New Wave
In a time of
transition in the field of medical research, focus is shifting towards big data
analytics. While the notion of information so dense it can’t be processed using
traditional applications is intimidating, a DarkDaily news
release noted “at least one data scientist” that considers it to be the future
in genomic medicine. Previous research into genomic medicine has been centered
in therapeutic determination and presymtomatic disease assessment, but the ability
to understand the immense amount of data delivered by modern technology could mark
pathologists and laboratory managers as the potential “rock stars” of the
industry.
“It’s not
about the $1,000 genome,” stated data scientist Jim Golden. “It’s about big
data generation and analytics for insight creation over the clinical course of
a patient’s journey through cancer.”
Instrumental
to the developments in $1,000 genome research, Golden “designed, built, and
programmed DNA sequencing devices” during his apprenticeship in the human genome
program and what would later become a 15 year career “working towards the
$1,000 genome.” He recently echoed the sentiments of Harvard pathologist Mark
S. Boguski, MD, PhD, FACM, however -- declaring the end of the “$1,000 genome
meme.” Both researchers agreed that, while the race to a cost-efficient genome
promoted radical advances in research, “Products such as direct-to-consumer
genomic testing have proved more educational and recreational than medicinal.”
The article later
noted that the quick decline in the cost of sequencing technology lead to what
Boguski refers to as the “third wave” of genomic research: medicinal
application. The “first wave” concentrating on single-nucleotide polymorphisms
(SNL) and therapeutic developments, while the “second wave” centering on “presymptomatic
testing for disease risk assessments.” The cost-effective access to genetic sequencing
allowed for research into “postsymtomatic genotyping” with the prospect of more
personalized treatment and care.
“This is
where genomics is likely to bring the most direct and sustained impact on
healthcare for several reasons,” commented Boguski. “Genomics technologies
enable disease diagnosis of sufficient precision to drive both cost-effective
[patient] management and better patient outcomes. Thus, they are an essential
part of the prescription for disruptive healthcare reform.”
The value of
their research remains unparalleled, but the direction of clinical laboratories
is uncertain -- with scientists like Golden noting the “need to get in front of
patients and treating physicians.” A better understanding of big data analytics
allows researchers to become proactive rather than reactive by remaining one
step ahead. Boguski remarked on the “overlooked” effects of “pathologist-directed,
licensed clinical laboratory testing” on “clinical decision-making,” testing
services accounting for only “2 percent of healthcare expenditures in the United
States” and the influence of laboratory research on the “remaining 98 percent
of costs,” offering data on “prevention, diagnosis, treatment and management of
disease” in fields across the map.