Redefining clinical trials: Adopting AI for speed, volume and diversity

Successful
clinical
studies
hinge
on
efficiently
recruiting
and
retaining
diverse
participants.
Yet,
clinical
trial
professionals
across
the
globe
grapple
with
notable
challenges
in
these
areas.
In
this
chapter
of
the

IBM
series
on
clinical
trial
innovation,
we
spotlight
key
strategies
for
boosting
recruitment
speed,
helping
to
ensure
diversity,
and
harnessing
digital
advancements.
Seamlessly
integrating
these
elements
is
essential
for
leading-edge
success
in
clinical
development.

Recruitment
difficulties
are
the
leading
reason
for
trial
terminations.
While
the
overall

clinical
trial
termination
rate
has
decreased
over
time,
low
accrual
rates
within
trials
remain
the
most
common
termination
reason.
The
public
is
often
unaware
that
they
have
the
option
to
participate
in
clinical
trials.

This
knowledge
gap
is
even
more
pronounced
among
minority
populations.
Of
people
who
enroll
in
a
clinical
trial,
the
majority
say
they
motivate
themselves
to
stay
engaged,
as
seen
in
Exhibit
1.
Industry
analysts

report
that
dropout
rates
in
phase
3
clinical
trials
can
sometimes
reach
20%
to
30%.
This
underscores
the
need
to
redefine
the
roles
of
trial
administrators
and
investigators
in
the
process.

However,
high
turnover
rates
among
clinical
trial
investigators
also
contribute
to
inefficiency,
instability
and
increased
costs.
Our
analysis
of
the
voluntarily
reported
Form
FDA
1572
BMIS
database
reveals
a
potential
lack
of
sustainability
in
the
investigator
pool,
both
in
the
United
States
(US)
and
globally
(Exhibit
2).
The
number
of
first-time
clinical
investigators
has
declined,
especially
among
non-US
based
investigators.

Lastly,
addressing
the
lack
of
demographic
diversity
in
clinical
trials
is
crucial.
In
2022,
less
than
10%
of
trial
participants
for
FDA
approval
were
Black,
fewer
than
12%
were
Asian,
under
13%
were
Hispanic,
and
women
constituted
less
than
50%
(Exhibit
3),
not
reflective
of
the
current
US
population.
Recognizing
this
gap,
regulators
emphasize
the
importance
of
greater
diversity.

For
instance,
the
FDA
released
guidance
in
November
2020
titled,
“Enhancing
the
diversity
of
clinical
trial
populations.”
In
April
2022,
they
issued
another
draft
guideline,
“Diversity
plans
to
improve
enrollment
of
participants
from
underrepresented
racial
and
ethnic
populations
in
clinical
trials:
Guidance
for
industry,”
aiming
to
provide
recommendations
for
sponsors
to
increase
enrollment
of
underrepresented
populations.

5
barriers
to
efficient
patient
recruitment
and
retention

There
are
several
key
factors
contributing
to
the
challenges
of
inadequate
patient
volume
and
sluggish
recruitment
speed
in
clinical
trials:

1. 
   Complex
   trial
   protocols:
   Delays
   often
   stem
   from
   intricate
   or
   unrealistic
   trial
   protocols.
   It’s
   crucial
   to
   evaluate
   the
   feasibility
   of
   trials
   and
   refine
   protocols
   using
   evidence-based
   strategies.
2. 
   Barriers
   to
   patient
   accessibility:
   Numerous
   challenges
   like
   geographical
   constraints,
   transportation
   issues,
   scarce
   trial
   site
   availability
   and
   physical
   disabilities
   restrict
   potential
   participants
   from
   accessing
   trials.
3. 
   Patient
   pool
   expansion
   hurdles:
   Despite
   efforts
   to
   broaden
   participant
   inclusion,
   clinical
   trials
   still
   face
   hurdles
   in
   identifying
   and
   engaging
   new
   patient
   demographics,
   especially
   underrepresented
   groups.
4. 
   Ineffective
   outreach:
   Clinical
   trial
   marketing
   efforts
   sometimes
   miss
   the
   mark.
   Lack
   of
   awareness
   and
   trust
   among
   potential
   participants
   underscores
   the
   need
   for
   enhanced
   communication
   and
   trust-building
   strategies.
5. 
   Site
   underperformance:
   Many
   clinical
   trials
   face
   interruptions
   due
   to
   suboptimal
   performance
   at
   trial
   sites.
   Predicting
   site
   performance,
   spotting
   underperforming
   sites
   and
   formulating
   timely
   interventions
   are
   essential.

5
moves
to
boost
recruitment
speed,
patient
volume
and
diversity

1.
Optimize
protocols
using
historical
and
synthetic
data

Complex
and
stringent
protocols
are
notorious
for
delaying
clinical
trials
and
eroding
patient
engagement.
Ensuring
early
assumptions
resonate
with
real-world
execution
is
paramount.
Enter
the
age
of
data-driven
protocol
assessment:
using
benchmarking
tools
and
predictive
modeling
to
gauge
protocol
intricacies
and
forecast
eligible
patient
numbers,
which
then
inform
protocol
adjustments.

Diving
deep
into
historical
trial
data
with
a
protocol
complexity
rating
also
reveals
golden
insights,
especially
around
patient-centric
elements.
Key
facets
to
spotlight
in
a
protocol’s
design
include
the
investigational
product’s
nature,
study
design,
endpoint
definition,
eligibility
criteria,
administrative
burden,
the
presence
of
redundant
processes,
and
the
time
that
a
patient
would
need
to
invest
to
participate.
Grasping
these
dimensions
sharpens
the
recruitment
lens.
Refining
trial
protocols
isn’t
a
once-off;
it’s
an
evolving,
multidisciplinary
quest,
enriched
by
lessons
from
the
past
to
shape
future
(more
effective)
trial
designs.

Learning
from
historical
protocol
data
and
using
synthetically
generated
scenario
events
to
optimize
inclusion
and
exclusion
criteria
can
be
powerful
for
achieving
efficient
trial
design.
By
fine-tuning
these
criteria,
protocols
can
help
attract
a
targeted
and
more
relevant
patient
group,
speeding
up
recruitment.

When
patients
align
with
the
inclusion
criteria
more
accurately,
their
willingness
to
enroll
increases.
The

FDA’s
2020
guidance
emphasized
expanding
eligibility
criteria
and
reducing
unnecessary
exclusions.
Broader
eligibility
criteria
not
only
streamline
recruitment
but
also
promote
greater
diversity,
helping
to
ensure
a
more
comprehensive
and
inclusive
clinical
trial.

The
latest
developments
in
large
language
models
(LLMs)
have
the
potential
to
significantly
expedite
protocol
design
processes.
The
current,
labor-intensive
manual
approach
can
compromise
the
timeliness,
accuracy
and
validity
of
results.
LLMs
demonstrate
a
superior
understanding
of
the
semantic
relationships
between
entities
within
inclusion
and
exclusion
criteria.
They
also
possess
query
generation
capabilities
that
can
automate
the
process
of
identifying
matching
patients
with
trials,
expediting
the
trial
start-up
process.

Additionally,
generative
adversarial
networks
(GANs)
can
be
used
to
simulate
real
recruitment
scenarios,
further
optimizing
protocol
design.
These
technological
advancements
promise
substantial
improvements
in
protocol
design,
ultimately
boosting
patient
enrollment.

2.
Embrace
decentralized
approaches
for
expanded
reach
and
efficiency

Decentralized
clinical
trials
(DCTs)
are
gaining
traction
for
their
prowess
in
dismantling
traditional
hurdles
in
patient
participation
in
clinical
research.
By
removing
geographical
limitations,
increasing
accessibility
and
broadening
the
participant
base,
DCTs
not
only
improve
recruitment
and
retention
but
also
foster
greater
diversity,
welcoming
participants
from
underserved
communities.

The
FDA,
in
its
May
2023
draft
guidance,
backed
the
adoption
of

DCTs
across
drugs,
biologics
and
medical
devices,
highlighting
their
merits
such
as
enhanced
patient
convenience,
diminished
caregiver
burden,
broader
access
to
varied
demographics,
amplified
trial
productivity,
and
support
for
research
on
rare
or
mobility-restricted
patient
groups.

Integral
to
DCTs
are

digital
health
technologies
and
software.
The
rise
in
the
deployment
of
electronic
patient-reported
outcomes
(ePROs),
electronic
clinical
outcome
assessments
(eCOAs),
and
electronic
informed
consent
(eConsent)
from
2020
to
2021,
primarily
driven
by
contract
research
organizations
underscores
this
shift.

Incorporating
telehealth,
real-time
monitoring
via
devices
such
as
activity
trackers,
blood
pressure
monitors,
and
other
digital
tools
is
now
commonplace
across
many
therapeutic
areas.
Augmented
reality
(AR)
and
virtual
reality
(VR)
devices
are
increasingly
playing
a
role
and
can
be
integrated
into
DCTs.
The
swift
progression
of
these
technologies
is
revolutionizing
clinical
trial
paradigms.

Digital
health
technologies
and
software
do
more
than
just
enhance
accessibility
and
efficiency
in
clinical
trials.
They
also
pave
the
way
into
the
realm
of
digital
behavior
data.
This
vast
data
set
can
provide
insights
into
patient
behaviors.
In
some
instances,
one

wearable
device
can
collect
120
million
data
points
per
day
for
each
patient.
Access
to
such
a
massive
volume
of
daily
behavior
data
provides
a
comprehensive
understanding
of
each
patient,
promoting
personalized
engagement.

This
pivot
towards
patient-centric
care
bolsters
clinical
trial
patient
recruitment
and
retention.
Moreover,
by
transitioning
away
from
the
traditional
site-centric
model,
clinical
trials
can
tap
into
nationwide
data,
pinpointing
underrepresented
populations
and
thus
encouraging
greater
diversity
within
clinical
trial
cohorts.

3.
Partner
with
primary
care:
A
goldmine
for
patient
recruitment

Forging
alliances
with
community-based
primary
care
physicians
can
dramatically
enhance
clinical
trial
participation.
Given
their
longstanding
patient
relationships
and
in-depth
understanding
of
patient
history,
primary
care
providers
offer
a
doorway
to
a
vast,
diverse
reservoir
of
potential
trial
participants.
The
bond
of
trust
between
patients
and
their
primary
care
team
cannot
be
understated.

A
nod
from
a
trusted
doctor
can
greatly
sway
a
patient’s
decision
to
participate
in
a
trial,
significantly
boosting
enrollment
figures.
Engaging
the
primary
care
team
not
only
enhances
recruitment
but
also
elevates
the
overall
quality
of
trials.

Primary
care
doctors
have
access
to
vast
amounts
of
patient
health
and
medical
data,
including
both
structured
and
unstructured
information,
as
well
as
medical
images
and
videos.
Machine
learning
and
deep
neural
network
models
can
effectively
analyze
this
data
to
identify
patterns,
correlations
and
relationships,
which
is
particularly
useful
for
understanding
a
patient’s
unique
profile.

Computer
vision
models,
such
as
convolutional
neural
network
models,
can
assist
doctors
in
detecting
and
classifying
diseases
in
2D
and
3D
medical
images.
Recently
developed
computer
vision
foundation
models
have
significantly
improved
the
accuracy
of
image
classification
tasks.

The
amalgamation
of
artificial
intelligence
(AI)
with
primary
care
offers
significant
advantages
in
the
realm
of
clinical
trials.
By
deriving
insights
from
diverse
patient
data
formats,
primary
care
doctors
can
achieve
a
more
profound
understanding
of
patient
profiles.
Such
medical
insights
can
be
instrumental
in
refining
trial
protocols
to
align
more
closely
with
genuine
patient
experiences
and
help
ensure
continual
oversight
regarding
patient
safety.
When
patients
engage
in
trials
under
the
continual
care
of
their
physician,
their
likelihood
of
sustained
involvement
increases,
consequently
reducing
attrition
rates.

4.
Refine
marketing
tactics
to
elevate
awareness
and
foster
trust

Based
on
data
from
the

2020
Health
Information
National
Trends
Survey,
41.3%
of
the
3772
surveyed
US
adults
reported
not
knowing
about
clinical
trials.
Elevating
this
awareness
demands
a
targeted
marketing
thrust,
using
tools
like
social
media
promotion,
engaging
with
key
opinion
leaders,
and
impactful
campaigns
to
bridge
the
gap
with
prospective
patients.

Studies
over
the
past
10
years
underscore
the
profound
role
of
trust
in
determining
clinical
research
participation,
especially
among
underrepresented
groups.
A
pivotal
insight
reveals
that
trust,
or
the
lack
thereof,
is
a
primary
determinant
of
participation.

Prevailing
trust-related
apprehensions
encompass
fears
of
mistreatment,
exploitation
and
unintended
consequences.

These
3
tactics
have
proven
to
be
effective:

• 
  AI-powered
  social
  media
  advertising:
  Enhance
  the
  effectiveness
  of
  social
  media
  outreach
  for
  clinical
  trial
  promotions
  by
  employing
  AI
  algorithms
  on
  platforms
  such
  as
  Facebook,
  Instagram
  and
  Twitter.
  These
  algorithms
  can
  help
  curate
  highly
  personalized
  advertisements
  and
  content
  tailored
  to
  the
  desired
  audience.
  Through
  in-depth
  AI
  analysis
  of
  user
  behaviors
  and
  patterns,
  promotional
  messages
  can
  be
  fine-tuned
  to
  resonate
  with
  specific
  age
  groups,
  geographic
  locations
  and
  health
  interests,
  amplifying
  the
  relevancy
  and
  impact
  of
  the
  outreach.
  By
  harnessing
  these
  AI
  capabilities,
  clinical
  trial
  promotions
  on
  social
  media
  can
  precisely
  target
  the
  right
  audience,
  delivering
  the
  appropriate
  message
  at
  the
  optimal
  moment.
  This
  strategic
  approach
  not
  only
  elevates
  awareness
  but
  also
  fosters
  a
  sense
  of
  community
  within
  the
  target
  audience,
  heightening
  engagement
  and
  the
  likelihood
  of
  participation
  in
  the
  clinical
  trial.
• 
  Engage
  with
  healthcare
  influencers
  and
  advocacy
  groups:
  Forge
  partnerships
  with
  trusted
  healthcare
  influencers
  and
  patient
  advocacy
  entities.
  Their
  expansive
  reach
  and
  credibility
  in
  patient
  circles
  make
  them
  invaluable
  allies.
  By
  collaborating,
  their
  endorsement
  can
  effectively
  expand
  the
  message
  reach
  and
  engagement
  levels.
• 
  Targeted
  campaigns
  at
  recruitment
  locations:
  Execute
  campaigns
  that
  are
  precisely
  calibrated
  for
  individual
  recruitment
  sites
  and
  their
  associated
  communities.
  Such
  specificity
  helps
  ensure
  that
  the
  outreach
  resonates
  with
  the
  unique
  attributes
  of
  each
  site
  or
  community,
  capturing
  the
  attention
  of
  potential
  participants.

A
sharp,
tailored
marketing
approach
elevates
clinical
trial
visibility.
Moreover,
it’s
crucial
to
address
and
build
the
trust
factor,
as
it
plays
an
essential
role
in
influencing
participation
decisions.
The
strategies
listed
are
instrumental
in
widening
awareness
and
fostering
trust
among
potential
participants.

5.
Streamline
site
performance
and
enrollment
with
AI

Integrating
AI-enabled
capabilities
in
biopharma
operations
transforms
clinical
trial
site
selection,
promotes
scalable
AI
expertise
and
helps
ensure
cost-efficiency.
AI
algorithms
consistently
outperform
traditional
methods
by
analyzing
intricate
recruitment
data,
helping
to
ensure
precise
forecasting
for
study,
indication
and
country-specific
enrollments.
By
accurately
predicting
enrollment
rates,
AI
has
the
potential
to
minimize
financial
risks,
refine
enrollment
strategies
and
support
budgeting
to
preclude
potential
setbacks
and
delays.

Moreover,
gaining
instantaneous
insights
into
site
performance
keeps
stakeholders
informed
about
enrollment
dynamics,
quickly
identifies
potential
bottlenecks
and
paves
the
way
for
agile
decision-making
and
necessary
adjustments.
The
AI
automation
enables
real-time
site
performance
tracking,
sends
prompt
alerts
and
helps
ensure
streamlined
reporting.

Additionally,
the
next
best
action
mechanisms
have
the
potential
to
provide
real-time
recommendations
on
the
most
impactful
measures
to
enhance
site
performance.
This
agility
helps
to
ensure
uninterrupted
trials,
reduces
disruptions
and
empowers
stakeholders
to
adeptly
navigate
unforeseen
challenges.

Embracing
AI
technologies
strategically

In
the
intricate
landscape
of
clinical
trials,
the
dual
challenges
of
recruitment
and
retention
persist,
often
becoming
significant
roadblocks
to
pharmaceutical
progress.
However,
with
the
strategic
embrace
of
AI
technologies,
we
can
collectively
reshape
this
narrative.
IBM
is
at
the
forefront
of
adopting
AI
for
the
pharmaceutical
business,
showcasing
our
commitment
to
refining
this
domain.

Through
tailored
protocol
designs,
decentralized
trial
models,
enriched
primary
care
collaborations,
strategic
marketing
endeavors
and
the
powerful
precision
of
predictive
engines,
we
can
surge
past
these
barriers.

The
quest
for
faster,
diverse
and
robust
clinical
trials
is
not
just
an
aspiration,
it’s
an
achievable
reality.
Clinical
professionals
globally
have
the
tools
and
insights
and
now
is
the
time
to
wield
them
with
intent.
For
those
ready
to
revolutionize
the
world
of
research
and
development,
remember
that
innovation
is
not
just
about
technology;
it’s
about
harnessing
every
available
resource
to
usher
in
a
new
era
of
clinical
excellence.

Transform
pharmaceutical
business
with
data
and
AI