A knowledge based collaborative model for the rapid integration of platforms, people and processes.<br />Feb 19th 2010<br ...
The views and opinions expressed in the following PowerPoint slides are those of the individual presenter and should not b...
Introduction<br />
How we work today<br />Information and procedural silos<br />In today’sGxPlandscapewe have: <br />Many individuals, groups...
Lack of operational knowledge<br />In a silo based model, it is difficult to gain cross system, cross functional knowledge...
The Challenge<br />In todays R&D environment, our challenge is to:<br />Makebetterdrugdevelopmentdecisions<br />Accelerate...
Meeting the Challenge..<br />To meet the challenge we must break down organizational and procedural silos by:<br />Leverag...
Definition of BPM<br />Business process management (BPM) is a management approach focused on aligning all aspects of an or...
BPM technology elements<br />
Definition of Business Intelligence<br />In 1958 Hans Peter Luhn, a computer scientist at IBM used the term business intel...
Definition of BI<br />BI refers to skills, processes, technologies, applications and practices used to support decision ma...
BI Implementation<br />Top Critical Success Factors are:<br />Business driven methodology & project management<br />Clear ...
Mapping out processes – High level to detailed<br />We typically think of clinical trial organization as hierarchical<br /...
Process Maps<br />Molecule <br />Development<br />Bio-<br />Equivalence<br />Discovery<br />PROGRAM<br />IND<br />Phase I<...
Identifying milestones and KPI<br />Milestones are predefinedeventswithin a process or processes<br />Milestones are calcu...
Identifying milestones and KPIs with process maps<br />KPIs are keyoperationalindicatorswhich are calculatedusing informat...
Identifying milestones and KPIs with process maps<br />MOL101 – IND Preparation <br />Time = 4mths<br />IND<br />Started<b...
Identify data sources and integration points<br />Data sources for KPIs and Milestonescan come from:<br />Documents and do...
IntegratingProcessesthrough BPM<br />
Building an operational knowledge model<br />Dashboards - <br />roll-up, drill-down, drill-in<br />By identifyingkeymetric...
Aligning with the QMS<br />Implementingthisapproachoftenrequires changes to components of the QMS<br />Whenre-engineering ...
Recommended approach<br />Map out R&D processmaps; rememberhigh to low<br />Identifyprocesses (SOPs) and interactions for ...
The light is at the end of the tunnel<br />Drug Information Association<br />www.diahome.org<br />23<br />
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A knowledge based collaborative model for the rapid integration of platforms, people and processes.

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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.

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  • Process Engine – a robust platform for modeling and executing process-based applications, including business rulesBusiness Analytics — enable managers to identify business issues, trends, and opportunities with reports and dashboards and react accordinglyContent Management — provides a system for storing and securing electronic documents, images, and other filesCollaboration Tools — remove intra- and interdepartmental communication barriers through discussion forums, dynamic workspaces, and message boards
  • A knowledge based collaborative model for the rapid integration of platforms, people and processes.

    1. 1. A knowledge based collaborative model for the rapid integration of platforms, people and processes.<br />Feb 19th 2010<br />Paul Fenton<br />Montrium Inc.<br />
    2. 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. <br /> <br /> 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. <br />2<br />www.diahome.org<br />Drug Information Association<br />
    3. 3. Introduction<br />
    4. 4. How we work today<br />Information and procedural silos<br />In today’sGxPlandscapewe have: <br />Many individuals, groups and organizations working independently<br />Many computerized systems working independently<br />Many different department or organization specific processes<br />All generate data and information which for the most part remains dislocated and underexploited <br />This makesourworkingenvironment inefficient and costly<br />
    5. 5. Lack of operational knowledge<br />In a silo based model, it is difficult to gain cross system, cross functional knowledge<br />We spend a lot of time transcribing, reconciling and collating data <br />Often we do not have a clear picture of study progress at any one point in time, even less across programs of studies<br />We do not fully exploit operational data (generated from automated system processes) and transform it into knowledge<br />
    6. 6. The Challenge<br />In todays R&D environment, our challenge is to:<br />Makebetterdrugdevelopmentdecisions<br />Accelerate time to market<br />Increase organizational efficiencies and agility<br />Improve understanding and management of R&D processes<br />Reduce cost<br />Reduce risk<br />Improve quality<br />Improvecompliance<br />
    7. 7. Meeting the Challenge..<br />To meet the challenge we must break down organizational and procedural silos by:<br />Leveraging new technologies and work methods<br />Map out, re-engineer, automate and integrate processes<br />Leverage and establish procedural and data standards<br />Integrate computerized systems and data sources<br />Identify clear and measurable metrics and KPIs<br />Align and integrate the quality system withautomatedprocesses<br />BPM and BI can help!<br />
    8. 8. Definition of BPM<br />Business process management (BPM) is a management approach focused on aligning all aspects of an organization<br />It is a holistic management approach that promotes business effectiveness and efficiency while striving for innovation, flexibility, and integration with technology<br />Is based on continuous improvement of processes<br />Source: Wikipedia<br />
    9. 9. BPM technology elements<br />
    10. 10. Definition of Business Intelligence<br />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."<br />
    11. 11. Definition of BI<br />BI refers to skills, processes, technologies, applications and practices used to support decision making<br />BI technologies provide historical, current, and predictive views of business operations<br />BI is composed on reports, dashboards, metrics and analytical models<br />BI is capable of transforming operational and business data into information and knowledge<br />
    12. 12. BI Implementation<br />Top Critical Success Factors are:<br />Business driven methodology & project management<br />Clear vision & planning<br />Committed management support & sponsorship<br />Data management & quality issues<br />Mapping the solutions to the user requirements<br />Performance considerations of the BI system<br />Robust & extensible framework <br />Source: Naveen K Vodapalli, 2009 <br />
    13. 13. Mapping out processes – High level to detailed<br />We typically think of clinical trial organization as hierarchical<br /> Processes usually align to a particular level of hierarchy<br />Processes can be high level and then drill down<br />
    14. 14. Process Maps<br />Molecule <br />Development<br />Bio-<br />Equivalence<br />Discovery<br />PROGRAM<br />IND<br />Phase I<br />Launch<br />NDA<br />Phase II<br />Phase III<br />Pre-Clinical<br />Studies<br />API/DP<br />eCTD<br />Submission<br />Regulatory<br />Approval<br />Publishing<br />MOLECULE<br />STUDY<br />Site <br />Selection<br />Monitoring<br />Plan<br />Protocol <br />Development<br />ICF <br />Development<br />eCRF<br />Development<br />SITE<br />CDA<br />SQV<br />SIV<br />CTM<br />Ship.<br />CTA<br />
    15. 15. Identifying milestones and KPI<br />Milestones are predefinedeventswithin a process or processes<br />Milestones are calculated or non-calculated values based on one or many datapoints<br />Milestones correspond to predefinedkeyevents or values within the variouslevels of the processmaps<br />Examples of Milestoneswouldbe:<br />IND Submission (MoleculeLevel)<br />Protocol Approval (StudyLevel)<br />FPFV (Site Level)<br />
    16. 16. Identifying milestones and KPIs with process maps<br />KPIs are keyoperationalindicatorswhich are calculatedusing information fromprocesses, data and documents<br />KPIs are calculated or non-calculated values based on one or many datapoints<br />KPIscanbedrilled in to toseeunderlyingKPIs and data or rolled-up to seehigherlevelKPIs<br />Examples of KPIswouldbe:<br />Time between FPFV and DB Lock (studylevel)<br />Time between last query and DB lock (studylevel)<br />Time to queryresolution (study, site level)<br />Number of queries by status (study / site) <br />Averageprotocol IRB approval time (site)<br />
    17. 17. Identifying milestones and KPIs with process maps<br />MOL101 – IND Preparation <br />Time = 4mths<br />IND<br />Started<br />eCTD<br />Submission<br />Document<br />Authoring<br />eCTD<br />Compilation<br />Time to FPFV <br />= 6mths<br />Document <br />Publishing<br />Document<br />Review & Approval<br />Phase I <br />Initiation<br />FPFV<br />Time to FPFV <br />= 1mth<br />CDA<br />SQV<br />SIV<br />CTM<br />Ship.<br />CTA<br />IRB<br />Approval<br />FP <br />Screened<br />FP FV<br />
    18. 18. Identify data sources and integration points<br />Data sources for KPIs and Milestonescan come from:<br />Documents and document metadata<br />Procedures and procedural data (workflows)<br />Databases (EDC, CTMS, Safety etc.)<br />Project plans and manualmetrics<br />Whenthinking about data for KPIs and Milestones, itis important to identify unique data sources<br />Establishment and use of standards iskey to be able to integrate data sources and procedures<br />
    19. 19. IntegratingProcessesthrough BPM<br />
    20. 20. Building an operational knowledge model<br />Dashboards - <br />roll-up, drill-down, drill-in<br />By identifyingkeymetrics, milestones and indicatorsat all levelswe are able to develop multi-dimensionaldashboards<br />Thesedashboardsallow up to move up and down in ouroperationalknowledge<br />By adding a third dimension we are able to drill in both in terms of data but also time<br />This model enables us to pin point keyfactorswhich have positive/negative impacts on ouroperations<br />
    21. 21. Aligning with the QMS<br />Implementingthisapproachoftenrequires changes to components of the QMS<br />Whenre-engineering processestry and break them down intoclearsteps, tasks, responsabilities and delvierableelements<br />Clearlyidentify all interconnections on processmaps<br />Re-engineermanualprocessesintoautomatedprocesses<br />Finallyaligntheseelements to your BPM and collaborative environment<br />
    22. 22. Recommended approach<br />Map out R&D processmaps; rememberhigh to low<br />Identifyprocesses (SOPs) and interactions for eachlevel and step<br />Identify people and organizationswhointervene in eachprocess and step<br />Identify data sources<br />Identifykeymetrics, milestones and KPIs<br />Identifytechnologyelements<br />Define a scope for pilot project<br />Implement and improve<br />
    23. 23. The light is at the end of the tunnel<br />Drug Information Association<br />www.diahome.org<br />23<br />

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