Presentation given at DIA EDM meeting in Washington DC in February 2010. Presentation introduces the notions of BPM and BI for the life sciences industry.

1. A knowledge based collaborative model for the rapid integration of platforms, people and processes. Feb 19th 2010 Paul Fenton Montrium Inc.

2. The views and opinions expressed in the following PowerPoint slides are those of the individual presenter and should not be attributed to Drug Information Association, Inc. (“DIA”), its directors, officers, employees, volunteers, members, chapters, councils, Special Interest Area Communities or affiliates, or any organization with which the presenter is employed or affiliated. These PowerPoint slides are the intellectual property of the individual presenter and are protected under the copyright laws of the United States of America and other countries. Used by permission. All rights reserved. Drug Information Association, DIA and DIA logo are registered trademarks or trademarks of Drug Information Association Inc. All other trademarks are the property of their respective owners. 2 www.diahome.org Drug Information Association

3. Introduction

4. How we work today Information and procedural silos In today’sGxPlandscapewe have: Many individuals, groups and organizations working independently Many computerized systems working independently Many different department or organization specific processes All generate data and information which for the most part remains dislocated and underexploited This makesourworkingenvironment inefficient and costly

5. Lack of operational knowledge In a silo based model, it is difficult to gain cross system, cross functional knowledge We spend a lot of time transcribing, reconciling and collating data Often we do not have a clear picture of study progress at any one point in time, even less across programs of studies We do not fully exploit operational data (generated from automated system processes) and transform it into knowledge

6. The Challenge In todays R&D environment, our challenge is to: Makebetterdrugdevelopmentdecisions Accelerate time to market Increase organizational efficiencies and agility Improve understanding and management of R&D processes Reduce cost Reduce risk Improve quality Improvecompliance

7. Meeting the Challenge.. To meet the challenge we must break down organizational and procedural silos by: Leveraging new technologies and work methods Map out, re-engineer, automate and integrate processes Leverage and establish procedural and data standards Integrate computerized systems and data sources Identify clear and measurable metrics and KPIs Align and integrate the quality system withautomatedprocesses BPM and BI can help!

8. Definition of BPM Business process management (BPM) is a management approach focused on aligning all aspects of an organization It is a holistic management approach that promotes business effectiveness and efficiency while striving for innovation, flexibility, and integration with technology Is based on continuous improvement of processes Source: Wikipedia

9. BPM technology elements

10. Definition of Business Intelligence In 1958 Hans Peter Luhn, a computer scientist at IBM used the term business intelligence for the first time. He defined intelligence as: "the ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal."

11. Definition of BI BI refers to skills, processes, technologies, applications and practices used to support decision making BI technologies provide historical, current, and predictive views of business operations BI is composed on reports, dashboards, metrics and analytical models BI is capable of transforming operational and business data into information and knowledge

12. BI Implementation Top Critical Success Factors are: Business driven methodology & project management Clear vision & planning Committed management support & sponsorship Data management & quality issues Mapping the solutions to the user requirements Performance considerations of the BI system Robust & extensible framework Source: Naveen K Vodapalli, 2009

13. Mapping out processes – High level to detailed We typically think of clinical trial organization as hierarchical Processes usually align to a particular level of hierarchy Processes can be high level and then drill down

14. Process Maps Molecule Development Bio- Equivalence Discovery PROGRAM IND Phase I Launch NDA Phase II Phase III Pre-Clinical Studies API/DP eCTD Submission Regulatory Approval Publishing MOLECULE STUDY Site Selection Monitoring Plan Protocol Development ICF Development eCRF Development SITE CDA SQV SIV CTM Ship. CTA

15. Identifying milestones and KPI Milestones are predefinedeventswithin a process or processes Milestones are calculated or non-calculated values based on one or many datapoints Milestones correspond to predefinedkeyevents or values within the variouslevels of the processmaps Examples of Milestoneswouldbe: IND Submission (MoleculeLevel) Protocol Approval (StudyLevel) FPFV (Site Level)

16. Identifying milestones and KPIs with process maps KPIs are keyoperationalindicatorswhich are calculatedusing information fromprocesses, data and documents KPIs are calculated or non-calculated values based on one or many datapoints KPIscanbedrilled in to toseeunderlyingKPIs and data or rolled-up to seehigherlevelKPIs Examples of KPIswouldbe: Time between FPFV and DB Lock (studylevel) Time between last query and DB lock (studylevel) Time to queryresolution (study, site level) Number of queries by status (study / site) Averageprotocol IRB approval time (site)

17. Identifying milestones and KPIs with process maps MOL101 – IND Preparation Time = 4mths IND Started eCTD Submission Document Authoring eCTD Compilation Time to FPFV = 6mths Document Publishing Document Review & Approval Phase I Initiation FPFV Time to FPFV = 1mth CDA SQV SIV CTM Ship. CTA IRB Approval FP Screened FP FV

18. Identify data sources and integration points Data sources for KPIs and Milestonescan come from: Documents and document metadata Procedures and procedural data (workflows) Databases (EDC, CTMS, Safety etc.) Project plans and manualmetrics Whenthinking about data for KPIs and Milestones, itis important to identify unique data sources Establishment and use of standards iskey to be able to integrate data sources and procedures

19. IntegratingProcessesthrough BPM

20. Building an operational knowledge model Dashboards - roll-up, drill-down, drill-in By identifyingkeymetrics, milestones and indicatorsat all levelswe are able to develop multi-dimensionaldashboards Thesedashboardsallow up to move up and down in ouroperationalknowledge By adding a third dimension we are able to drill in both in terms of data but also time This model enables us to pin point keyfactorswhich have positive/negative impacts on ouroperations

21. Aligning with the QMS Implementingthisapproachoftenrequires changes to components of the QMS Whenre-engineering processestry and break them down intoclearsteps, tasks, responsabilities and delvierableelements Clearlyidentify all interconnections on processmaps Re-engineermanualprocessesintoautomatedprocesses Finallyaligntheseelements to your BPM and collaborative environment

22. Recommended approach Map out R&D processmaps; rememberhigh to low Identifyprocesses (SOPs) and interactions for eachlevel and step Identify people and organizationswhointervene in eachprocess and step Identify data sources Identifykeymetrics, milestones and KPIs Identifytechnologyelements Define a scope for pilot project Implement and improve

23. The light is at the end of the tunnel Drug Information Association www.diahome.org 23