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Extrac'ng	
  Clinical	
  Value	
  from	
  Next	
  Gen	
  
Sequencing	
  (NGS)	
  
Frameworks	
  for	
  the	
  Transforma'o...
A	
  Framework	
  Needed	
  to	
  Extract	
  Clinical	
  Value	
  
from	
  the	
  Overabundant	
  Data	
  from	
  NGS	
  
...
Genomic	
  Data	
  from	
  NGS	
  Requires	
  
Transforma'on	
  to	
  be	
  Used	
  Clinically	
  
Data	
  
Raw	
  sequenc...
Follow	
  the	
  WIP	
  as	
  much	
  as	
  the	
  Money	
  
•  To	
  iden'fy	
  leverage	
  |	
  pressure	
  points—prese...
There	
  are	
  Three	
  Core	
  Resources	
  and	
  Capabili'es	
  
for	
  this	
  Transforma'on	
  
©	
  2013	
  Winton	...
Molecular	
  Biology	
  Complements	
  this	
  Core	
  
©	
  2013	
  Winton	
  Gibbons	
   6	
  
Genomic	
  
sequencing	
 ...
And	
  a	
  Number	
  of	
  IT	
  Plaeorms/Algorithms	
  
Facilitate	
  the	
  Transforma'on	
  
©	
  2013	
  Winton	
  Gi...
Only	
  with	
  the	
  Integrated	
  Aspects	
  Outlined	
  will	
  
the	
  Abundance	
  of	
  NGS	
  Data	
  Contribute	
...
•  LinkedIn	
  
– hkp://www.linkedin.com/in/wintongibbons/	
  
•  Twiker	
  
– @wingibbons	
  
•  Blog	
  
– hkp://www.win...
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Extracting clinical value from next gen sequencing

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It has become cliché in the clinical environment, and genetic sequencing realm, that there is a glut of sequence data. The conundrum is how to translate or transform the overabundance of data into clinically useful knowledge. This situation has only grown more acute since the introduction of next gen sequencing.

To arrive at the clinical knowledge, there needs to be a concentric series of integrated capabilities, and the necessary capacity. The core is of course the sequencing process itself, the IT tools to process it, and the human expertise. However, the essentials in the first two aspects, sequencing and IT, need to exist, and thereby create opportunities for organizations.

As there are numerable subtleties even within the essential capabilities, a single organization may not be able to develop all under one roof. Nor may certain abilities yet exist sufficiently. However, a complete ecosystem at best, or promising potential at worst, is still required.

The attached presentation illustrates the high-level transformation frameworks for this, and the subsequent translation of data to be clinically useful.

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Transcript of "Extracting clinical value from next gen sequencing"

  1. 1. Extrac'ng  Clinical  Value  from  Next  Gen   Sequencing  (NGS)   Frameworks  for  the  Transforma'on   to  Medical  Knowledge  
  2. 2. A  Framework  Needed  to  Extract  Clinical  Value   from  the  Overabundant  Data  from  NGS   •  Since  before  the  human  genome  project  was   completed,  the  throughput  of  nucleic  acid   sequencing  has  grown  exponen'ally  over  'me,   and  resul'ng  costs  exponen'ally  decline.   •  This  situa'on  has  only  grown  more  acute  since   the  introduc'on  of  next  gen  sequencing.   •  The  conundrum  is  how  to  translate  or  transform   the  overabundance  of  genomic  data  into   clinically  useful  knowledge.   ©  2013  Winton  Gibbons   2  
  3. 3. Genomic  Data  from  NGS  Requires   Transforma'on  to  be  Used  Clinically   Data   Raw  sequence   Informa+on   Assembled  and   annotated  data   Knowledge   Informa'on   applied  to   par'cular   purpose   ©  2013  Winton  Gibbons   3  
  4. 4. Follow  the  WIP  as  much  as  the  Money   •  To  iden'fy  leverage  |  pressure  points—presen'ng  both  opportuni'es  and  problems—the  NGS   clinical  transla'on  process  should  be  viewed  as  analogous  to  a  manufacturing  plant.     •  For  opportuni'es  or  leverage  points,  follow  the  WIP  (work  in  process).  Where  there  is  too  much,   downstream  capacity  is  required,  or  a  new  “machine”  need  to  convert  the  WIP:  oen  new   soware,  but  can  be  new  instrumenta'on,  or  even  clinical  data.   •  At  any  point  in  'me,  there  will  be  over-­‐and  under  capacity  for  various  stages,  e.g.,  too  much  raw   sequence  data  |  too  few  assembled  genomes  |  fewer  clinical  databases  |  yet  fewer  transla'onally   trained  doctors  |  insufficient  integra'on  among  gene'cs,  drugs  and  regulatory.   •  Different  vendors  and  users  will  likely  be  honed  for  various  steps  in  the  process,  not  fully   integrated.  Some  may  choose  to  integrate,  but  that  is  likely  best  done  through  acquisi'on  of  the   best-­‐of-­‐breed.   •  The  balance  will  not  always  stay  the  same.  It  is  likely  there  will  yet  be  an  oversupply  (not  just   overproduc'on)  of  sequencing  capacity.  Sequencer  and  reagent  growth  might  stall.  Clinical   databases  will  catch  up  for  some  condi'ons,  and  not  for  others.  For  some  medical  special'es,  use   of  gene'cs  will  come  before  it  does  for  others.  Regulatory  and  reimbursement  will  lag.   ©  2013  Winton  Gibbons   4  
  5. 5. There  are  Three  Core  Resources  and  Capabili'es   for  this  Transforma'on   ©  2013  Winton  Gibbons   5   Sequencing   output   IT   processing   throughput   Human   exper'se  
  6. 6. Molecular  Biology  Complements  this  Core   ©  2013  Winton  Gibbons   6   Genomic   sequencing   Puta've   muta'ons   Proteins  or   epigene'cs   Func'on   Clinical   effect   Sequencing   output   IT   process ing   throug hput   Human   exper's e  
  7. 7. And  a  Number  of  IT  Plaeorms/Algorithms   Facilitate  the  Transforma'on   ©  2013  Winton  Gibbons   7   Genome   assembly   Computa'onal   comparison   and  annota'on   Visualiza'on   Experimental   planning  and   data  collec'on   Desktop   integra'on,  and   Soware  as  a   Service  (SaaC)   Genomi c   sequenc ing   Puta've   muta'o ns   Proteins   or   epigene 'cs   Func'o n   Clinical   effect   Sequencin g  output   IT   proce ssing   throu ghput   Human   exper' se  
  8. 8. Only  with  the  Integrated  Aspects  Outlined  will   the  Abundance  of  NGS  Data  Contribute  Clinically   Data   Raw  sequence   Informa+on   Assembled  and   annotated  data   Knowledge   Informa'on   applied  to   par'cular   purpose   ©  2013  Winton  Gibbons   8   •  Integrate  medical  condi'on  with   informa'on  on  gene'c  varia'on,   and  protein  func'on.   •  Provide  through  a  user-­‐friendly   query  and  visualiza'on  interface.  
  9. 9. •  LinkedIn   – hkp://www.linkedin.com/in/wintongibbons/   •  Twiker   – @wingibbons   •  Blog   – hkp://www.wingibbons.wordpress.com     ©  2013  Winton  Gibbons  
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