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 Personalised	  and	  Par,cipatory	                       Medicine	                                            	          ...
Introduc$on	  •  Broadband	  can	  provide	  many	     opportuni$es	  for	  the	  health	  sector:	      –  Improving	  yo...
Aging	  Well  	  –  Mobile	  and	  broadband	   	     technologies	  for	  ameliora,ng	     social	  isola,on	  in	  older...
Telehealth	  –    Individual	  Electronic	  Health	  Records	   	  –    The	  Telestroke	  Study	  –    Hap*c	  Tele-­‐Reh...
Current	  challenges	  in	  Medicine	  •  Need	  of	  earlier	  diagnosis	  	  	  •  More	  personalized	  therapies	  •  ...
The Digitalization of Medicine•  Digital	  revolu$on	  in	  other	  domains	  (banking,	  insurance,	     leisure,	  gover...
Vision•  The	  convergence	  of	  medicine	  and	  the	  digital	  revolu$on	       will	  produce	  an	  informa,on	  eco...
High-­‐capacity	  Broadband	  technologies	  and	  networks                                                               ...
Collecting genome data•  Benchtop	  Ion	  Proton™	     Sequencer	  –	  designed	  to	     sequence	  the	  en$re	  human	 ...
Collec$ng	  phenome	  data	  
Collec$ng	  exposome	  data	  •  Compilation of exposures experienced over an individual   lifetime (Christopher Wild, 200...
Remote	  pa$ent	  data	  monitoring	  and	  data	  collec$on	    Environmental sensors                                    ...
Na$onal	  Broadband	  Network	  
Patient Data (sensors and imaging)                                                                                  Sensor...
Personalized	    medicine	  
Defini$on	  •  Personalized	  medicine	  uses	  an	     individuals	  gene*c	  (and	  molecular)	     profile	  and	  indivi...
Clinical	  applica$ons	  of	  genomic	  informa$on	  •  Pharmacogene$cs	  –	  Personalized	     Medicine	  Coali$on	  	  -...
Personal Genomics
Self-­‐genomics	  -­‐	  Clinical	  annota$on	  of	                   individual	  genomes	  	    •  Prof.	  Quake	  -­‐	  ...
First	  personal	  	  longitudinal	  OMICS	  profiling	  exercise	  •    Combined	  analysis	  of	  genomic,	  transcriptom...
Par$cipatory	     Health	  
Par$cipatory	  Health	  • •  From Web 1.0 – Use of internet to find health information to Web 2.0 –   web-based communitie...
Par$cipatory	  Health	                    self tracking devicesSocial web                                            games...
PCEHR	                                 	  •  Quality = patients reviewing their own records - Shared   Medical Records•  M...
DIY	  EHR-­‐	  The	  Cathedral	  and	  the	                      Bazaar   	  
Social	  media	  as	  a	  research	  tool                                                                               	 ...
Crowdsourced	  clinical	  trials                                      	  •  DIY science, Crowdsourced Health Research Stud...
•      Self	  tracking	  /	  self	  quan$fying	  /	  self	  monitoring	  •      The	  belief	  that	  gathering	  and	  an...
Pa$ent	  empowerment                                      	  Current           NBN-enabled       Driving forces: patient e...
Barriers•  New	  regulatory	  framework	  (new	  models	  of	  clinical	     trials)	  •  New	  informa$cs	  methods	  to	...
Thank	  you	  	             	                        sms@unimelb.edu.au	         www.healthinforma$cs.unimelb.edu.au	     ...
Personalised and Participatory Medicine Workshop15 may 2012
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Personalised and Participatory Medicine Workshop15 may 2012

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Personalised and Participatory Medicine Workshop

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Personalised and Participatory Medicine Workshop15 may 2012

  1. 1.  Personalised  and  Par,cipatory   Medicine     Workshop,  15  May  2012     Fernando  Mar*n-­‐Sanchez   Ins$tute  for  a  Broadband-­‐Enabled  Society   &  Melbourne  Medical  School    
  2. 2. Introduc$on  •  Broadband  can  provide  many   opportuni$es  for  the  health  sector:   –  Improving  youth  mental  health  and  aged   care  services   –  Monitoring  health  condi$ons       –  Enabling  shared  electronic  health  records   –  Telehealth    •  Convergence  with  other  technologies   towards  Digitally  Enabled  Personalized   and  Par$cipatory  Medicine  
  3. 3. Aging  Well  –  Mobile  and  broadband     technologies  for  ameliora,ng   social  isola,on  in  older  people  –  Smart  Homes  for  the  Elderly  –   recent  developments  in  Korea   Youth  Mental  Health      −  HORYZONS:  Online   Recovery  for  Youth  Onset   Psychosis  
  4. 4. Telehealth  –  Individual  Electronic  Health  Records    –  The  Telestroke  Study  –  Hap*c  Tele-­‐Rehabilita/on    –  Teleden/stry      –  Virtual  visits:  Inves*ga*ng  the  acceptability  of  webcam  consulta*ons  for  young   adults’  sexual  health  –  Wireless  broadband  monitoring  of  knee  osteoarthri/s  –  Overcoming  geographical  barriers  for  community  health  –  Interpreter  mediated  cogni*ve  assessments  using  video  conferencing  soFware  –  SeeCare  IPTV:  Personalised  Health  Literacy  Demonstrator  –  Mobile  Augmented  Reality  –  Interpreter  mediated  cogni/ve  assessments  using  video  conferencing  soFware    –  High  resolu*on  monitoring  of  atmospheric  pollutants  to  iden*fy  their  impact  on   popula*on  health  –  Overcoming  geographical  barriers  for  community  health  –  Using  video-­‐conferencing  to  pilot  an  educa*on  and  clinical  support  package  for   rural  GPs  in  Mildura  
  5. 5. Current  challenges  in  Medicine  •  Need  of  earlier  diagnosis      •  More  personalized  therapies  •  Clinical  trials  and  the  development  of  new   drugs  need  to  be  faster  and  more  effec$ve  •  Improve  disease  classifica$on  systems      •  Risk  profiling,  disease  predic$on  and   preven$on      •  Control  health  system  costs    •  Ci$zens  should  take  more  responsibility  for   the  maintenance  of  their  own  health.  
  6. 6. The Digitalization of Medicine•  Digital  revolu$on  in  other  domains  (banking,  insurance,   leisure,  government,…)  •  The  incorpora$on  of  digital  systems  in  healthcare  is  lagging   behind  other  sectors:   –  Reasons:  complexity,  privacy,  volume  of  data,  lack  of   demand   –  It  has  greatly  affected  healthcare  at  the  hospital  or   research  centre  level.     –  The  digital  revolu$on  has  not  yet  reached  medicine,  at   the  pa$ent/ci$zen  level     • BUT  THIS  IS  STARTING  TO  HAPPEN  NOW  !!!  
  7. 7. Vision•  The  convergence  of  medicine  and  the  digital  revolu$on   will  produce  an  informa,on  ecosystem  that  will  facilitate   the  advent  of  safer  and  more  efficient  preven$ve,   diagnos$c  and  therapeu$c  solu$ons.      •  The  ci$zen  will  have  access  to  her  gene,c  profile  and   clinical  record,  and  will  monitor  and  adjust  her  health   using  next  genera$on  sensors  and  social  networks  to   share  this  informa$on  with  peers,  clinicians  and   researchers.      
  8. 8. High-­‐capacity  Broadband  technologies  and  networks  •  The  availability  of  ultra-­‐high-­‐speed,  high-­‐capacity,   ubiquitous,  ‘always-­‐on’  broadband  connec$vity  will   contribute  to  the  development  of  an  integrated   digital  infrastructure  for  medicine,  reaching  the   ci,zen,  that  will  make  feasible  the  concepts  of   personalized  medicine  and  par$cipatory  health.    •  Ultra  high  speed  broadband  networks  will  be   required  to  transmit  enormous  volumes  of  data   from  pa$ents’  homes  to  health  prac$$oners  and   vice  versa  in  a  $mely  manner,  and  to  enable  the   processing  of  this  deluge  of  data.  
  9. 9. Collecting genome data•  Benchtop  Ion  Proton™   Sequencer  –  designed  to   sequence  the  en$re  human   genome  in  a  day  for  $1,000  
  10. 10. Collec$ng  phenome  data  
  11. 11. Collec$ng  exposome  data  •  Compilation of exposures experienced over an individual lifetime (Christopher Wild, 2005)•  OUTSIDE / INSIDE – Absorbed -- Industrial chemicals, combustion emissions, radiation, response to stress, physical activity levels – heat/cold, noise, food, microbiome•  Evaluating Personal Exposures •  Phones: Light meters, GPS, Accelerometer •  Senspod Monitor (Ozone, carbon monoxide, CO2, NO, Noise and UV) •  Arizona State University – Petroleum derived hydrocarbons (Benzene, Toluene)
  12. 12. Remote  pa$ent  data  monitoring  and  data  collec$on   Environmental sensors Genomic sensors Phenomic sensorsEnvironmental risk factors Biomarkers (DNA sequence,(pollution, radiation, toxic agents, …) proteins, gene expression, epigenetics Physiological, biochemical parameters (cholesterol, temperature, glucose, heart rate…) Integrated personal health record
  13. 13. Na$onal  Broadband  Network  
  14. 14. Patient Data (sensors and imaging) Sensors Genomic Phenomic Environmental Integrated Personal EHR Health Record Module 1 Health Profile GWAS Assessment Tables (weighted factors) Modelling Risks Diagnosis Personal Health Profile CDSS Health Profile Module 2 Improvement TrialbanksNetworks Risk reduction Decision matrix, protocols Follow-up Personalised Therapy Health Recommendations
  15. 15. Personalized   medicine  
  16. 16. Defini$on  •  Personalized  medicine  uses  an   individuals  gene*c  (and  molecular)   profile  and  individual  informa*on   about  environmental  exposures  to   guide  decisions  made  in  regard  to  (risk   profiling)  and  the  preven*on,   diagnosis,  and  treatment  of  disease.     (Adapted  from  F.  Collins,  Director  NIH)  
  17. 17. Clinical  applica$ons  of  genomic  informa$on  •  Pharmacogene$cs  –  Personalized   Medicine  Coali$on    -­‐  72  drugs  in   2011  •  Cys$c  fibrosis  –  successful  clinical   trial  for  a  specific  muta$on  •  Iden$fica$on  of  metabolic   diseases  
  18. 18. Personal Genomics
  19. 19. Self-­‐genomics  -­‐  Clinical  annota$on  of   individual  genomes     •  Prof.  Quake  -­‐  Stanford  -­‐    -­‐  Nature  gene$cs   paper  -­‐  $50.000,  1  week,  Helicos.  Stanford   team  -­‐     •  Clinical annotation of genome from “patient Zero” –  Drug  metabolism   –  Rare  gene$c  variants  -­‐  rare  diseases   –  Common  gene$c  variants  -­‐  Risk  of   complex  diseases  Ashley et al. The Lancet, Volume 375, Issue 9725, Pages 1525 - 1535, 1 May 2010
  20. 20. First  personal    longitudinal  OMICS  profiling  exercise  •  Combined  analysis  of  genomic,  transcriptomic,  proteomic,   metabolomic  and  immunological  profiles  from  a  single   individual  (one  of  the  authors-­‐    Prof.  Michael  Snyder),  over  a   14  month  period.  More  than  3  billion  measurements.    •  He  contracted  two  mild  viral  infec$ons  in  the  data-­‐gathering   period,  which  lem  their  molecular  signature  in  the  analyses.  •  During  one  of  these  infec$ons,  his  blood  glucose  levels  began   to  approach  those  of  a  diabetes  sufferer.  Amer  changing  his   diet  and  exercise  habits,  glucose  level  returned  to  normal.  •  This  study  shows  that  diseases  are  a  product  of  an  individual’s   gene$c  profile  as  well  as  interac$on  with  the  environment  and   that  disease  can  be  treated  based  on  molecular  informa$on.     (Chen  et  al,  Cell  148,  1293-­‐1307  March  16  2012  )  
  21. 21. Par$cipatory   Health  
  22. 22. Par$cipatory  Health  • •  From Web 1.0 – Use of internet to find health information to Web 2.0 – web-based communities and services. NHS Social Care Model (NHS)•  A survey of 1,060 U.S. adults by the PwC Health Research Institute found that a third of respondents are gravitating toward social media as a place for discussions of health care.•  Pew Internet study – 27% of US internet users had tracked health data online•  Care management, disease management, supported self-care, promoting better health à Patients empowered, informed and involved in decision making, prevention and learning
  23. 23. Par$cipatory  Health   self tracking devicesSocial web games Participatory Health mobile Internet of things sensors PCEHR
  24. 24. PCEHR    •  Quality = patients reviewing their own records - Shared Medical Records•  MyHealth@Vanderbilt – information on prescriptions is shared. Knowledge management team – consumers will have convenient e-access to their medical records and genetic profiles to social media & games•  Facebook • Lifeline – support line for suicide • Organ donor status • Blood type – app will contact the user
  25. 25. DIY  EHR-­‐  The  Cathedral  and  the   Bazaar  
  26. 26. Social  media  as  a  research  tool  •  We  are  witnessing  a  transi$on  from  research  informa$on  systems   centralized  at  hospitals  and  clinical  research  centres  to  distributed  systems   that  reach  out  to  the  residence  of  any  ci$zen  /  pa$ent  who  opts  in.    •  Clinical  Research  with  the  pa$ents,  not  on  the  pa$ents  •  Examples   –  23andMe  –  Parkinson’s  Disease  –  PLoS  Gene$cs,  2  new  gene$c   associa$ons   –  Pa$entsLikeMe  –  Nature  Biotech.  Self-­‐reported  data  from  600  pa$ents   on  the  use  of  lithium  for  Amyotrophic  Lateral  Sclerosis  (ALS)  
  27. 27. Crowdsourced  clinical  trials  •  DIY science, Crowdsourced Health Research Studies, Citizen science, Amateur Scientist, Self- Experimentation•  Patients Like Me – 125.000 members. 1000 condition- based communities –25 Papers published in PNAS, Nat Biotech, JMIR, …•  23andme – 23 and we –•  Acor, RevolutionHealth, Curetogether, Genomera, Althea Health
  28. 28. •  Self  tracking  /  self  quan$fying  /  self  monitoring  •  The  belief  that  gathering  and  analysing  data  can  help  them  improve   their  lives!  •  QS’ers    doubling  every  year.–  5524  members,  42  meetup  groups  •  Larry  Smarr–  10years  quan$fying  his  body   –  Weight  –  physical  ac$vity:  calories  burnt  (body  media)  –  Food   intake  –  Sleep  (Zeo)  –  blood  chemicals  (60  Markers)  –   cholesterol/triglycerides  /  Apo  B  /  Ω  –  6,  Ω  –  3/  C-­‐reac$ve  protein   -­‐  Ultrasound  –  (plaque  in  arteries)  –  stool  test  –  colonoscopy  –   DNA  –  Microbiome    •  Fitbit  –  Sleep  –  Movement  •  +9000  health  apps,  each  person  connected  to  140  devices,  9  billion  of   connected  devices  now,  24  billion  by  2020  •  NODE  Sensor  Environment      
  29. 29. Pa$ent  empowerment  Current NBN-enabled Driving forces: patient empowerment,networks personalized medicine, social networksEHR – Personally Citizens are able to maintain and controlElectronic Controlled EHR their own health informationHealth RecordGene-disease Personal Citizens ask for genetic analysis of theirassociation genomics DNA through the Internet and receivestudies reports on various aspects of their healthClinical trials Crowdsourced The patient voluntarily shares information clinical trials on treatments and evolution of his/her illness with other patients
  30. 30. Barriers•  New  regulatory  framework  (new  models  of  clinical   trials)  •  New  informa$cs  methods  to  compile  and  interpret  all   the  informa$on  •  Educa$on  of  pa$ents  and  health  professionals  •  Ethics,  data  security  and  confiden$ality  issues  •  Wide  availability  of  clinical  decision  support  systems  at   the  point-­‐of-­‐care  •  New  cost-­‐effec$veness  assessment  and  financial   models  of  care  •  Need  to  prove  clinical  effec$veness  before  DTC  services   are  offered.  
  31. 31. Thank  you       sms@unimelb.edu.au   www.healthinforma$cs.unimelb.edu.au   Twiuer:  @ibeshbir    

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