1. PolyAnalyst Web Report Training
Analytical Applications in Pharma Industry
PolyAnalyst Web Report Training
Megaputer Intelligence
© 2014 Megaputer Intelligence Inc.

2. Outline Pharma Research Tasks
Run searches against relevant external data sources (PubMed, Cancer.gov, etc.)
Retrieve full text articles from different content providers
Extract information on Drugs, Illnesses, Biomarkers, Number of Patients, etc.
Discover relationships between different extracted entities

3. Downloaded Articles
Outline

4. Extracted Biomarkers
Outline

5. Total Number of Patients
Outline

6. Drug – Sponsor - Biomarker
Outline

7. Drug vs. Conditions
Outline

8. Merck Data Sources and Questions
Data Source 1: Search for articles on “Migraine” on PubMed, received during
Like to see a co-author analysis over time
Can we determine products identified and strengths and weakness?
Can we indentify the topics and sentiment of the abstract and any intelligence from the data?
Look at publication performance by journal and compare to average benchmarks for 1st author
Data Source 1: Website of  blogs for migraine
How many blogs can we capture to do a trend analysis?
How can we see who comments on blogs and who is connected together?
Can we indentify the topics and sentiment?

9. “Migraine” articles
on PubMed

10. PolyAnalyst flowchart for the project

11. Federated Search (PubMed) for Migraine

12. 4643 Migraine articles on PubMed

13. Calculate Time Prior to Publication

14. Project Results in Report Viewer

15. Publication Processing Time Deviation

16. First Author Affiliations

17. Journals the Author publishes in

18. Authors publishing many joint papers

19. Virtual Collaboration Communities

20. Co-Authors evolution by Year

21. Leading Authors (first in the list)

22. Article Publishing Trends

23. Authors found in the First Position

24. Affiliations of Leading Authors

25. Exploratory Analysis: Keyword Extraction

26. Exploratory Analysis: clusters of information

27. Defining Nervous-Psychiatric category

28. Support for MeSH, SNOMED CT and MeDRA

29. Categorization results

30. Distribution of Categorization Results

31. Drug Names extracted

32. Disease Names extracted

33. Biomarkers extracted

34. Migraine types extracted through MeSH

35. Risk Factors extracted

36. Sentiments extracted

37. Drugs tested on different Migraines

38. Correlations between key facts from text

39. Facts associated with Maxalt

40. Studies where Maxalt was effective

41. Maxalt: Decreased Headaches

42. Journals with articles on Maxalt

43. “Migraine” Blogs Analysis

44. PolyAnalyst flowchart for the project

45. Loading Messages
Point PolyAnalyst “Internet Source” to the website’s URL
Grab the starting html page and follow all the links from it, collecting every page it links to (within the domain, 4 levels deep).

46. Data Cleaning
Removed RSS feeds announcements lists (over a thousand), leaving over 41,000 pages with actual content for analysis.

47. Entity Extraction
Used Entity Extraction node to identify a list of posting users (with profiles)

48. Score Every Conversation with Participating User Names

49. Link Posters (Through Comments Pages)

50. Find and Highlight all Drugs (with synonyms), mentioned in posts

51. Identify User’s Favorite Drugs (based on participation in conversations)

52. Drill Down on Selected User’s Posts
During the interactive demonstration, we picked a group of posts and reviewed which drugs and other keywords were used, including a brief sentiment analysis.

53. Posts’ Sentiment Scoring
You can quickly identify all positive and negative parts of conversations and focus on those of highest interest to you.

54. Contacting Megaputer
Questions?