Praveen Gupta, MD, Premas Life Sciences
The fast paced progresses in the field of genomics over the past quarter-century have* resulted in considerable advances in the amount of genomic data available with considerably reduced cost of genome sequencing/genotyping. The underlying costs associated with different methods and strategies for sequencing genomes is of significance as they influence the scope and scale of all genomics research projects. These projects will then translate into genomics based diagnosis and disease management. With the increasing scale of human genetics studies and the growing number of clinical applications for genome sequencing, cost of genome sequencing is an important consideration.
Since innovation in genome-sequencing technologies* and strategies will continue to advance, one can readily expect continuous lowering in the cost for human genome sequencing. The key factors to consider when assessing the 'value' associated with an estimated cost for generating a human genome sequence - in particular, the amount of the genome (whole versus exome), quality, and associated data analysis (if any) - will be expected to remain the same. With software and flowcell advances on existing population scale DNA-sequencing platforms anticipated in the coming years, the nature of the generated sequence data and the associated costs will likely continue to be dynamic. As such, continued attention will need to be paid to the way in which the costs associated with genome sequencing are calculated not just from a sequencing perspective but more holistically from collection to interpretation.
The time is not too far away when most patients entering the health-care system will have their genome sequenced before clinical assessment.
For that reason, the composition of genetic testing will be vitally transformed to focus on analysis of genomic data in the context of an individual, their immediate and long-term needs, their personal choices and their environment.
This will not be an overnight revolution, as it will be some time before emergent bioinformatics solutions for interpreting genomic data are able to straddle both high quality and low cost. Once such solutions gain wider traction, high-quality health care will become more accessible to a wider population.