1) The document discusses gathering unstructured data from online sources like social media and patient registries and storing it in an Enterprise Data Hub. 2) An analytics engine is used to analyze the data, including mining text and determining keyword frequencies, and to analyze sentiments of key opinion leaders. 3) The results of the sentiment analysis are visualized using Incedo's sentiment analysis framework to provide insights into categories like drug performance, efficacy and safety issues.

1. INPUT – DATA SOURCES
GATHERING UNSTRUCTURED DATA FROM ONLINE SOURCES
• Structure and store data
in Enterprise Data Hub
• Crawl online sources
for data
• Use pre-defined search
criteria
Social Media Biomedical & Pa ent Registry
PROCESSING – ANALYTICS ENGINE
• Mining text using data pre-processing and determining frequency of keywords
ANALYSING DATA FOR KOL SENTIMENTS
1250
mentions
885
mentions
4320
mentions
2570
tweets
Positive
Neutral
Negative
41%
28%
31% 0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
42%
25%
20%
9%
6%
VISUALIZATION
USING INCEDO’S
SENTIMENT ANALYSIS
FRAMEWORK FOR KOL INSIGHTS
Classifica on of data pa erns
into sen ments
Generate broad data
insights
Derive insights by
categories
Enterprise Data Hub
dose
feelingpharmacy
acetaminophen swelling great
severe
therapy
fever
redness
pain
response
pregnancydrug
pa ent
APAPmedicine
headache oral
days
paracetamol
Drug
Performance
Efficacy
/Safety
Add-on
TreatmentIssues
Payer
(1475)
(3300)
(1350)
(920)
(430)(1230)
(1915)
Insurance
(670)
Interac ve UI for
Deeper Insights
Word Cloud of InsightsHeat Map
1000
No of Tweets
- 5000
> 5000
100 - 1000
Paracetamol
Program
Feedback
Vomi ng
Nausea
(1800)
Side Effects
(5200)
(13,305)
www.incedoinc.com/lifesciences | rachel@incedoinc.com
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