TRG's semantic technology solution can help life sciences companies aggregate and analyze their research and development data to accelerate innovation. It uses linguistic analysis to understand relationships between unstructured data from different sources and systems. This semantic intelligence allows researchers to search for relevant information more precisely and get a holistic view of data, relationships and trends to inform research directions. TRG provides deep domain expertise and claims benefits like automatic categorization and summarization to empower researchers.

1. www.tech-resource.com
FASTER R&D analysis of
go-to-market data
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TRG’S SEMANTIC
TECHNOLOGY
White Paper

2. IS YOUR R&D EMPOWERED FOR ACCELERATED
INNOVATION?
The Future of pharmaceutical and biotechnology space is Personalized
Medicine and researchers are working towards understanding of these
complex disease mechanisms, so that they can deliver right treatment to
right person.
A typical drug before going to manufacturing travels a period of 7- 10 years
through R&D division. The time to market is majorly dependent on research
and development division where they are constantly researching on new
molecules or modifying old molecules to improve their efficacy with process
of simple combination of theoretical frameworks and experimental
hypothesis and validation to combined sciences of biology/medicine,
analytical technologies, and informatics. The core vision of every
Pharmaceutical/Biotech organizations is to get their drug in market as soon
as possible and this can be achieved by reducing the time spend in the
research and development. These departments are heavily dependent on
massive amount of data. This information is present but scattered across
multiple databases and sources, both public and private wherein it’s very
difficult to complete the jig saw puzzle. Although due to the era of Web 2.0,
we are connected to lot of data and information but the catch lies in are we
getting the relevant information, that also on time?
Figure 1: Exploding Volumes of Data: Life sciences data producers such as the Whitehead Institute and the Sanger Center are
already managing many TeraBytes (TBs) of data, and require high throughput processing capabilities and 24 x 7 availability to keep
pace with the high volume of data generated from today's sequencing equipment. This quote from the Sanger Center gives and idea
of the magnitude of data that needs to be managed for life science problems.
1994 1995 1996 1997 1998 Oct
1999
Apr
2000
Nov
2001
Jan
01
2002 2003 2004 2005 2006
500TB
450TB
400TB
350TB
300TB
250TB
200TB
150TB
100TB
50TB
0
Genetic databases are estimated
to be doubling in size every six months,
more than twice as fast

3. Major Bottlenecks exists in life sciences research and development;
1. Rely on newer and innovative methods for successful transfer from
research to clinic.
2. Complex and dynamic data across the systems.
3. Data is locked inside hundreds of different information systems across
the individual disciplines /in silos
4. Data explosion of emerging Biotech laboratories and has considerably
increased the complexity and scale of data
5. Enormous volumes/heterogeneous nature of data creates a gap in the
existing computational system to infer its meaning, the dynamics of this
biological data depends on the experiment, that makes the researcher in
need of adaptable and extensible systems
With TRG, research organizations can aggregate data from disparate
systems-both within their own institutions and from partner
organizations-and use that data with agility. This aggregated access allows
researchers to address many data challenges from a single system, by
allowing data to flow freely from existing specialized locations to
destinations where it is needed for downstream analysis, and by making it
possible for outcomes and results to help define directions for upcoming
research.
Figure 2: TRG semantic service articulation
Visualization
SEMANTIC
TECHNOLOGY
Communication
Sense Engine
Integration
Mapping
Data
Navigator
Knolwledge Management
Semantic Agent
Business
Intelligence
Auto
Mail
Categorizer
Semantic
Search

4. The solution to put the bits of puzzle to picture is Semantic technology.
Semantic Technologies are designed to extend the capabilities of
information on the Web and enterprise systems to be networked in
meaningful ways. With the era of Web 3.0 coming up, TRG has realized the
importance of semantic technology and its impact to the revenue to our
Lifesciences customers. With the power of product COGITO and the
experience in product implementation, system integration, content
management and Application Maintenance & Operations, TRG with Expert
System brings semantic solutions and products to the Lifesciences
Company.
Our solution is based on semantic intelligence platform which is able to take
any kind of text or formats, after which a linguistic analysis is done which is
able to break the information and understand the meaning of each data and
the relationship with each other, giving the exact information needed by the
user with different view of analysis
Figure 3: COGITO: the power of semantic intiligence
unstructured information
e-mail
intranet
information
streams
web
mobile
content
input linguistic analysis output solutions
semantic intelligence conceptual map structured information
(documents, report, analysis)
Semantic
Search
Categorizer
Extraction
and selection
of information
Intelligence
Interpretation
of natural
language
COGITO
morfological analysis
parsing
sentence analysis
semantic analysis
Sensigrafo
Semantic Network
Concepts,
Domain Ontologies,
Geographical Places,
Companies, products, People
R
documents

5. FEATURES
More parameters to expand the meaning of a particular query which is
searched by the scientists and researchers
Relationship or mapping of query with one and others to give better and
accurate results
With Subject-Action-Object tool one can get information regarding the
history , development stage of other scientists and researchers working
on other molecules on a click
Dashboard centric information to give a holistic view of mapped
information.
Content analysis through geographic maps that can help researchers
get more structured insight over the medical data globally
TOTAL BENEFITS OF TRG SEMANTIC SOLUTION
Deep understanding of Lifesciences domain helps in capability to
perform full Disambiguation
Precision: Retrieving a high level of accurate results relevant to search
query
Recall: Retrieving a high percentage of relevant documents
Real time information search discussing about the trends and opinions
Automatic categorization
Automatic tagging of main elements
Automatic summary of article and research papers
Extracts specific relationships that exist between the concepts
BENEFITS TO USERS (SCIENTISTS/RESEARCHERS)
Aggregating Life Sciences data and their statements on the Web
Common system for referencing things across all research domains
even they exist in one of many databases
URI resources can be typed and associated with cross-community
vocabularies
Support the collective knowledge of an R&D Community
A Wiki with semantic relations
Substrate for Next Generation Discovery Tools
Flexible Integration of scientific networks

6. WHY CHOOSE TRG AS YOUR SERVICE PARTNER.
1. Pharma Business Aligned IT
Aligning business process with IT service delivery results in Process
Cycle Time Reduction and Enhanced Business Performance
Large US Pharmaceutical Company – Business Process Changes
resulting in reduced cycle time for order processing and
manufacturing lead times by 25%
2. Complex Transformational Projects
Saving 2.6 Million USD Beyond Labor Arbitrage by productivity gains
TRG Supports 90 % of ERP Apps, Human Health, Clinical & Pre
clinical IT
One of the Largest Pharma SOA Enablement Reference
3. Pharma Reference and ERP Domain Depth
TRG works with 10 of the top 15 pharmaceutical and companies
#3 SAP Integrator by scale and completeness of solution
#1 for SAP Customer Satisfaction
#1 in Remote Infrastructure Services
Global Delivery network beyond INDIA of Poland, brazil, Malaysia
and China Centers and Near SHORE in North Carolina
4. Service Innovation
Joint IP creation with SAP for Clinical Trial Supply Chain &
Manufacturing Domains
eZ Migrate & ASSET - Efficient migration & transition methodologies
5. Output/Outcome based Models
Utility Based Pricing
Efficiency accrued is passed on to the customer as cost benefit
Steady transition to step level pricing model