Research & Development
Support early diagnosis and clinical trial referrals
Real World
Predict positive therapy outcomes with greater precision
Commercial
Optimize multi-channel
marketing
AI unlocks new possibilities for healthcare
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Research & Development
IQVIA ai and machine learning
Challenge
Alzheimer's Disease has proven
difficult to treat. Early diagnosis is critical for trial success and patient health.
negative trials
in 20 years
see results
Support early diagnosis and clinical trial referrals
100
+
see chart
challenge
our solutions
results
challenge
Our Solutions
Powered by predictive analytics
and machine learning
Informed by data assets including claims, EMRs, and prescription data
Identify and predict prodromal Alzheimer’s Disease patient
hot spots
see challenge
see our solutions
•
•
Results
predictive algorithm precision
See our solutions
our solutions
results
80%
patients predicted as high risk from 72.6m
U.S. residents
223k
of identified patient
hot spots in
primary care setting
76%
Operationalized data
insights for trial
referral networks
Effects of Delay of Onset of Disease
on Prevalence of Dementia
0
.5
1
2
5
(Estimates for U.S.)
Delay
(years)
1997
2007
2017
2027
2037
2047
Year
U.S. Prevalence of AD (millions)
8
6
4
2
0
Real World
challenge
our solutions
results
IQVIA ai and machine learning
Predict positive therapy outcomes with greater precision
Results
results
See our solutions
Our Solutions
our solutions
Identify key clinical and demographic predictors of the disease with real world data from
see results
see challenge
see chart
Challenge
challenge
Predict treatment response in degenerative condition affecting the elderly.
see our solutions
Predict outcomes more precisely
No predicted benefit from
more than 10 doses
Doses
specialist
centers
40
non-identified
patients
25k
Partner with large-scale EMR vendor and treating physicians
•
Commercial
challenge
our solutions
results
IQVIA ai and machine learning
Optimize multi-channel marketing
Results
results
See our solutions
our solutions
Our Solutions
Applied customized machine learning techniques to dynamically measure HCP responsiveness
•
Combined longitudinal multi- channel marketing, prescription, and claims data
•
Generate HCP promotion sensitivity scores by channel and time
Prioritize which physicians to reach,
and the best channel to reach them
see results
see challenge
Challenge
see chart
challenge
Identify the most effective method and best channel to reach physicians
with promotions.
see our solutions
Details
Which channel should be used?
Meeting
Email
Details
Paid Search
Mobile
Alert
Direct
Mail
Dr.A
Dr.B
Dr.C
Dr.D
Dr.E
Dr.F
Direct Mail
Dr.A
Dr.B
Dr.C
Dr.D
Dr.E
Dr.F
Which customer should
be contacted?
Optimized channel synergy and investment
Identified who, when, and how to effectively promote across channels
revenue increase at no additional cost
$20M+
$
$
Reduce uncertainty
Enabling optimal dosage and treatment
could be further deployed to support physician-patient engagement in determining the best course of action
within 7 months of implementation
back
Predict treatment response in 12 months
•
Develop predictive tool for integration into EMR systems to support physician-patient engagement
•
Powered by state-of-the-art machine learning and predictive analytics
Develop predictive tool for integration into EMR systems to support physician-patient engagement
•
Predict treatment response in 12 months
•
Predictive treatment optimization tool
Predictive treatment optimization tool
•
•
•
•