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An Open Source Reporting System for Life Sciences

Magnus Mengelbier Director. An Open Source Reporting System for Life Sciences. Topics. Introduction Traditional process Library Analysis Reporting Connections Summary. Listings. Derived. Tables. Graphs. Source. Listings. SDTMs. ADaMs. Tables. Graphs. Define. Tradition.

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An Open Source Reporting System for Life Sciences

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  1. Magnus Mengelbier Director An Open Source Reporting System for Life Sciences

  2. Topics • Introduction • Traditional process • Library • Analysis • Reporting • Connections • Summary

  3. Listings Derived Tables Graphs Source Listings SDTMs ADaMs Tables Graphs Define Tradition Source

  4. Specifications Templates Shells Data Sets Tables Listings Define SAP Programs Shells Data Sets Data Sets SAP Templates and Specifications

  5. Templates et al

  6. SAP Library Library Specifications Programs Shell Data Sets Tables Listings Define TLGs Data Sets Data Sets

  7. Organizing Content • Directory Trees • No restriction on the number of levels • No restriction on naming conventions • Contexts • Aware of parent directory • Contexts have to be consistent within a directory tree • Directory tree can be your departmental drive or network share

  8. Default Defintions • Data Sets • Tables • Listings • Graphs

  9. Definitions and Inheritance • Types of definition controlled for each level • Definitions can be inherited from parent to child levels

  10. A Specification is just a set of links to content in the Library All Definitions have to be in the Library Specification Specifications Library

  11. A Comparison of Defintions

  12. Repository Data Sets Tables Listings Graphs Simple Meta-Data Engine • Model – View – Controller (MVC) design pattern • Model – Meta-data • View – Graphical and programming interface • Controller – ”Administrator” of the meta-data • Very primitive and flexible meta-data engine

  13. Repository - Definitions • Defintions • Type, e.g Data Set, Table, etc. • Identified by Type and Name • References and associations to other meta-data items • Look-up • Ordered list • Versions • Increment • Construct for a unique reference to variations of the same item • More than one version is selectable • Future plans include major/minor versions

  14. Sequence Reference 1 NAME 2 SEX Collections 3 AGE 4 HEIGH 5 WEIGHT Repository – Data Set

  15. Repository – Table (1)

  16. Repository – Table (2)

  17. N • MEAN_SD • MEDIAN • MIN-MAX • MEAN • SD • MIN • MAX Repository – Table (3) • N • MEAN_SD • MEDIAN • MIN-MAX

  18. Code library • Code generators • Statistics “meta-data” interface • Requires an analytics engine (SAS/R/S-Plus) Analytics • Meta-data driven • Standard statistics

  19. Code Generator DataSets Data Sets Tables Listings Define Specifications Non-standard Programs SAP • N • MEAN • SD • MIN • MAX Analytics Library Code TLGs Data Sets • MEAN_SD • MEDIAN • MIN-MAX

  20. Reporting By Elements • Data • Input Data Set • Select Parameter(s) • Subset • Summaries & Statistics • Compute • Append • Format • Render Table • Report structure • Format • Sort & Order • Render Library Analytics Reporting

  21. Reporting by Elements ADAE ADLB ADVS … Analysis Data Sets StatisticsData Sets STAE STLB STVS … STSUBSET Outputs

  22. PK Analytics Non-standard Programs Code Generator Code Library Analytics Repository Analytics Repository

  23. Non-standard Programs Code Generator Code Library Tables Listings Graphs Submission files Portals Reporting Results PK Analytics Analytics Repository

  24. Other Outputs Data Sets Tables Listings Graphs Simple Meta-Data Engine • Model – View – Controller (MVC) design pattern • Model – Meta-data • View – Graphical and programming interface • Controller – ”Administrator” of the meta-data • Very primitive and flexible meta-data engine • Adding an output starts with a Model, View and Controller(s)

  25. Track status Track and enforce dependencies Code Generator DataSets Data Sets Tables Listings Define Specifications Non-standard Programs Common Work Flow Tracking and Status Library Code TLGs Data Sets

  26. Organization Revisited • Directory Trees • No restriction on the number of levels • No restriction on naming conventions • Contexts • Aware of parent directory • Contexts have to be consistent within a directory tree • Directory tree can be your departmental drive or network share

  27. Code Generator DataSets Data Sets Tables Listings Define Specifications Non-standard Programs Network Subversion SAS Server SDD * R * SAS Drug Development Connections Library Code TLGs Data Sets Common Work Flow

  28. Code Generator DataSets Data Sets Tables Listings Define Specifications Non-standard Programs SDD * * SAS Drug Development Web Services Library Code TLGs Data Sets Common Work Flow PC SAS S-Plus / R SAS Server Anything really

  29. Conclusion Data Sets Tables Listings Graphs Simple Meta-Data Engine • Model – View – Controller (MVC) design pattern • Model – Meta-data • View – Graphical and programming interface • Controller – ”Administrator” of the meta-data • Very primitive and flexible meta-data engine • Adding an output starts with a Model, View and Controller(s)

  30. Code Generator DataSets Data Sets Tables Listings Define Specifications Non-standard Programs Network Subversion SAS SDD * S-Plus / R * SAS Drug Development Conclusion Library Code TLGs Data Sets Common Work Flow

  31. Questions & Comments Magnus MengelbierDirectorLimelogic Ltd mmr@limelogic.com+44 208 144 5701 • Introduction • Traditional process • Library • Analysis • Reporting • Connections • Summary

  32. T H E E N D

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