1. Innovative Activities @ Novartis Knowledge Center
Innovative Novartis Knowledge Center -- Create and deliver value beyond traditional information delivery
Richard Cai
Competitive Intelligence Manager
Novartis Knowledge Center
Philadelphia, June 2016

2. Topics
Innovations to add value beyond traditional information delivery at Novartis Knowledge Center
Innovative Alert Sharing
Text Mining (highlighted later)
Expert Identification
Social Network Analysis
...
| Presentation Title | Presenter Name | Date | Subject | Business Use Only

3. Novartis Knowledge Center (NKC) Overview
NKC is THE information service provider for Novartis
Who we support
What we do
General support
Resource/vendor management
Document delivery
Training
Special services
| Presentation Title | Presenter Name | Date | Subject | Business Use Only

4. New environment, new roles
Visualization
Search
Sources
Analysis
Enabling scientists to reach their full potential by allowing them to manage and interpret more of the information made readily available to them
Advising individuals and teams on the best resources for their current needs and enabling them to get the most from those resources
Information Consultant
Consulting clients who have special requests with detailed analysis and insights
Traditional Search (AND/OR/NEAR/...)
| Presentation Title | Presenter Name | Date | Subject | Business Use Only

5. Going beyond traditional information delivery @ NKC
Text Mining
AlertMe
Expert ID /
Doc Tagging
NetWorking
| Presentation Title | Presenter Name | Date | Subject | Business Use Only

6. Current and Future View
Expertise Location
Network Analysis
Community/Social Media
Automated Workflow
User Customization
Integration of Tools /Outputs
Note: image free to use /
| Presentation Title | Presenter Name | Date | Subject | Business Use Only

7. Goals and Strategies of a Pilot
Goals and Strategies of a Pilot -- can we facilitate compound repurposing
All NVS Past &
Present Targets
(regardless of
indications)
New Relationships
Retinal
Diseases
Medline Full (prev. 5 yr)
Linguamatics Search:
NVS Targets – relationship – Retinal Diseases
Medline, Weekly Updates
Genes related to disease
Doc
Calculate occurrences w/in the prev. 5 yrs
without gene match in MESH, with long disease names
with NVS targets in MESH
Genes ranked by occurrences
| Presentation Title | Presenter Name | Date | Subject | Business Use Only

8. Statistics Users normally go directly to abstracts, skipping the gene
Total hits 1241
“New” rel. hits* 145
Tech. wrong hits** 63
# “New” rel. hits
# Wrong hits
Average around 4.5 hits/wk
Among wrong hits:
All with misidentified genes
Four also with misidentified diseases wk
Users normally go directly to abstracts, skipping the gene
Users estimate that 25% of the time they find the papers interesting enough to download the full articles
Wrong genes not necessarily lead to non-relevant papers. This is probably because we do a good job getting the diseases right.
*: “New” rel. hits: hits that reveal relationships that have not been published or only once in the past 5 years.
**: Wrong hits: hits with misidentified genes or diseases. These are judged technically, not scientifically.
| Presentation Title | Presenter Name | Date | Subject | Business Use Only

9. Some Thoughts Can search with large #s of terms, including synonyms
Can customize complex query structures
Works well with structured data
Not a general tool
Requires expertise and has a relatively steep learning curve
Depends on Linguamatics for indexing
| Presentation Title | Presenter Name | Date | Subject | Business Use Only

10. More Thoughts Quality of the dictionaries Flexibility of the tools
Get it right (from pure technology perspective) vs Get it right (from customer’s need perspective)
| Presentation Title | Presenter Name | Date | Subject | Business Use Only