SMBE 2015: Rapid Identification of Phylogenetically Informative Data from Next-Gen Sequencing
Extracting clinical value from next gen sequencing
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Extrac’ng Clinical Value from Next Gen Sequencing (NGS) Frameworks for the Transforma’on to Medical Knowledge
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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.
Transcript of Extracting clinical value from next gen sequencing
Extrac'ng Clinical Value from Next Gen Sequencing (NGS)
Frameworks for the Transforma'on to Medical Knowledge
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
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
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: o\en new so\ware, 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
There are Three Core Resources and Capabili'es for this Transforma'on
© 2013 Winton Gibbons 5
Sequencing output
IT processing throughput
Human exper'se
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 processing
throughput
Human exper's
e
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 So\ware as a Service (SaaC)
Genomic
sequencing
Puta've muta'o
ns Proteins
or epigene'cs
Func'on
Clinical effect
Sequencing output
IT processing throughput
Human exper'se
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.
• LinkedIn – hkp://www.linkedin.com/in/wintongibbons/
• Twiker – @wingibbons
• Blog – hkp://www.wingibbons.wordpress.com
© 2013 Winton Gibbons
