The clinical trial field is already very challenging with
researches being made over new ailments and improvements on old medications.
So, anything done to overcome these challenges could be of great help. And,
artificial intelligence (AI) is one such element, which when combined with Big
Data, holds the potential to resolve many such challenges.
The combination can increase trial efficiency through better
protocol design, patient enrolment, patient retention, etc. Anyways, sponsors
are looking for ways to accelerate timeliness and reduce costs because clinical
trials account for 40% of the entire research budget; and AI can help with such
cost-effectiveness and efficiency. This is possible with data-driven protocols
and strategies that are powered by advanced AI algorithms processing the data
collected from mobile apps, electronic records, mobile sensors, and other such
sources. Data quality is improved, while increasing patient retention and
compliance; thus allowing effective and reliable treatment more than ever
before. Obviously, newer challenges are presented with these new elements, but
on the whole, the entire process becomes cost-effective, hassle-free, and
reliable.
Even so, AI has the capability to transform clinical trials
by uncovering new therapeutic options in masses of data that can't be found by
humans. This transformation begins with protocol development, reducing or
replacing outcome assessments, and utilizing remote connected technologies that
reduce the need for patients to travel long distances for site visits.
Furthermore, masses of real world data can be included into protocol designs,
unlike in the case with traditional processes. Objective data from sensors and
mobile devices captured in real time data from individuals carrying out their
normal activities can capture more meaningful clinically relevant insights.
Such real-time real-world data with wearable devices can produce consistent and
objective evidence of actual disease states and can impact drug efficacy on
disease symptoms, unlike in the case of verbal or written evidence from
patients at clinical visits and clinic observations. With wearable devices, a
wide range of signals can be captured like heart rate, blood pressure,
activity/inactivity throughout the day, which isn't possible through human
assessment. Thus, with AI, much richer and more detailed amounts of data can be
collected!
With all of this happening remotely, patients can
comfortably be at home without having to travel long distances to the clinic
frequently. This ultimately reduces the burden on patients, lowers site costs,
and improves the quality of patient retention. In fact, patients can also send
feedback on treatment symptoms and manage medication intake, and share
information with researchers easily right from home. All of this thus affects
patient retention.
All-in-all, Artificial Intelligence when incorporated into
clinical trials can generate new insights into disease processes that can open
up new treatment opportunities. It also brings potential of personalized
medication by identifying patient responses to treatments; thus reducing the
risk of drug development by creating predictive models that are much more
powerful.
Just like Artificial Intelligence has made its mark in the
clinical research industry to help patients test and report from home,
AvignaClinical Research Institute has also innovatively developed its educational
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