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Adjusting Information Flow
  from In House HTS to
    Global Outsourcing
         Partners.


               Brian Bissett
          Pfizer Inc. Groton CT
   Structural and Automation Sciences
Overview
   HTS/DASH Work Flow
   Outsourcing Modifications
        Molecular Properties (Solubility, LogD, etc.)
        ADME Screens
   Data Transfer
        Serv U File Server
   Data Formatting
        Desktop Java J2EE Applications
   Data Uploading
        Bioloader
   Data Viewing
        RGATE (Research Gateway)
   Future FTP Application
        Excel VBA Based
        Marshallsoft FTP Component
     
Reality
   Despite dramatically increasing expenditures
    for in-house pharmaceutical research and
    development (R&D) at major drug companies,
    few internally discovered, breakthrough
    products are on the horizon.
   The pharmaceutical industry's R&D
    expenditures doubled over the past decade, but
    new molecular entity approvals plummeted by
    more than 50%. Source: Cutting Edge Information.
   As a result of the changing landscape in the
    pharmaceutical industry, there will continue to
    be considerable consolidation and restructuring
    within the industry.
    Transformational Disruption in the Pharmaceutical Industry - Jeffrey Leiden, M.D., Ph.D. Clarus
    Ventures
Consequences
Workflow
Global View of Groton Sample Logistics

                                    TA
               Dry Store         Chemistry
 Cambridge,
   WuXi,                                            ACSL
ChemBiotech                                      Purification

 SND, STL,
    LJ                                           Local Cmpd
                            Sample
                           Logistics               Storage
 QC & QQC
  (ACSL)
                                                      Liquid
                                                     Storage
      EMS                                             (COE)
     Biology
                  Others – PDM          TA Biology
                                       (screening)
Compound Flow to Screens




                                        TO SHIPPING
      Dry                           TO SCREENS
     Power
                                    DASH Plates
                                 (30 or 4 mM, >2uL)
   Liquid             Sample
                     Logistics
30 mM Stock

                                  Assay Ready
                                     Plates
   REMP Plate




                                       TO SHIPPING
4 mM; 2ul or 10 uL                  TO SCREENS
The Traditional Model
                                       Idea
   Structure-based design
   Computational Chemistry
   Combinatorial Chemistry
    To Chemistry


                          Synthesis & Purification


                                         To Users
      Screening

                        DB
The Brave New World Model
        Idea
                           Ohio

                                  China

                                          India

Synthesis & Purification
Screening



                                          To
         DB                                Users
Serv-U File Server
Serv-U Top Level Screen Specific




   The Top Level of the File Server has a Directory
    for each type of Screen that is Outsourced.
   Currently:
        LogD
        Solubility
   Future: pKa & Stability
Serv-U Screen Specific Data




   Plates = Information we Send to Analiza
   Results = Information Analiza Sends to Pfizer
   Special = Special Studies
        Special Study Files may not conform to agreed upon
         standards and may require special intervention to
         process and load.
Desktop Java Application Formats Data




   User Selects appropriate plate from drop
    down menu
   Files are then reformatted with proper
    headers and made compliant with the Pfizer
    Bioloader Application.
File Changes are Tracked and Logged




   Each Reformatted File Processed Creates a log
    file which indicates changes made and any
    errors that occurred during reprocessing.
Loading Data - BioLoader




   Web based tool for Assay Data Loading.
   Same tool Utilized at all sites for all screens.
BioLoader Screen Selection




   Any properly registered Screen can load data
    using Bioloader.
   Users have access to screens based on their
    specific needs.
BioLoader Main Screen




   Shows Data Loaded and Data Pending to Load
The Loading Process – User Feedback
A Successful Data Load
Getting Results - Research Gateway
RGATE – Select Screen(s) to Query
                          Computational
                           Screens require
                           much longer
                           computing
                           times. ACD
                           Labs, Tripos,
                           etc.
                          Multiple screens
                           and parameters
                           may be queried
                           at once.
RGATE – Query Methods
Running RGATE Query
                         Some
                          Queries
                          take hours
                          or even
                          days to
                          run.
                         Time
                          depends
                          on number
                          of CP’s to
                          be
                          returned
                          and
                          computing
                          required.
RGATE – Report Creation from DB
Automated FTP File Processing
   Processing the files that come back from
    Analiza is a very time consuming process.
   Plate Files and Result Files must first be
    matched.
   The files must then be processed to form a
    Results File which can be uploaded using the
    Bioloader Tool.
   The processed Results Files must then be
    manually uploaded to the Oracle DB using the
    Bioloader Tool.
   A log must be manually kept which records the
    last Plate and Results files that were processed,
    so the starting point is known the next time the
    process is run.
   The processed plates need to be compared
    against the plates shipped so to guard against
    the possibility that compounds were lost.
Automated FTP File Processing
What we have Accomplished
   Plate Files and Result Files must first be
    matched.
   The files must then be processed to form a
    Results File which can be uploaded using the
    Bioloader Tool.
   A log must be manually kept which records the
    last Plate and Results files that were processed,
    so the starting point is known the next time the
    process is run.
   The processed plates need to be compared
    against the plates shipped so to guard against
    the possibility that compounds were lost.
   The processed Results Files must then be
    automatically uploaded to the Oracle DB using
    the Bioloader Tool.
Additional Resources
Practical Pharmaceutical
 Laboratory Automation
   Hardcover: 464 pages
   Publisher: CRC Press (May 2003)

   ISBN: 0849318149




Automated Data Analysis with
 Excel
   Softcover: 442 Pages
   Chapman & Hall (June 2007)

   ISBN: 1-58488-885-7
Acknowledgements
Marina Shalaeva
   Scientist - Molecular Properties Group

Tatyana Doroshenko
   Data Manager - Therapeutic Area Scientific Information
   Services (TASIS)

Dr. Alex Yanovsky
   Associate Research Fellow - Oncology Medicinal Chemistry

Dr. Laurence Philippe
   Associate Research Fellow - Analytic and Sample Logistics

George Perkins
   Associate Research Fellow - Structural and Automation
   Sciences

Aimee N. Kestranek
   Analiza - Director of Analytical Services

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Bio-IT World 2009: Adjusting Information Flow from In-house HTS to Global Outsourcing Partners

  • 1. Adjusting Information Flow from In House HTS to Global Outsourcing Partners. Brian Bissett Pfizer Inc. Groton CT Structural and Automation Sciences
  • 2. Overview  HTS/DASH Work Flow  Outsourcing Modifications  Molecular Properties (Solubility, LogD, etc.)  ADME Screens  Data Transfer  Serv U File Server  Data Formatting  Desktop Java J2EE Applications  Data Uploading  Bioloader  Data Viewing  RGATE (Research Gateway)  Future FTP Application  Excel VBA Based  Marshallsoft FTP Component 
  • 3. Reality  Despite dramatically increasing expenditures for in-house pharmaceutical research and development (R&D) at major drug companies, few internally discovered, breakthrough products are on the horizon.  The pharmaceutical industry's R&D expenditures doubled over the past decade, but new molecular entity approvals plummeted by more than 50%. Source: Cutting Edge Information.  As a result of the changing landscape in the pharmaceutical industry, there will continue to be considerable consolidation and restructuring within the industry. Transformational Disruption in the Pharmaceutical Industry - Jeffrey Leiden, M.D., Ph.D. Clarus Ventures
  • 6. Global View of Groton Sample Logistics TA Dry Store Chemistry Cambridge, WuXi, ACSL ChemBiotech Purification SND, STL, LJ Local Cmpd Sample Logistics Storage QC & QQC (ACSL) Liquid Storage EMS (COE) Biology Others – PDM TA Biology (screening)
  • 7. Compound Flow to Screens TO SHIPPING Dry TO SCREENS Power DASH Plates (30 or 4 mM, >2uL) Liquid Sample Logistics 30 mM Stock Assay Ready Plates REMP Plate TO SHIPPING 4 mM; 2ul or 10 uL TO SCREENS
  • 8. The Traditional Model Idea  Structure-based design  Computational Chemistry  Combinatorial Chemistry To Chemistry Synthesis & Purification To Users Screening DB
  • 9. The Brave New World Model Idea Ohio China India Synthesis & Purification Screening To DB Users
  • 11. Serv-U Top Level Screen Specific  The Top Level of the File Server has a Directory for each type of Screen that is Outsourced.  Currently:  LogD  Solubility  Future: pKa & Stability
  • 12. Serv-U Screen Specific Data  Plates = Information we Send to Analiza  Results = Information Analiza Sends to Pfizer  Special = Special Studies  Special Study Files may not conform to agreed upon standards and may require special intervention to process and load.
  • 13. Desktop Java Application Formats Data  User Selects appropriate plate from drop down menu  Files are then reformatted with proper headers and made compliant with the Pfizer Bioloader Application.
  • 14. File Changes are Tracked and Logged  Each Reformatted File Processed Creates a log file which indicates changes made and any errors that occurred during reprocessing.
  • 15. Loading Data - BioLoader  Web based tool for Assay Data Loading.  Same tool Utilized at all sites for all screens.
  • 16. BioLoader Screen Selection  Any properly registered Screen can load data using Bioloader.  Users have access to screens based on their specific needs.
  • 17. BioLoader Main Screen  Shows Data Loaded and Data Pending to Load
  • 18. The Loading Process – User Feedback
  • 20. Getting Results - Research Gateway
  • 21. RGATE – Select Screen(s) to Query  Computational Screens require much longer computing times. ACD Labs, Tripos, etc.  Multiple screens and parameters may be queried at once.
  • 22. RGATE – Query Methods
  • 23. Running RGATE Query  Some Queries take hours or even days to run.  Time depends on number of CP’s to be returned and computing required.
  • 24. RGATE – Report Creation from DB
  • 25. Automated FTP File Processing  Processing the files that come back from Analiza is a very time consuming process.  Plate Files and Result Files must first be matched.  The files must then be processed to form a Results File which can be uploaded using the Bioloader Tool.  The processed Results Files must then be manually uploaded to the Oracle DB using the Bioloader Tool.  A log must be manually kept which records the last Plate and Results files that were processed, so the starting point is known the next time the process is run.  The processed plates need to be compared against the plates shipped so to guard against the possibility that compounds were lost.
  • 26. Automated FTP File Processing
  • 27. What we have Accomplished  Plate Files and Result Files must first be matched.  The files must then be processed to form a Results File which can be uploaded using the Bioloader Tool.  A log must be manually kept which records the last Plate and Results files that were processed, so the starting point is known the next time the process is run.  The processed plates need to be compared against the plates shipped so to guard against the possibility that compounds were lost.  The processed Results Files must then be automatically uploaded to the Oracle DB using the Bioloader Tool.
  • 28. Additional Resources Practical Pharmaceutical Laboratory Automation  Hardcover: 464 pages  Publisher: CRC Press (May 2003)  ISBN: 0849318149 Automated Data Analysis with Excel  Softcover: 442 Pages  Chapman & Hall (June 2007)  ISBN: 1-58488-885-7
  • 29. Acknowledgements Marina Shalaeva Scientist - Molecular Properties Group Tatyana Doroshenko Data Manager - Therapeutic Area Scientific Information Services (TASIS) Dr. Alex Yanovsky Associate Research Fellow - Oncology Medicinal Chemistry Dr. Laurence Philippe Associate Research Fellow - Analytic and Sample Logistics George Perkins Associate Research Fellow - Structural and Automation Sciences Aimee N. Kestranek Analiza - Director of Analytical Services