Quan%fying  Health:  Digitally  Disrup%ng  the  Health  Care  System  

Jerry  Sheehan,  Chief  of  Staff  California  Ins%tute  for  Telecommunica%ons  and  

Informa%on  Technology  [Calit2]    

Presenta%on  to  California  Emerging  Technology  Fund  Board,  June  22nd,  2012  

 

My  Car:    An  Analogy  

Calit2’s Digitally Enabled Genomic Medicine View of The Future is Emerging

July/August 2011 February 2012

Quan%fying  My  Weight  

Technology  used,  Withings  Scale,  see  hLp://www.withings.com  

Quan%fying  My  Ac%vity  and  Caloric  Intake  

Source:    Bodymedia,  see  hLp://www.bodymedia.com  

Quan%fying  My  Sleep  

Technology  used,  Zeo,  see  hLp://myzeo.com  

Making  a  Game  of  My  Measurements  

Technology  used,  Nike+Fuel  Band,  see  hLp://www.nike.com/fuelband    

Data  Fuels  Scien%fic  Discovery  

Many  Users,  Rich  Data,  Big  Data  Challenges  

•  23&Me:      – 150,000  Users  

 • Nike+  Users:  

– +5M  Users  

Source:  BodyMedia  Blog  

The  World’s  Most  Self-­‐Aware  Man?:    The  Atlan%c  July-­‐August  2012  

July-­‐August  2012  

hLp://www.theatlan%c.com/magazine/archive/2012/07/the-­‐measured-­‐man/9018/?single_page=true  

A  Quick  Message  from  the  Measured  Man    

The  Exposome  

“Genes  load  the  gun,  Environment  pulls  the  trigger”    –  Francis  Collins,  MD,  PhD  

The  Exposome  

Historical  approaches  to  measuring            environmental  exposures  and  behaviors  -­‐    •  Self  report  via  quesEonnaires  every  few  day  or  months  (if  

that…)  

•  Biomarkers  (e.g.  blood,  urine)  of  exposure,  some  good  but  others  that  are  oNen  indirect  and  imprecise  or  focused  on  only  one  or  two  outcomes.  

•  Direct  measurement  of  the  environment  across  a  broad  geographic  area  yielding  only  crude  inferences  about  person-­‐level    exposures  in  Eme  and  space.  Moreover,  these  are    almost  always  focused  only  on  air  and  water.  

BUT…MILLIONS  OF  NEW  SENSORS  AND  DEVICES  CHANGE  THIS  AND  CREATE  UNPRECDENTED  OPPORTUNITIES  FOR  POPULATION  LEVEL  SENSING  AND  INTEVENTION    

Dr.  Kevin  Patrick,  UC  San  Diego  

PALMS  Personal  AcEvity  LocaEon  Measurement  System    

•  Funded  by  NIH/NCI  Grant  1  U01  

CA130771-­‐01  Genes,  Environment  and  Health  Ini%a%ve  (GEI)  

•  Kevin  Patrick,  Jacqueline  Kerr,  Fredric  Raab,  Greg  Norman,  Barry  Demchak,  Ingolf  Krueger,  Suneeta  Godbole  

PALMS  Fuses  Physical  Ac%vity  Data  with  GPS:  Showing  How  and  Where  PA  Occurs  

Heart  rate  shown  in  Google  Earth  

resting light moderate vigorous

PALMS  Can  Place  These  Data  Within  GIS  To  Provide  CONTEXT  

Heart rate shown in ESRI ArcGIS against land use

Heart  Rate  Fused  with  Land  Use  from  ESRI  ArcGIS    

 K.  Patrick  |  Slide  17  

   Determine  Indoor  /  Outdoor  

30 second epoch

Indoors

Outdoors

Tracking indoor and outdoor time

Research  QuesEon:  Is  Time  Spent  Outdoors  Related  To  Cancer  Outcomes,    Mental  Health  Status  Or  PolluEon  Exposures  Of  Interest?  

   Merged  GPS  &  AcEvity  Data  

Sedentary

Light

Moderate

Research  QuesEon:  Which  Park  Features  Support  the  Most  Physical  AcEvity?    

PALMS  Users  Worldwide   ((5  –  7  days  of  data  for  1800+  par%cipants)  

As  of  6/1/2012  

Ci%Sense  

Always-­‐on  Par%cipatory  Sensing  for  Air  Quality  

Principal  Inves%gator:    Bill  Griswold,  Computer  Science  &  Engineering,  UC  San  Diego    Co-­‐Inves%gators:    Sanjoy  Dasgupta,  Tajana  Rosing,  Ingolf  Krueger,  Hovav  Shacham,  Kevin  Patrick    

Measuring  Air  Quality  in  San  Diego  

10  EPA  Sensors    3.1  Million  Residents    4000  Square  Miles  

The  Ci%Sense  Project:  A  UCSD/NSF  Project  

EPA  

Ci%Sense            

contribute  

distribute  

Ci%Sense  Hardware  

Temperature,  Humidity,  Barometric  Pressure  3  Electrochemical  gas  sensors:    CO,  NO2,  Ozone  

The  Sensor   Smart  Phones  for  Data  Storage/Analysis  

Aggregated  User  Data  &  User  Feedback  

“I  guess  I  always  just  thought  of  the  atmosphere  as  being  evenly  mixed  but  it  is  not”,  

The  Looming  Data  and  Computa%onal  Challenge  In  Health  

You  Are  A  Superorganism:  Your  Body  Has  Ten  Microbes  For  Every  Human  Cell!  

Source:    Science  v.330,  p.  1619  (2010)  

Firmicutes  Are  the  Dominant  Phyla    in  the  Human  Microbiome  

Integra%ve  Personal  Omics  Profiling:  1000x  the  Leading  Edge  of  Data  Today  

•  Michael  Snyder,  Chair  of  Genomics  Stanford  Univ.  

•  Genome  140x  Coverage  •  Blood  Tests  20  Times  in  14  

Months  –  tracked  nearly  20,000  

dis%nct  transcripts  coding  for  12,000  genes  

–  measured  the  rela%ve  levels  of  more  than  6,000  proteins  and  1,000  metabolites  in  Snyder's  blood  

Cell  148,  1293–1307,  March  16,  2012  

SDSC/Triton  

Skaggs/Users    

         Storage  Leichtag/Sequencer  

Calit2/Storage  

UCSD  Next  Genera%on  Sequencer  Example:  Professor  Trey  Idekar    

Source:  Chris  Misleh,  Calit2/SOM  

Next  Gen    Sequencers  Generate    ~1TB/Run  

New  NCBC:  integra%ng  Data  for  Analysis,    Anonymiza%on,  and  SHaring  (iDASH)  

funded  by  NIH  U54HL108460    29  

•  Data  Exported  for  Computa%on  Elsewhere  –  Users  download  data  from  iDASH  

                                             

•  Computa%on  Comes  to  the  Data  –  Users  access  data  in  iDASH  –  Users  upload  algorithms  into  iDASH  

•  iDASH  Exportable  Cyberinfrastructure  –  Users  download  infrastructure  

 

   

 –     

Private  Cloud  at  SD  Supercomputer  Center  Medical  Center  Data  HosEng  

HIPAA  cerEfied  facility  

Source:  Lucila  Ohno-­‐Machado,  UCSD  SOM  

The  Future  of  Health  is  Understanding  Networks  

Source:    New  England  Journal  of  Medicine,  Network  Medicine-­‐From  Obesity  to  the  Diseasome”,  July  2007    Editorial  by  Dr.  Albert-­‐Laszlo  Barbasi