Streamline patient stratification together with omics and sample management Find out how the solution enables research scientists and clinicians across Healthcare, Pharma and other Life Sciences organizations to create a comprehensive research platform that empowers high quality decision-making. It provides the building blocks to allow clinical researchers to capture and curate their data, to manage ontologies, and to integrate, search and visualize data from clinical, biobanks and omics data sources. In this webinar you will see how to: - improve sample management - capture Data Provenance - stratify patient populations - explore omics data in the context of clinical phenotype - facilitate a results sharing culture between departments and collaborators To view the webinar: http://www.idbs.com/en/news-events/list-of-webinars/2014/03/increase-research-efficiency-and-enable-collaboration-with-the-idbs-translational-science-solution/

1. ©2014 IDBS, Confidential
Increase research efficiency and enable
collaboration with the IDBS Translational
Science Solution
Learn how to streamline patient stratification
together with omics and sample management
Robin Munro, Ph.D.
Renata Kabiljo, Ph.D.

2. ©2014 IDBS, Confidential
All of us are on a journey to improve
our research and development
And we all face obstacles
that shape that journey

3. ©2014 IDBS, Confidential
An enabling solution
 IDBS offers flexible translational science data management with
notebook capabilities and data provenance
 Improving sample management and data is key – sample integrity for clinical
development is key to incorporating accurate genomic data in trials
 Biomarker research groups need to be more successful – groups have to be
empowered with the right information management to allow proper mining of the
data
 Clinical development is moving away from a purely biostatistics approach – now
its not just about outcomes and safety analysis, but they need to be combined with
advanced data management and analytics of biomarker and genomic data
 Information is more valuable when shared – allow control and manage the flow
of data both internally and across collaborations

4. ©2014 IDBS, Confidential
Leading to easier Collaboration
The building blocks for collaboration
 The Solution enables research scientists
and clinicians to create a comprehensive
research platform that empowers high
quality decision-making
 It provides the building blocks to allow
clinical researchers
• to capture and curate their data
• to manage ontologies
• to integrate, search and visualize data
from clinical, biobanks and omics data
sources
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5. ©2014 IDBS, Confidential
Improve cross-departmental processes & query, and enable a results sharing culture
between biomarker groups, preclinical and clinical development
Examples of high level use cases
 Support large omics, sample and clinical data management to ask relevant
translational questions
• In all cell lines treated with a compound , show if there is a correlation of IC50 and what
omics features
 Stratification of subjects on trial with associated biomarker data, Pt-Gt correlation
• How many subjects have BMI >25 and how many of these have gene expression profiles?
• Identify a new sub-population based on set of biomarkers, CNVs, etc...
 Query research data in context of clinical studies
• Which patients have mutations in marker genes identified from a pathway
 Study management for clinical, image, pharmacogenomics and biomarker data

6. ©2014 IDBS, Confidential
Jewish General Hospital
 Initial Phase across 3 disease areas with a preliminary cohort of patients
1. Q-CROQ-1 Colorectal cancer
2. Q-CROQ-3 Breast cancer
3. Pathology Study Melanoma
 All pilots cover data from different systems or CRF’s
• Patient demographics
• Medical history
• Cancer type Treatment History (e.g. Colorectal, Breast, Melanoma)
• BioSample Results
• Omics Data
• aCGH
• FLOW cytometry
• IHC (Immunohistochemistry)
• Mutation Status

7. ©2014 IDBS, Confidential
“Cross organizational collaboration within translational science is
crucial. Our patients want doctors and scientists talking and sharing
with each other and employing the IDBS solution helps build confidence
and gets us closer to that goal. The more people get together, the more
likely it is to see new things, or see old things with new minds.”
“It’s time to kick down the walls to help cut away the
research silos and collaborate with each other
transnationally”
Dr Gerald Batist
• Director of the Segal Cancer Center at the Jewish General Hospital

8. ©2014 IDBS, Confidential
Software Demonstration
Translational Science Solution
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9. ©2014 IDBS, Confidential
Demonstration
 Stratifying patient populations
 Exploring omics data in the context of clinical
phenotype
 Facilitating a results sharing culture between
departments and collaborators
 Capturing data provenance
 Sample management
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10. ©2014 IDBS, Confidential
High grade serous ovarian cancer (HGS-OvCa) patients
Dataset
 Clinical Data from TCGA – 573 patients
 Research data for majority of these patients
• various microarrays for gene expression and copy number
aberrations
• next generation sequencing data for somatic mutations
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11. ©2014 IDBS, Confidential
Increase research efficiency and enable collaboration
Summary
 Some of the challenges when running effective
Translational Science projects
 Jewish General Use Case
 Demonstration of the Solution
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