>> Thank you.
This next group is led by Bruce SUNGSTROM national institute of health and allergy infectious
disease, this group focused on identifying reviewers with expertise for NIH grant applications
and contract proposals.
And the title is expert locater for grant and contract review.
Please come on up.
[Applause]
>> Good morning, everyone.
I'm AUDRY representing the team members who are Dr. SUNGSTROM, we are scientific review
officers, at the national institute of allergy infectious disease, I will tell you a little
bit what our team is doing and our prototype which is called expert locater which optimizes
peer review.
The NIH funding process is complex but let's just say the NIH is the world's largest biomedical
research funding in the world, investing over $32 billion per year.
NIH disseminates funding through rigorous scientific peer review process.
And basic how it happens is when NIH identify biomedical needs or problems, funding opportunities
are issued.
Applications were applied through grants.gov into study sections which are made up of expertise
of reviewers we call peer review.
And then NIH disseminate the funding after decision is made this particular process from
application submission to funding dissemination takes nine months given number of applications
and complexity of the funding opportunities.
The funding process at NIH is not as smooth and linear in terms of progression, it can
be viewed like a bottle where you have a diverse application pool then peer review process
which is a huge bottleneck peer review process includes identification of potential reviewer
to serve on these study sections followed by review of application.
It takes from two weeks to couple of months.
Now compounded with NIH budget cuts which result in fewer awards, fewer qualified reviewers
and more applications, these factors directly impact and affect the time and the effort
to recruit reviewers by scientific review offices such as myself and team members.
There is decrease funding research outcomes.
So SROs, we want to target or try to solve or expedite peer review stage.
So what we did was to ask a question who are affected by peer review?
And what we found was mind boggling but impressive.
Peer review affects not only review program staff at NIH, it affects grant applicants
which many are taxpayers, research institutes, centers, as well as policy makers.
This is an ecosystem of what funds -- NIH funding is all about.
This ecosystem supports the NIH mission.
What we did was we went out and actually interviewed more than 100 people within this ecosystem.
Simply by starting after them F they have a magic wand what would they wish for?
What do they think that we can do to alleviate that bottleneck, widen it a little bit, shorten
amount of time of peer review.
. After we collected all the feedback, we produced
our prototype which expedites peer review process while not sacrificing the quality
of the review.
Our solution is a semiautomated program where we -- it is a time line that links several
steps utilizing the current internal NIH database.
It is a matching algorithm that pairs the applications that come in with the qualified
reviewers of the appropriate expertise along with quantitative metrics.
What we also build in a hyperlink to information on the reviewers, the applicants, the application
all at your fingertips.
It also maximize current NIH database to expand reviewer pool.
What's very important is it has a time saving feature normally peer review process can take
weeks to couple of months, we reduce from weeks to few hours.
This substantially allow review staff to redirect the attention to other peer review processes
and attend additional application.
Clearly, reviewer identification program is starting to become popular because we found
four major companies who have a foothold in this particular market.
However it's superior for several reasons, number one, we utilize the current terminology
criteria research familiar to the NIH staffers.
The quantitative metrics is established by NIH itself.
And utilize internal NIH database constantly maintained and updated so the projected estimated
annual cost to NIH is substantially less compared to if one venture out to these outside vendors.
We started this project a year ago and we have finished the initial stages highlighted
in dark blue.
We even produce a instructional video for EXLOG user.
What we want is to adapt it to a Web-based platform and expand further tempting to all
the 24 funding institutes and centers with NIH and hopefully expand market to other HHS
agencies where peer review is a crucial part of the operation.
That's the message.
Alleviate the bottleneck of peer review, we can expand the bottleneck and widen biomedical
science and continue to progress.
Thank you for your attention.
[Applause]