bio-it world 2009: adjusting information flow from in-house hts to global outsourcing partners
DESCRIPTION
Adjusting Information Flow from In-house HTS to Global Outsourcing Partners Brian Bissett , Staff Scienti st, Molecular Properti es, Pfi zer This talk will describe the benefi ts and pitf alls of working with a single supplier for screening services, methods for determining if reliable data is being generated by an outsourcing partner, and various mechanisms of acti on for manipulati ng, transferring, and integrati ng data into the corporate environment from a foreign entity.TRANSCRIPT
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Adjusting Information Flow from In House HTS to
Global Outsourcing Partners.
Brian BissettPfizer Inc. Groton CT
Structural and Automation Sciences
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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 http://www.marshallsoft.com/
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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
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Consequences
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Workflow
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Global View of Groton Sample Logistics
Sample Logistics
TA Chemistry
QC & QQC (ACSL)
Liquid Storage (COE)
Local Cmpd Storage
ACSL Purification
Cambridge, WuXi,
ChemBiotech
Dry Store
TA Biology (screening)
Others – PDM
EMS Biology
SND, STL, LJ
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Compound Flow to Screens
Sample Logistics
Liquid 30 mM Stock
REMP Plate
4 mM; 2ul or 10 uL
Dry Power
Assay Ready Plates
DASH Plates
(30 or 4 mM, >2uL)
TO
SH
IPP
ING
TO SCREENS
TO
SH
IPP
ING
TO SCREENS
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The Traditional Model Structure-based design Computational Chemistry Combinatorial Chemistry
Idea
To Chemistry
Synthesis & Purification
Screening
DB
To Users
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The Brave New World Model
Ohio
China
India
Idea
Synthesis & Purification
Screening
DBTo Users
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Serv-U File Server
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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
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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.
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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.
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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.
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Loading Data - BioLoader
Web based tool for Assay Data Loading. Same tool Utilized at all sites for all screens.
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BioLoader Screen Selection
Any properly registered Screen can load data using Bioloader.
Users have access to screens based on their specific needs.
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BioLoader Main Screen
Shows Data Loaded and Data Pending to Load
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The Loading Process – User Feedback
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A Successful Data Load
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Getting Results - Research Gateway
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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.
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RGATE – Query Methods
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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.
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RGATE – Report Creation from DB
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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.
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Automated FTP File Processing
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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.
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Additional ResourcesPractical 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
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AcknowledgementsMarina Shalaeva
Scientist - Molecular Properties Group
Tatyana DoroshenkoData Manager - Therapeutic Area Scientific Information Services (TASIS)
Dr. Alex Yanovsky Associate Research Fellow - Oncology Medicinal Chemistry
Dr. Laurence PhilippeAssociate Research Fellow - Analytic and Sample Logistics
George PerkinsAssociate Research Fellow - Structural and Automation Sciences
Aimee N. KestranekAnaliza - Director of Analytical Services