Structure 2014 - The strategic value of the cloud - Joe Weinman
Structure 2014 - The strategic value of the cloud - Joe WeinmanStructure 2014 - The strategic value of the cloud - Joe Weinman
Structure 2014 - The strategic value of the cloud - Joe WeinmanGigaom
 

Andere mochten auch (10)

Ppc glossary
Ppc glossaryPpc glossary
Ppc glossary
 
Django ws
Django wsDjango ws
Django ws
 
UX, UI, WTF
UX, UI, WTFUX, UI, WTF
UX, UI, WTF
 
BACK TO THE FUTURE: DATAFLOW FINALLY COMES OF AGE from Structure 2012
BACK TO THE FUTURE: DATAFLOW FINALLY COMES OF AGE from Structure 2012BACK TO THE FUTURE: DATAFLOW FINALLY COMES OF AGE from Structure 2012
BACK TO THE FUTURE: DATAFLOW FINALLY COMES OF AGE from Structure 2012
 
The laddo project
The laddo projectThe laddo project
The laddo project
 
Django Worst Practices
Django Worst PracticesDjango Worst Practices
Django Worst Practices
 
Structure 2014 - The future of cloud computing survey results
Structure 2014 - The future of cloud computing survey resultsStructure 2014 - The future of cloud computing survey results
Structure 2014 - The future of cloud computing survey results
 
Structure 2014 - Launchpad Competition
Structure 2014 - Launchpad CompetitionStructure 2014 - Launchpad Competition
Structure 2014 - Launchpad Competition
 
Structure 2014 - The right and wrong way to scale - Rackspace
Structure 2014 - The right and wrong way to scale - RackspaceStructure 2014 - The right and wrong way to scale - Rackspace
Structure 2014 - The right and wrong way to scale - Rackspace
 
Structure 2014 - The strategic value of the cloud - Joe Weinman
Structure 2014 - The strategic value of the cloud - Joe WeinmanStructure 2014 - The strategic value of the cloud - Joe Weinman
Structure 2014 - The strategic value of the cloud - Joe Weinman
 

Mehr von Gigaom

Structure 2014 - Cloud trends - Battery
Structure 2014 - Cloud trends - BatteryStructure 2014 - Cloud trends - Battery
Structure 2014 - Cloud trends - BatteryGigaom
 
Structure Data 2014: HOW MICRODATA CAN SAY A LOT ABOUT MACROECONOMICS, David ...
Structure Data 2014: HOW MICRODATA CAN SAY A LOT ABOUT MACROECONOMICS, David ...Structure Data 2014: HOW MICRODATA CAN SAY A LOT ABOUT MACROECONOMICS, David ...
Structure Data 2014: HOW MICRODATA CAN SAY A LOT ABOUT MACROECONOMICS, David ...Gigaom
 
Structure Data 2014: QLIK SPONSOR WORKSHOP: ANALYTICS THE WAY NATURE INTENDED...
Structure Data 2014: QLIK SPONSOR WORKSHOP: ANALYTICS THE WAY NATURE INTENDED...Structure Data 2014: QLIK SPONSOR WORKSHOP: ANALYTICS THE WAY NATURE INTENDED...
Structure Data 2014: QLIK SPONSOR WORKSHOP: ANALYTICS THE WAY NATURE INTENDED...Gigaom
 
Structure Data 2014: FIVE MYTHS ABOUT BIG DATA, Amit Bendov
Structure Data 2014: FIVE MYTHS ABOUT BIG DATA, Amit BendovStructure Data 2014: FIVE MYTHS ABOUT BIG DATA, Amit Bendov
Structure Data 2014: FIVE MYTHS ABOUT BIG DATA, Amit BendovGigaom
 
Structure Data 2014: AMID BILLIONS OF METRICS, YOUR SOFTWARE IS TRYING TO TEL...
Structure Data 2014: AMID BILLIONS OF METRICS, YOUR SOFTWARE IS TRYING TO TEL...Structure Data 2014: AMID BILLIONS OF METRICS, YOUR SOFTWARE IS TRYING TO TEL...
Structure Data 2014: AMID BILLIONS OF METRICS, YOUR SOFTWARE IS TRYING TO TEL...Gigaom
 
Structure Data 2014: SISENSE SPONSOR WORKSHOP: ON BEER, CHIPS AND DATA,
Structure Data 2014: SISENSE SPONSOR WORKSHOP: ON BEER, CHIPS AND DATA, Structure Data 2014: SISENSE SPONSOR WORKSHOP: ON BEER, CHIPS AND DATA,
Structure Data 2014: SISENSE SPONSOR WORKSHOP: ON BEER, CHIPS AND DATA, Gigaom
 
Structure Data 2014: INVERTING 80/20: BEYOND BESPOKE BIG DATA, Ari Gesher
Structure Data 2014: INVERTING 80/20: BEYOND BESPOKE BIG DATA, Ari GesherStructure Data 2014: INVERTING 80/20: BEYOND BESPOKE BIG DATA, Ari Gesher
Structure Data 2014: INVERTING 80/20: BEYOND BESPOKE BIG DATA, Ari GesherGigaom
 
Structure Data 2014: TRACKING A SOCCER GAME WITH BIG DATA, Chris Haddad
Structure Data 2014: TRACKING A SOCCER GAME WITH BIG DATA, Chris HaddadStructure Data 2014: TRACKING A SOCCER GAME WITH BIG DATA, Chris Haddad
Structure Data 2014: TRACKING A SOCCER GAME WITH BIG DATA, Chris HaddadGigaom
 
Structure Data 2014: TECH AGAINST HUMAN TRAFFICKING AND ILLICIT NETWORKS, Jus...
Structure Data 2014: TECH AGAINST HUMAN TRAFFICKING AND ILLICIT NETWORKS, Jus...Structure Data 2014: TECH AGAINST HUMAN TRAFFICKING AND ILLICIT NETWORKS, Jus...
Structure Data 2014: TECH AGAINST HUMAN TRAFFICKING AND ILLICIT NETWORKS, Jus...Gigaom
 
Structure Data 2014: DATA DRIVEN DESIGN AT FORMULA ONE SPEED, Geoff McGrath
Structure Data 2014: DATA DRIVEN DESIGN AT FORMULA ONE SPEED, Geoff McGrathStructure Data 2014: DATA DRIVEN DESIGN AT FORMULA ONE SPEED, Geoff McGrath
Structure Data 2014: DATA DRIVEN DESIGN AT FORMULA ONE SPEED, Geoff McGrathGigaom
 
Structure Data 2014: IS VIDEO BIG DATA?, Steve Russell
Structure Data 2014: IS VIDEO BIG DATA?, Steve RussellStructure Data 2014: IS VIDEO BIG DATA?, Steve Russell
Structure Data 2014: IS VIDEO BIG DATA?, Steve RussellGigaom
 
Structure Data 2014: BIG DATA ANALYTICS RE-INVENTED, Ryan Waite
Structure Data 2014: BIG DATA ANALYTICS RE-INVENTED, Ryan WaiteStructure Data 2014: BIG DATA ANALYTICS RE-INVENTED, Ryan Waite
Structure Data 2014: BIG DATA ANALYTICS RE-INVENTED, Ryan WaiteGigaom
 
How Data is Remaking E-commerce - from Roadmap 2013
How Data is Remaking E-commerce - from Roadmap 2013How Data is Remaking E-commerce - from Roadmap 2013
How Data is Remaking E-commerce - from Roadmap 2013Gigaom
 
25 Favorite Experiences in Tech - from Roadmap 2013
25 Favorite Experiences in Tech - from Roadmap 201325 Favorite Experiences in Tech - from Roadmap 2013
25 Favorite Experiences in Tech - from Roadmap 2013Gigaom
 
How Moore’s Law is Influencing Design - from Roadmap 2013
How Moore’s Law is Influencing Design - from Roadmap 2013How Moore’s Law is Influencing Design - from Roadmap 2013
How Moore’s Law is Influencing Design - from Roadmap 2013Gigaom
 
Building the Visual Language of the Web - from Roadmap 2013
Building the Visual Language of the Web - from Roadmap 2013Building the Visual Language of the Web - from Roadmap 2013
Building the Visual Language of the Web - from Roadmap 2013Gigaom
 
Your Device Knows What You’re Thinking Before You Do - from Mobilize 2013
Your Device Knows What You’re Thinking Before You Do - from Mobilize 2013Your Device Knows What You’re Thinking Before You Do - from Mobilize 2013
Your Device Knows What You’re Thinking Before You Do - from Mobilize 2013Gigaom
 
Gigaom Research Sector RoadMap: Enterprise Mobility Management
Gigaom Research Sector RoadMap: Enterprise Mobility Management Gigaom Research Sector RoadMap: Enterprise Mobility Management
Gigaom Research Sector RoadMap: Enterprise Mobility Management Gigaom
 
5 ESSENTIAL TOOLS FOR OPTIMIZING IAAS from Structure:Europe 2013
5 ESSENTIAL TOOLS FOR OPTIMIZING IAAS from Structure:Europe 20135 ESSENTIAL TOOLS FOR OPTIMIZING IAAS from Structure:Europe 2013
5 ESSENTIAL TOOLS FOR OPTIMIZING IAAS from Structure:Europe 2013Gigaom
 
BMW ACCELERATES CLOUD ADOPTION WITH ODCA from Structure:Europe 2013
BMW ACCELERATES CLOUD ADOPTION WITH ODCA from Structure:Europe 2013BMW ACCELERATES CLOUD ADOPTION WITH ODCA from Structure:Europe 2013
BMW ACCELERATES CLOUD ADOPTION WITH ODCA from Structure:Europe 2013Gigaom
 

Mehr von Gigaom (20)

Structure 2014 - Cloud trends - Battery
Structure 2014 - Cloud trends - BatteryStructure 2014 - Cloud trends - Battery
Structure 2014 - Cloud trends - Battery
 
Structure Data 2014: HOW MICRODATA CAN SAY A LOT ABOUT MACROECONOMICS, David ...
Structure Data 2014: HOW MICRODATA CAN SAY A LOT ABOUT MACROECONOMICS, David ...Structure Data 2014: HOW MICRODATA CAN SAY A LOT ABOUT MACROECONOMICS, David ...
Structure Data 2014: HOW MICRODATA CAN SAY A LOT ABOUT MACROECONOMICS, David ...
 
Structure Data 2014: QLIK SPONSOR WORKSHOP: ANALYTICS THE WAY NATURE INTENDED...
Structure Data 2014: QLIK SPONSOR WORKSHOP: ANALYTICS THE WAY NATURE INTENDED...Structure Data 2014: QLIK SPONSOR WORKSHOP: ANALYTICS THE WAY NATURE INTENDED...
Structure Data 2014: QLIK SPONSOR WORKSHOP: ANALYTICS THE WAY NATURE INTENDED...
 
Structure Data 2014: FIVE MYTHS ABOUT BIG DATA, Amit Bendov
Structure Data 2014: FIVE MYTHS ABOUT BIG DATA, Amit BendovStructure Data 2014: FIVE MYTHS ABOUT BIG DATA, Amit Bendov
Structure Data 2014: FIVE MYTHS ABOUT BIG DATA, Amit Bendov
 
Structure Data 2014: AMID BILLIONS OF METRICS, YOUR SOFTWARE IS TRYING TO TEL...
Structure Data 2014: AMID BILLIONS OF METRICS, YOUR SOFTWARE IS TRYING TO TEL...Structure Data 2014: AMID BILLIONS OF METRICS, YOUR SOFTWARE IS TRYING TO TEL...
Structure Data 2014: AMID BILLIONS OF METRICS, YOUR SOFTWARE IS TRYING TO TEL...
 
Structure Data 2014: SISENSE SPONSOR WORKSHOP: ON BEER, CHIPS AND DATA,
Structure Data 2014: SISENSE SPONSOR WORKSHOP: ON BEER, CHIPS AND DATA, Structure Data 2014: SISENSE SPONSOR WORKSHOP: ON BEER, CHIPS AND DATA,
Structure Data 2014: SISENSE SPONSOR WORKSHOP: ON BEER, CHIPS AND DATA,
 
Structure Data 2014: INVERTING 80/20: BEYOND BESPOKE BIG DATA, Ari Gesher
Structure Data 2014: INVERTING 80/20: BEYOND BESPOKE BIG DATA, Ari GesherStructure Data 2014: INVERTING 80/20: BEYOND BESPOKE BIG DATA, Ari Gesher
Structure Data 2014: INVERTING 80/20: BEYOND BESPOKE BIG DATA, Ari Gesher
 
Structure Data 2014: TRACKING A SOCCER GAME WITH BIG DATA, Chris Haddad
Structure Data 2014: TRACKING A SOCCER GAME WITH BIG DATA, Chris HaddadStructure Data 2014: TRACKING A SOCCER GAME WITH BIG DATA, Chris Haddad
Structure Data 2014: TRACKING A SOCCER GAME WITH BIG DATA, Chris Haddad
 
Structure Data 2014: TECH AGAINST HUMAN TRAFFICKING AND ILLICIT NETWORKS, Jus...
Structure Data 2014: TECH AGAINST HUMAN TRAFFICKING AND ILLICIT NETWORKS, Jus...Structure Data 2014: TECH AGAINST HUMAN TRAFFICKING AND ILLICIT NETWORKS, Jus...
Structure Data 2014: TECH AGAINST HUMAN TRAFFICKING AND ILLICIT NETWORKS, Jus...
 
Structure Data 2014: DATA DRIVEN DESIGN AT FORMULA ONE SPEED, Geoff McGrath
Structure Data 2014: DATA DRIVEN DESIGN AT FORMULA ONE SPEED, Geoff McGrathStructure Data 2014: DATA DRIVEN DESIGN AT FORMULA ONE SPEED, Geoff McGrath
Structure Data 2014: DATA DRIVEN DESIGN AT FORMULA ONE SPEED, Geoff McGrath
 
Structure Data 2014: IS VIDEO BIG DATA?, Steve Russell
Structure Data 2014: IS VIDEO BIG DATA?, Steve RussellStructure Data 2014: IS VIDEO BIG DATA?, Steve Russell
Structure Data 2014: IS VIDEO BIG DATA?, Steve Russell
 
Structure Data 2014: BIG DATA ANALYTICS RE-INVENTED, Ryan Waite
Structure Data 2014: BIG DATA ANALYTICS RE-INVENTED, Ryan WaiteStructure Data 2014: BIG DATA ANALYTICS RE-INVENTED, Ryan Waite
Structure Data 2014: BIG DATA ANALYTICS RE-INVENTED, Ryan Waite
 
How Data is Remaking E-commerce - from Roadmap 2013
How Data is Remaking E-commerce - from Roadmap 2013How Data is Remaking E-commerce - from Roadmap 2013
How Data is Remaking E-commerce - from Roadmap 2013
 
25 Favorite Experiences in Tech - from Roadmap 2013
25 Favorite Experiences in Tech - from Roadmap 201325 Favorite Experiences in Tech - from Roadmap 2013
25 Favorite Experiences in Tech - from Roadmap 2013
 
How Moore’s Law is Influencing Design - from Roadmap 2013
How Moore’s Law is Influencing Design - from Roadmap 2013How Moore’s Law is Influencing Design - from Roadmap 2013
How Moore’s Law is Influencing Design - from Roadmap 2013
 
Building the Visual Language of the Web - from Roadmap 2013
Building the Visual Language of the Web - from Roadmap 2013Building the Visual Language of the Web - from Roadmap 2013
Building the Visual Language of the Web - from Roadmap 2013
 
Your Device Knows What You’re Thinking Before You Do - from Mobilize 2013
Your Device Knows What You’re Thinking Before You Do - from Mobilize 2013Your Device Knows What You’re Thinking Before You Do - from Mobilize 2013
Your Device Knows What You’re Thinking Before You Do - from Mobilize 2013
 
Gigaom Research Sector RoadMap: Enterprise Mobility Management
Gigaom Research Sector RoadMap: Enterprise Mobility Management Gigaom Research Sector RoadMap: Enterprise Mobility Management
Gigaom Research Sector RoadMap: Enterprise Mobility Management
 
5 ESSENTIAL TOOLS FOR OPTIMIZING IAAS from Structure:Europe 2013
5 ESSENTIAL TOOLS FOR OPTIMIZING IAAS from Structure:Europe 20135 ESSENTIAL TOOLS FOR OPTIMIZING IAAS from Structure:Europe 2013
5 ESSENTIAL TOOLS FOR OPTIMIZING IAAS from Structure:Europe 2013
 
BMW ACCELERATES CLOUD ADOPTION WITH ODCA from Structure:Europe 2013
BMW ACCELERATES CLOUD ADOPTION WITH ODCA from Structure:Europe 2013BMW ACCELERATES CLOUD ADOPTION WITH ODCA from Structure:Europe 2013
BMW ACCELERATES CLOUD ADOPTION WITH ODCA from Structure:Europe 2013
 

Kürzlich hochgeladen

Elevate Developer Efficiency & build GenAI Application with Amazon Q​
Elevate Developer Efficiency & build GenAI Application with Amazon Q​Elevate Developer Efficiency & build GenAI Application with Amazon Q​
Elevate Developer Efficiency & build GenAI Application with Amazon Q​Bhuvaneswari Subramani
 
FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024The Digital Insurer
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FMESafe Software
 
Exploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusExploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusZilliz
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FMESafe Software
 
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc
 
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost SavingRepurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost SavingEdi Saputra
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...DianaGray10
 
Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)Zilliz
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerThousandEyes
 
MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MIND CTI
 
DBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDropbox
 
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot TakeoffStrategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoffsammart93
 
Strategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a FresherStrategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a FresherRemote DBA Services
 
AWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAndrey Devyatkin
 
Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...apidays
 
Vector Search -An Introduction in Oracle Database 23ai.pptx
Vector Search -An Introduction in Oracle Database 23ai.pptxVector Search -An Introduction in Oracle Database 23ai.pptx
Vector Search -An Introduction in Oracle Database 23ai.pptxRemote DBA Services
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfsudhanshuwaghmare1
 
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWEREMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWERMadyBayot
 
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...apidays
 

Kürzlich hochgeladen (20)

Elevate Developer Efficiency & build GenAI Application with Amazon Q​
Elevate Developer Efficiency & build GenAI Application with Amazon Q​Elevate Developer Efficiency & build GenAI Application with Amazon Q​
Elevate Developer Efficiency & build GenAI Application with Amazon Q​
 
FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
Exploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusExploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with Milvus
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
 
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost SavingRepurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
 
Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024
 
DBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor Presentation
 
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot TakeoffStrategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
 
Strategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a FresherStrategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a Fresher
 
AWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of Terraform
 
Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...
 
Vector Search -An Introduction in Oracle Database 23ai.pptx
Vector Search -An Introduction in Oracle Database 23ai.pptxVector Search -An Introduction in Oracle Database 23ai.pptx
Vector Search -An Introduction in Oracle Database 23ai.pptx
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
 
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWEREMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
 
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
 

Structure 2014 - Genomics - where science fiction meets reality - Illumina

Hinweis der Redaktion

  1. Oncology start to finish transformation (would like to create something similar to reproductive health paradigm) - Relegating cancer to a chronic disease
  2. In addition to direct impacts to human health and health care, there are many other markets affected by genomic science that will impact our quality of life. Like public safety … Forensics Forensics Story – what will be possible? Full profiling (eye color, ethnicity, hair, etc.) from genetic material
  3. In genome sequencing, data is generated, analyzed computationally and then those findings are “interpreted”, typically by experts. When you think about populations being sequenced and scaling this process, it begs for automation. 700TB = NetFlix repository = that would hold 210,000 whole human genomes Developed world population = 7.2B in 2013, expected to go to 8.2B over the next 12 years 4,761 times more data 1TB disk drive = 300 whole human genomes Public genome repositories, such as the one maintained by the National Center for Biotechnology Information, or NCBI, already house petabytes — millions of gigabytes — of data, and biologists around the world are churning out 15 petabases (a base is a letter of DNA) of sequence per year. If these were stored on regular DVDs, the resulting stack would be 2.2 miles tall. http://www.wired.com/2013/10/big-data-biology/ roughly 100 billion bases and millions of genes that make up the microbes found in the human body. Life scientists are embarking on countless other big data projects, including efforts to analyze the genomes of many cancers, to map the human brain, and to develop better biofuels and other crops. (The wheat genome is more than five times larger than the human genome, and it has six copies of every chromosome to our two.) uencing, data is generated, analyzed computationally and then those findings are “interpreted”. This process doesn’t scale when you are talking populations and begs for automation.
  4. But unlike the computing space, where Moore’s law is our friend, in the genomics space, we are outstripping the pace of Moore’s law, which is both amazing and also creates a challenge….
  5. This is where we need to go … but there are challenges…. Major hurdle is aggregating and analyzing the voluminous data output and interpreting it for clinical decisions. Need streamlined, scalable processes Data is unstructured and some of it is not easily analyzed as a result Once aggregated, we need standards and structure to make it usable for analytics. Data is in siloes today Need discovery environment that support all scientific/medical experts Need comprehensive longitudinal review of a patient record incorporating a variety of data across systems Integrate public data with private data Analysis is too complex Curation is manual today, using experts that provide a qualitative “filter” to what’s relevant and what’s not, what should be dug into further Need simplified interfaces that allow clinicians, patients to query the data and receive simplified answer sets And it all needs to be secure, compliant and be able to be anonymized
  6. Clinical data is highly dimensional, temporal, and disconnected from molecular data. Patient data in multiple transactional system is difficult to aggregate (average hospital EMR integration can have over 100 integration points) Genomic information is inherently complex with most relationships not well understood DNA/RNA, RNA/methylation, temporal, risk predisposition, etc Genomic information is poorly available in a medical context Like many data types, it’s inherently temporal, especially in progressive diseases like cancer To make things worse, scientists don’t have a good understanding of how many of these different variables interact. Discovery of novel relationships can guide deeper dives by specialists Interactive analytics is a proven tool to enable subject matter experts Big data analytics will expand impact by allowing better access to aggregated information Normalization across data sets unlocks the value of data aggregation Ontologies a required first step! There is enormous leverage in the combination of curated private data that can be combined with normalized public information In an effort to deal with some of these challenges, in 2012 the National Institutes of Health launched the Big Data to Knowledge Initiative (BD2K), which aims, in part, to create data sharing standards and develop data analysis tools that can be easily distributed. Researchers studying social media networks, by contrast, know exactly what the data they are collecting means; each node in the network represents a Facebook account, for example, with links delineating friends. A gene regulatory network, which attempts to map how different genes control the expression of other genes, is smaller than a social network, with thousands rather than millions of nodes. But the data is harder to define. “The data from which we construct networks is noisy and imprecise,” said Zola. “When we look at biological data, we don’t know exactly what we are looking at yet.” - From Wired article on big data and genomics
  7. LOTS OF DATA AND COMPLEX DATA The data picture progresses as populations of patients, even countries are sequenced and clinical data or phenotypic information, are collected. The data sources are diverse and always changing/evolving: new research, patients self-reporting, lots of open text information on phenotype, hundreds of data integration points in an EMR (xrays, blood tests, etc.) This data needs to be analyzed across massive databases for patterning. For example: How many patients with this genotype, have this type of breast cancer and have done well on this drug? What drug was used the most successfully for my patient who has diabetes, heart disease and this genotype? Artificial intelligence is not “intelligent” enough to handle it Patterning, differential analysis, are used in the computing world and can be applied to the world of genomic data It is only through rapid evolution of analysis tools that we will be able to deliver on the promise of individualized, personalized health care, treating the specific genetic and resulting physical attributes whole-istically.
  8. Consent Privacy Security Anonymity Personal Identifiers HIPAA
  9. The genomic revolution is here and we are in the fast lane on the genetic superhighway. It’s a brave new world, a genetic superhighway and at Illumina we believe it will take us far and transform our lives.