Attendees will find the context of David’s presentation to be helpful (i.e. mining the UK NHS data sources to extract meaningful information), but they will be more interested in what BT has done to implement the solution from a technical perspective. Things like; • Reducing complexity for the end user • Integrating Accelrys Enterprise Platform and BT Cloud Compute • The API’s that we used • The Grid Engines that we evaluated/used • Performance issues and resolutions (e.g. # cores versus physical memory trade-offs) • Scripting techniques (e.g. Chef and Puppet)

1. (ATS6-GS03) Cloud Enablement and
Big Health Data Analytics in the
Cloud David Brown
CTO BT Life Sciences for R&D
David.28.brown@bt.com

2. Content
• How BT are working with Accelrys to embed the Cloud
into AEP
• An example of how BT and Accelrys are using AEP to
unlock understanding from publically available data
produced by the UK National Health Service

3. • Designed for the life sciences industry
• Allows scientists to orchestrate in silico workflows to
identify new pharmaceutical targets and new drug
candidates
• Enables scientists to collaborate effectively
• Designed to enable customers to comply with the
industry’s stringent security, regulatory and compliance
requirements
• Leverages BT portfolio, such as BT One, BT Connect and BT
Assure
• BT Advise professional services, e.g. for application
migration
• Alliance with Accelrys, leading provider of scientific
applications.
BT for Life Sciences R&D

4. Geographic Availability Zones

5. On Premise / Cloud – co-existence
Virtualisation Virtualisation
OrchestrationOrchestration Integration level
Cloud Interface
One set of deployment
scripts can be use on
internal and external
resources
Internal Resource External Resource

6. Collection of
components that allows
the triggering of cloud
resources
Cloud Components

7. UKHealth data repository Open Science Project
1. To explore what information is available, both directly or in-directly related to
healthcare provision
2. To transforms small segments of information into a single research database.
a)Demographics
b)Pharmacy
c)Outcomes
d)Diagnosis codes
e)Hospital / ER utilization
f) Environment influences
g)Social Care Information
3. Form group of innovative companies to refine the ‘ask’ for data for
medical/discovery research

8. Disease State Modelling

9. DemoReal world health data demo

10. • AEP can do far more that chemistry and biology, pipeline
analytics has a major role in unlocking knowledge from
real world health data.
http://www.prnewswire.com/news-releases/scientifically-
aware-accelrys-enterprise-platform-90-breaks-new-ground-
in-big-data-management-209448061.html
Summary