From	
  the	
  Virtual	
  Human	
  to	
  a	
  	
  
‘Digital	
  Me’	
  
Nour	
  Shublaq,	
  Peter	
  Coveney	
  
Centre	
  ...
Overview	
  
•  What	
  is	
  a	
  ‘Digital	
  Me’?	
  	
  
•  Ingredients	
  
•  Some	
  challenges	
  ahead	
  and	
  ke...
A	
  ‘Digital	
  Me’:	
  Google	
  maps	
  of	
  the	
  human	
  body	
  
	
  	
  	
  	
  	
  ‘a	
  coherent	
  digital	
 ...
•  What	
  is	
  a	
  ‘Digital	
  Me’	
  ?	
  
•  Ingredients	
  
•  Some	
  challenges	
  ahead	
  and	
  key	
  to	
  
i...
Human	
  Genome	
  Sequencing	
  
Sixty years ago we barely understood
the genetic basis of heredity. Today,
next generati...
6
New	
  Sequencers	
   1 Human Genome in:
5 years (2001)
2 years (2004)
4 days (Jan 2008)
16 Hours (Oct 2008)
3 Hours (No...
Genotype-­phenotype	
  resources	
  
Molecular-­level	
  models	
  
(GWAS,	
  PPI,	
  …)	
  
Translational	
  Systems	
  B...
Use	
  Case:	
  Cancer	
  Treatment	
  	
  
8
Drug treatment
recommendation
Genome
and Transcriptome
sequencing
Tumor samp...
Consumer	
  led	
  Healthcare	
  
PaAentLikeMe	
  	
  
US-­‐based	
  social	
  networking	
  	
  
and	
  data	
  sharing	
...
MobileTech Special (Qualcomm)
Informationweek.com
RunKeeper	
  	
  
Best	
  App	
  for	
  Exercise	
  
Fooducate	
  	
  
Best	
  App	
  for	
  Healthy	
  Ea-ng	
  
Sleep	
 ...
Lose	
  It!	
  	
  
Best	
  App	
  for	
  Weight	
  
Loss	
  
ZocDoc	
  
Best	
  App	
  for	
  Finding	
  a	
  Doctor	
  
E-­‐infrastructure	
  and	
  compuAng	
  in	
  the	
  
‘cloud’	
  
Amazon and Microsoft are
providing cloud services
for d...
•  What	
  is	
  a	
  ‘Digital	
  Me’	
  ?	
  
•  Ingredients	
  
•  Some	
  challenges	
  ahead	
  and	
  key	
  to	
  
i...
Some	
  challenges	
  ahead	
  
Biological	
  challenges	
  
–  Do	
  we	
  understand	
  biology	
  and	
  
diseases	
  e...
•  Exploit	
  unprecedented	
  amounts	
  of	
  detailed	
  biological	
  data	
  being	
  
accumulated	
  for	
  individu...
Clinicians	
  of	
  Tomorrow	
  
•  With	
  the	
  rush	
  of	
  genomic	
  data	
  into	
  hospitals,	
  and	
  an	
  inc...
E-­‐infrastructure	
  &	
  ICT	
  Layers	
  
Ethical,	
  legal	
  and	
  societal	
  issues	
  
Autonomy	
   Well-­‐being	
   JusAce	
  
Scien-sts	
   Freedom	
  to	
 ...
•  What	
  is	
  a	
  ‘Digital	
  Me’	
  ?	
  
•  Ingredients	
  
•  Some	
  challenges	
  ahead	
  and	
  key	
  to	
  
i...
•  Medicine	
  today	
  is	
  a	
  driver	
  of	
  ICT	
  innova-on	
  and	
  vice	
  
versa	
  	
  
•  Advanced	
  IT	
  ...
Thank	
  you	
  for	
  your	
  aenAon!	
  
Nour	
  Shublaq	
  
University	
  College	
  London,	
  UK	
  
n.shublaq@ucl.ac...
Vph2012 20 sept12_shublaq_final
Vph2012 20 sept12_shublaq_final
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Talk entitled "from the Virtual Human to a Digital Me" presented at the Virtual Physiological Human 2012 Conference held at IET Savoy, Savoy Place, London, 18-20 September 2012.

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Vph2012 20 sept12_shublaq_final

  1. 1. From  the  Virtual  Human  to  a     ‘Digital  Me’   Nour  Shublaq,  Peter  Coveney   Centre  for  Computa-onal  Science   University  College  London,  UK   n.shublaq@ucl.ac.uk   VPH 2012 – Infrastructures: Looking Ahead, Thursday Sept 20, 2012, London
  2. 2. Overview   •  What  is  a  ‘Digital  Me’?     •  Ingredients   •  Some  challenges  ahead  and  key  to   implementa-on   •  Conclusions  
  3. 3. A  ‘Digital  Me’:  Google  maps  of  the  human  body            ‘a  coherent  digital  representa-on  that  is  used  as  an  integra-ve  framework   for  the  consolida-on  of  fundamental  and  transla-onal  Integra-ve   Biomedical  Research,  and  the  provision  to  (European)  Ci-zens  of  an   affordable  Personalised,  Predic-ve,  and  Integra-ve  Medicine’   •  Interface  to  informaAon  -­‐  having  an  efficient,  effec-ve  and  interac-ve   interface  to  the  combined,  heterogeneous  informa-on  based  on   innova-ve,  interac-ve  visualisa-on  technologies     •  Blender  of  informaAon  -­‐  the  ability  to  combine,  integrate,  fuse  informa-on   in  a  synergis-c  way,  and  to  return  such  fusion  to  the  user  visually.  This   involves  knowledge  management,  data  fusion,  image  processing,  mul--­‐ modal  visualisa-on,  and  visualisa-on  of  uncertainty     •  PaAent  avatar  -­‐  Modelling  of  physiological  and  pathological  processes  and   their  representa-on  in  a  way  that  fosters  understanding,  explora-on  and   possibly  the  produc-on  of  new  knowledge  from  pa-ent-­‐specific  and   popula-on-­‐specific  informa-on  and  knowledge                Digital  Pa)ent  Roadmap    
  4. 4. •  What  is  a  ‘Digital  Me’  ?   •  Ingredients   •  Some  challenges  ahead  and  key  to   implementa-on   •  Conclusions  
  5. 5. Human  Genome  Sequencing   Sixty years ago we barely understood the genetic basis of heredity. Today, next generation sequencing has led to fundamental shifts in our understanding of biology. No more than 25,000 protein coding genes in the human genome and not more than 100,000 previously thought. Thousands of DNA variants have now been associated with traits/diseases. Physical characteristics and disease risk are partly determined by small genetic differences Structure  Mol.  Profiles  Genomic   2 10 3000 30,000
  6. 6. 6 New  Sequencers   1 Human Genome in: 5 years (2001) 2 years (2004) 4 days (Jan 2008) 16 Hours (Oct 2008) 3 Hours (Nov 2009) 6 minutes (Now!) Cost of whole genome sequencing expected to drop to $100 in a few years
  7. 7. Genotype-­phenotype  resources   Molecular-­level  models   (GWAS,  PPI,  …)   Translational  Systems  Biology   Clinical  phenotypes   (EHR,  multi-­scale   physiological  models…)   Exposome   (drugs,  diet,  environmental   chemicals,…)   Developments   1 2 3 System-­level  models   (organ  networks,…)   Text  mining    &  semantic   web   Complex  disease   networks   Pharmacogenomics   Disease   susceptibility   Disease  gene   Oinding   Phenotypic   variation  
  8. 8. Use  Case:  Cancer  Treatment     8 Drug treatment recommendation Genome and Transcriptome sequencing Tumor sampling Tumor stem cell extraction/ expansion Modeling Drug Response The Cancer Model X X X Patient Specific Model Drug Database Mutation Database
  9. 9. Consumer  led  Healthcare   PaAentLikeMe     US-­‐based  social  networking     and  data  sharing  plaZorm  for     people  with  a  range  of  mainly     chronic  and  serious  condi-ons   -­‐  New  security  sengs     23andme     personal  genomics  company     stores  and  analyses  the     genotypes  of  thousands  of     individuals  at  over  500,000     different  posi-ons      
  10. 10. MobileTech Special (Qualcomm)
  11. 11. Informationweek.com
  12. 12. RunKeeper     Best  App  for  Exercise   Fooducate     Best  App  for  Healthy  Ea-ng   Sleep  Cycle     Best  App  for  Snoozing   Top  5  Health  Apps       The  Times    Aug  2012  
  13. 13. Lose  It!     Best  App  for  Weight   Loss   ZocDoc   Best  App  for  Finding  a  Doctor  
  14. 14. E-­‐infrastructure  and  compuAng  in  the   ‘cloud’   Amazon and Microsoft are providing cloud services for data storage and retrieval
  15. 15. •  What  is  a  ‘Digital  Me’  ?   •  Ingredients   •  Some  challenges  ahead  and  key  to   implementa-on   •  Conclusions  
  16. 16. Some  challenges  ahead   Biological  challenges   –  Do  we  understand  biology  and   diseases  enough  to  develop   reliable  computa-onal  models?   –  How  to  integrate  growing   knowledge  into  models?   ICT  Challenges   –  Data  quality   –  Data  management   –  Data  security   –  User  interfaces   Societal  challenges   –  Privacy   –  How  to  prevent  inequali-es  in   access  to  health  care?   –  Health  care  economics   –  Implementa-on  in  health  care   –  How  to  prevent  adverse   effects/misuse?  
  17. 17. •  Exploit  unprecedented  amounts  of  detailed  biological  data  being   accumulated  for  individual  people  (e.g.  at  GP  surgeries,  labs),  some  of   which  are  already  available  on  EHRs   •  Harness  the  latest  developments  in  ICT   –  large  scale  data  integra-on  and  mining,  cloud  compu-ng,  high   performance  compu-ng,  advanced  modelling  and  simula-on,     –  all  brought  together  in  a  highly  flexible  plaZorm.     •  Turn  this  informa-on  into  knowledge  that  assists  in  taking  medical,   clinical  and  lifestyle  decisions  for  the  ci-zen   •  Bridge  the  knowledge  gap  in  the  clinical/medical  community     •  Pay  acen-on  to  the  ethical,  legal  and  societal  issues     Key  to  ImplementaAon  
  18. 18. Clinicians  of  Tomorrow   •  With  the  rush  of  genomic  data  into  hospitals,  and  an  increased   adop-on  of  electronic  health  records,  the  medical/clinical   community  is  faced  with  a  knowledge  gap.     •  Match  the  knowledge  and  training  available  today  for  the  medical   and  clinical  communi-es  with  the  changing  landscape  of  medical   prac-ce  and  personalised  medicine   •  Train  clinicians  today  to  be  comfortable  and  familiar  with  the  use   of  genomic  data  in  managing  their  pa-ents.  For  example,   although  it  might  be  more  useful  for  sequencing  and  genomic   research  to  freeze  tumor  samples,  surgeons  and  pathologists  most   oden  store  -ssue  in  formalin,  which  tends  to  make  meaningful   sequencing  more  difficult.              
  19. 19. E-­‐infrastructure  &  ICT  Layers  
  20. 20. Ethical,  legal  and  societal  issues   Autonomy   Well-­‐being   JusAce   Scien-sts   Freedom  to   research   Facili-es  and   funding   Appropriate   reward  e.g.  IP   Pa-ents   Right  to  know  or   not  to  know   Improved   treatment  op-ons   Access  to   resources   Vulnerable  groups   Right  to  be  heard   Allevia-on  of   disadvantage   Equality   Professional   groups   Professional   judgment   Increased   burden?   Implica-ons  for   prac-ce   Data  breach  is  the  unauthorised  acquisi-on,  access,  use,  or  disclosure  of   protected  health  informa-on          ownership  of  data,  consent,  compliance,  what  are  the  applicable  laws  and  regula-ons    governing  the  data?  Audi-ng  in  the  cloud?  
  21. 21. •  What  is  a  ‘Digital  Me’  ?   •  Ingredients   •  Some  challenges  ahead  and  key  to   implementa-on   •  Conclusions  
  22. 22. •  Medicine  today  is  a  driver  of  ICT  innova-on  and  vice   versa     •  Advanced  IT  allows  us  to  analyse  pa-ents  all  the  way  up   from  their  own  DNA  sequences   •  A  personalised  ‘digital  Me‘  approach  is  expected  to  lead   to  improved     –  health  outcomes     –  drugs/treatments   –  disease  preven-on   –  evidence-­‐based  decision-­‐making   –  lifestyle  choices  for  global  ci-zens   Conclusions  
  23. 23. Thank  you  for  your  aenAon!   Nour  Shublaq   University  College  London,  UK   n.shublaq@ucl.ac.uk  
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