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How to Rapidly Configure Oracle Life Sciences Data Hub (LSH) to Support the Management of Patient Data

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Information about How to Rapidly Configure Oracle Life Sciences Data Hub (LSH) to Support...
Technology

Published on March 10, 2014

Author: BioPharmSystems

Source: slideshare.net

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PREVIOUS NEXTPREVIOUS NEXT How to Rapidly Configure Oracle Life Sciences Data Hub (LSH) to Support the Management of Patient Data September 2013 Slide 1 How to Rapidly Configure LSH to Support the Management of Patient Data September 17, 2013 Mike Grossman Vice President of Clinical Data Warehousing and Analytics BioPharm Systems

PREVIOUS NEXTPREVIOUS NEXT How to Rapidly Configure Oracle Life Sciences Data Hub (LSH) to Support the Management of Patient Data September 2013 Slide 2 Welcome & Introduction Mike Grossman Vice President of Clinical Data Warehousing and Analytics BioPharm Systems, Inc. • CDW/CDA practice lead since 2010 – Expertise in managing data for all phases and styles of clinical trials – Leads the team that implements, supports, enhances, and integrates Oracle’s Life Sciences Data Hub (LSH) and other data warehousing and analytics solutions • Extensive LSH experience – 10 years of experience designing and developing LSH at Oracle – 27 years in the industry – 5+ years of experiencing implementing LSH at client sites/in the cloud

PREVIOUS NEXTPREVIOUS NEXT How to Rapidly Configure Oracle Life Sciences Data Hub (LSH) to Support the Management of Patient Data September 2013 Slide 3 Agenda • What do we mean by managing patient data • Best practices • Data flows • Conforming data • Utilities and tools • Infrastructure • Implementation • Support • Conclusions and Q&A

PREVIOUS NEXTPREVIOUS NEXT How to Rapidly Configure Oracle Life Sciences Data Hub (LSH) to Support the Management of Patient Data September 2013 Slide 4 What do we mean by managing patient data? • Everything that occurs with clinical trials data after data capture • Includes eCRF data, central labs data, IVRx data, CRO data, legacy study data • Also can include metrics data such as CTMS data

PREVIOUS NEXTPREVIOUS NEXT How to Rapidly Configure Oracle Life Sciences Data Hub (LSH) to Support the Management of Patient Data September 2013 Slide 5 Best Practice Business Process • Conform patient data to a standard within 24 hours after data capture • Standard data review and listings available immediately after first patient first visit • Data sets available for formal analysis shortly after first patient first visit • Standard ADaM datasets available for listings, review, and analysis immediately after first patient first visit • Dynamic and cross-study analysis using tools like Spotfire supplement standard reporting and review

PREVIOUS NEXTPREVIOUS NEXT How to Rapidly Configure Oracle Life Sciences Data Hub (LSH) to Support the Management of Patient Data September 2013 Slide 6 Data Flow • Stage study specific data • Stage study specific views for cross study data • Map to conformed standard • Standard data review and reporting off of conformed study specific data • Analysis results in LSH or all analysis in LSH • Automatic pooling views • Special purpose data marts down stream from pooled views

PREVIOUS NEXTPREVIOUS NEXT How to Rapidly Configure Oracle Life Sciences Data Hub (LSH) to Support the Management of Patient Data September 2013 Slide 7 Data Flow Based on Holistic Architecture Outcomes Common Data Model Project level Conformed Data Value Added Study Data Conformed Study Data Operational Trial Metrics Inbound Data Sources Master Meta Data AES & Complaints Outcomes External Study Data LIMS/PK Central Labs CDMS/ EDC CTMS Staging Area AES & Complaints Source Specific Outcomes Data Shared Study and Project Meta Data Study Specific Data Staging Trials Management Warehouse Area Specialized Data Marts for Scientific Exploration and Mining Specialized Data Marts for Scientific Exploration and Mining Specialized Data Marts for Scientific Exploration and Mining Patient Sub Setting and Safety Warehouse Clinops Data Marts Meta Data Libraries, Version Control, Compliance Change Mgt Ad-Hoc Query Dashboards Structured Reports Analytical Tools Strategic Analysis Regulatory Reporting Data Mining Clinical Development Planning

PREVIOUS NEXTPREVIOUS NEXT How to Rapidly Configure Oracle Life Sciences Data Hub (LSH) to Support the Management of Patient Data September 2013 Slide 8 Staging Data Best Practice • Stage from EDC – Direct connect for OC/RDC – File-based or web services for RAVE, Inform and Others • Direct connect for internal systems such as LIMS, IVRS, CTMS • File-based load for systems that are not used repeatedly – Automated file load greatly reduces effort – SAS macro to load data from a SAS program allows for rapid loading of data into LSH • Study specific blinded views of the data are available for data such as LIMS data

PREVIOUS NEXTPREVIOUS NEXT How to Rapidly Configure Oracle Life Sciences Data Hub (LSH) to Support the Management of Patient Data September 2013 Slide 9 Conforming to Standard Best Practices • Mapping to a standard structure should be a specification process between data management and statistics • Programming can act as a bottleneck and should be minimized • Re-usability is key to saving time and effort • Conforming must be exportable to share with regulators and partners • Target service level of processing every active study every day

PREVIOUS NEXTPREVIOUS NEXT How to Rapidly Configure Oracle Life Sciences Data Hub (LSH) to Support the Management of Patient Data September 2013 Slide 10 Conforming Data Using a Process Approach 1 Specify meta data and mappings 2 Upload and parse for errors 3 Store under version control 4 Generate executable code and test 5 Recommend re-use of mappings (TBD) 6 Download with recommendations 7 Meta Data Reports

PREVIOUS NEXTPREVIOUS NEXT How to Rapidly Configure Oracle Life Sciences Data Hub (LSH) to Support the Management of Patient Data September 2013 Slide 11 Data Delivery and Data Review Best Practices • Automatically deliver the conformed data to statistics for on-going analysis via programming in LSH directly or via macro call via generic business area • On-going data review available with Spotfire or JReview. – Standard listings available on top of conformed data – Raw staged data always available for browsing and study specific listings • Metrics and CTMS data can be combined with patient data – LSH works with Oracle Clinical Development Analytics

PREVIOUS NEXTPREVIOUS NEXT How to Rapidly Configure Oracle Life Sciences Data Hub (LSH) to Support the Management of Patient Data September 2013 Slide 12 Example of Metrics Combined with Patient Data

PREVIOUS NEXTPREVIOUS NEXT How to Rapidly Configure Oracle Life Sciences Data Hub (LSH) to Support the Management of Patient Data September 2013 Slide 13 Why LSH? Loading STAGING CONFORM Transforming, Standards & Coding File and Data Mart Outputs SDTM ADaM SDTM+ • TFLs • Reconciliation Reports • SAS Datasets • PDF Reports • Reporting Data marts • Relational Data marts • Listings Oracle Life Sciences Hub – SCE & Validated Data Platform CODING POOLING Messages Data Sources Text Files Safety Database Connection EDC Systems xpt, sas7bat Visualisation, Reporting & Program Development Applications R JREVIEWCDA+ SASGENERIC VISUALISATION WEB BROWSER S+SPOTFIRE This slide courtesy of Oracle Corporation

PREVIOUS NEXTPREVIOUS NEXT How to Rapidly Configure Oracle Life Sciences Data Hub (LSH) to Support the Management of Patient Data September 2013 Slide 14 Utilities/Tools Required • LSH includes most of the infrastructure needed • Utilities needed to complete the picture – File Loading Utility – Study Templates – Data mapping application – Centrally Located IVRS utility – Centrally Located LIMS/Lab utility – Centrally located coding utility – Pooling Utility

PREVIOUS NEXTPREVIOUS NEXT How to Rapidly Configure Oracle Life Sciences Data Hub (LSH) to Support the Management of Patient Data September 2013 Slide 15 Example Setup of Utilities and Templates

PREVIOUS NEXTPREVIOUS NEXT How to Rapidly Configure Oracle Life Sciences Data Hub (LSH) to Support the Management of Patient Data September 2013 Slide 16 Infrastructure Required • Production environment sized for service level • Test/Validation environment • Sandbox/Development environment

PREVIOUS NEXTPREVIOUS NEXT How to Rapidly Configure Oracle Life Sciences Data Hub (LSH) to Support the Management of Patient Data September 2013 Slide 17 Diagram of Example Production Environment

PREVIOUS NEXTPREVIOUS NEXT How to Rapidly Configure Oracle Life Sciences Data Hub (LSH) to Support the Management of Patient Data September 2013 Slide 18 System Implementation Tasks • Sandbox/Dev installation • Requirements workshop • Requirements and design documents • Example configuration in Dev environment • Develop an OQ/PQ and other validation documentation • Install IQ in test environment including utilities • Execute OQ/PQ and other validation steps • Install IQ/Smoke test and of Production environment • Training • Ongoing Support and maintenance

PREVIOUS NEXTPREVIOUS NEXT How to Rapidly Configure Oracle Life Sciences Data Hub (LSH) to Support the Management of Patient Data September 2013 Slide 19 BioPharm Pre-configured Environment • Based on these best practices, BioPharm has pre- configured assets for this best practice environment – Rapid installation of LSH – Templates for requirements and design – Pre-developed utilities and configurations for • File Loading • SAS Macro based loading and extract • Data Pooling • Blinded sources – LSH integrated fully functional mapper and meta data repository – Templates for validation documents – Training classes

PREVIOUS NEXTPREVIOUS NEXT How to Rapidly Configure Oracle Life Sciences Data Hub (LSH) to Support the Management of Patient Data September 2013 Slide 20 Example of Study Data Mapper

PREVIOUS NEXTPREVIOUS NEXT How to Rapidly Configure Oracle Life Sciences Data Hub (LSH) to Support the Management of Patient Data September 2013 Slide 21 BioPharm Environments • Hosted in dedicated environments in cloud • Highly scalable • Fault tolerant configuration • LSH • Study Data Mapper • OBIEE • SAS • Informatica • JReview • Spotfire • Secure FTP • Oracle Data Management Workbench • Becomes part or your internal network

PREVIOUS NEXTPREVIOUS NEXT How to Rapidly Configure Oracle Life Sciences Data Hub (LSH) to Support the Management of Patient Data September 2013 Slide 22 Implementation Package • Sandbox Environment • Requirements and design workshop • Full system configuration • IQ/OQ/PQ • Training • Test environment and test execution • Full validation pack • Production release • Ongoing technical and application support

PREVIOUS NEXTPREVIOUS NEXT How to Rapidly Configure Oracle Life Sciences Data Hub (LSH) to Support the Management of Patient Data September 2013 Slide 23 On-going Support • Support includes both technical and application • Technical support includes service levels, backups, disaster recovery etc. • Application support includes asking questions about bugs and how to use the application itself. This can include questions about programming and setup of studies • Can act as liaison to to 3rd party software vendors such as Oracle • Telephone support and 24x7 at support.biopharm.com • Multi-lingual support available

PREVIOUS NEXTPREVIOUS NEXT How to Rapidly Configure Oracle Life Sciences Data Hub (LSH) to Support the Management of Patient Data September 2013 Slide 24 Rapid Release with Low Risk License and Pricing • For a hosted solution – Sandbox environment available within 2-4 weeks – Validated production go-live is 4-6 months • On premise solution also possible • Software licenses for LSH, Oracle, OBIEE, SAS, Spotfire, JReview, Mapper, etc. can be included as part of monthly hosting costs – Single contract – single monthly payment • Implementation available as fixed price or T&M • Hardware grows as planned and needed

PREVIOUS NEXTPREVIOUS NEXT How to Rapidly Configure Oracle Life Sciences Data Hub (LSH) to Support the Management of Patient Data September 2013 Slide 25 Conclusion • Best practice minimizes the costs and risks of managing patient data • LSH with supporting utilities enables best practice • Pre-defined mapping utility accelerates the most complex part of preparing patient data for review • BioPharm has pre built implementation templates for all aspects of implementation • Reduce risks, complexity, and time to go-live by hosting via BioPharm regulatory compliant cloud

PREVIOUS NEXTPREVIOUS NEXT How to Rapidly Configure Oracle Life Sciences Data Hub (LSH) to Support the Management of Patient Data September 2013 Slide 26 Q&A

PREVIOUS NEXTPREVIOUS NEXT How to Rapidly Configure Oracle Life Sciences Data Hub (LSH) to Support the Management of Patient Data September 2013 Slide 27 Contact Us • North America Sales Contacts: – Rod Roderick, VP of Sales, Trial Management Solutions – rroderick@biopharm.com – +1 877 654 0033 – Vicky Green, VP of Sales, Data Management Solutions – vgreen@biopharm.com – +1 877 654 0033 • Europe/Middle East/Africa Sales Contact: – Rudolf Coetzee, Director of Business Development – rcoetzee@biopharm.com – +44 (0) 1865 910200 • General Inquiries: – info@biopharm.com

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