CDISC Standards and the Semantic Web

Transcription

1 CDISC Standards and the Semantic Web Dave Iberson-Hurst 12 th October 2015 PhUSE Annual Conference, Vienna 1 Abstract With the arrival of the FDA guidance on electronic submissions, CDISC SHARE and the notion of Research Concepts the time is ripe to look at improved implementations of the CDISC standards to assist in producing high-quality clinical research data. The presentation/paper, drawing on experience of production work and the CDISC SHARE project, will examine a prototype implementation that is being used to gain insights into the use of Research Concepts combined with Semantic Web technologies as the foundation for implementing the CDISC standards. In particular: 1. Review why we want Research Concepts and highlight the principles behind them 2. Look at a prototype semantic web MDR implementation based upon the ISO11179 Metadata Standard, the ISO21090 Healthcare Datatypes Standard, the BRIDG model and RCs taken from the CDISC Therapeutic Area development work. 3. Examine prototype tools to see implementation issues and automation opportunities. 4. Detail the benefits Research Concepts bring to the business and support business artifacts such as annotated CRFs and define.xml. 5. List the existing sources of RC metadata. 2 1

2 3 We Need Better Clarity! Assumptions section with each SDTM domain contains rules and provisos! --CAT and --SCAT use. Some better defined than others! Often see examples quoted as definitive Complete! Terminology not defined in all cases! Variables float, are not related Support Business Need! Data aggregation and re-use of data! Sponsor! Regulators! Data transparency! Traceability! Operational efficiency! CDISC compliant data to regulators,! The end to end clinical trial process Easy to Understand! Should not require 10 years experience before becoming a SDTM guru Ease of Use! Electronic! Indication of changes! Version managed 4 2

3 Variable-Based World VSTESTCD C66741 VSORRESU C66770 X X 5 Variable-Based World VSTESTCD C66741? VSORRESU C66770? VSLOC VSLAT X X 6 3

4 Biomedical (Research) Concepts Impact Assessment " Clarity " Structure " Complete " Terminology " Machine readable " Reusable Biomedical Concept Automation End-to-End Traceability Business Outputs Note: Name change from Research Concept to Biomedical Concept took place in August Simple VS Biomedical Concepts Code C25347 HEIGHT Concept Test Result Name C25347 Height Value Date Units C49668 IN Time C48500 cm 8 4

5 Vital Signs Additional Information CDISC released (2014) additional information for Vital Signs and ECG VS Provides units and additional relationships e.g. HEIGHT & WEIGHT just units 9 Vital Signs Additional Information SYSBP and DIABP, units and position

6 Vital Signs Additional Information DIABP Code C25299 Concept Test PosiOon Name C25299 Diastolic Blood Pressure C77532 Result Value Units C49670 mmhg 11 Value Level Metadata Contained within the concepts, for example HEIGHT, Integer, ###, in & cm WEIGHT, Float, ###.##, lbs & kg Also POS, --LOC, --METHOD, --CAT, --SCAT will be handled Code C25347 HEIGHT Concept Test Result Name C25347 Height Value Date Units C49668 IN Time C48500 cm 12 6

7 Define Once, Use Many Protocol CRF Tabulation Measurement of vital signs (heart rate, blood pressure at rest) Position Diastolic Systolic Units mmhg Units mmhg Correct mapping PLUS Traceability V S T E S T C D V S P O S CRF Capturing DIABP Set the correct test code Protocol dictates capture of Blood Pressure (DIABP + SYSBP) ** Protocol IE criteria could also use RCs ** Shared terminology for response: SITTING, STANDING, SUPINE, ** Statistical Analysis Plan ** 13 Silos Design Study Build Study Capture Tabulate Analyse Submit Business Object Protocol CRF Tabula?on Analysis Dataset Content Std Physical Format??? CDASH SDTM ADaM SDTM??? SDM ODM SAS SAS XML Model BRIDG 14 7

8 Decrease Need for Mapping & Gain Traceability Design Study Build Study Capture Tabulate Analyse Submit Business Object Process & Traceability Protocol CRF Tabula?on Analysis Dataset Content Std Physical Format??? CDASH SDTM ADaM SDTM??? SDM ODM SAS SAS XML Model Research Concepts BRIDG 15 Increasing Rate of Change Taken from presentation by W Kubick, CDISC Intrachange, August

9 Increasing Rate of Change From: 17 So 18 9

10 Four Steps STEP 1 MODEL STEP 2 SIMPLE STEP 3 SEMANTIC DATABASE STEP 4 IMPROVE Create a semantic model that encompasses all the items needed to meet the business need. Create a simple MDR and Study Build tool to show the ideas working. The tool will use a simple filebased database to speed progress. Take the model from step 1 and build a user interface (UI) on top learning the lessons from step 2. Improve the initial implementation from step Step 1: Model 20 10

11 Step 1: Compare Terminology SPARQL Query XML XSLT XML DB XSLT XML SPARQL Query XML XSLT XML 21 Step 1: Compare Terminology 22 11

12 Step 1: Annotated CRF DB SPARQL Query XML XSLT ODM XSLT HTML 23 Step 1: Notes Used the Topbraid Composer tool to Build the model Be the database Lessons BC approach brings benefits Combined SPARQL query & XSLT approach works well 24 12

13 Step 2: Simple Tools Desire to see it and focus on user interaction Keep it simple for the user 25 Step 2: Skill Set CDISC Sponsor Domains Forms Domains Ability to create Forms based on BCs & custom Domains based on SDTM Models & BCs. BCs BCs Ability to create BCs (content) using BC Templates. Hide BRIDG from user. BC Templates Ability to create BC Templates. Requires BRIDG knowledge. Hopefully CDISC provide these. Terminology Terminology Ability to manage Sponsor, CDISC and other terminologies. BRIDG BRIDG provides the framework for BCs

14 Step 2: BC Editing 27 Step 2: BC Editing BC structure flattened using alias to make it understandable to those working in the business today Menu Structured to reflect the Skill Set Terminology BC Templates & BCs Form & Domains Study Concept Test Result Date Code Name Value Units C25347 C25347 C49668 HEIGHT Height IN Time C48500 cm 28 14

15 Step 2: acrf Automated acrf generation to show potential of using BCs and investigate issues 29 Step 2: Notes Built using PHP & Javascript Database a combination of files ODM for Forms and Studies Define for domains Some bespoke XML for other pieces Terminology XML files from Step 1 exports Lessons Can hide the complexity Confirmed the benefits of BCs Can make it easy for the users 30 15

16 Step 3: Semantic Database User Interface implemented by Web Site Database accessed by SPARQL over HTTP Ontotext S4 Cloud Service Fuseki Apache open source server Implements the model developed during stage 1 31 Step 3 : Terminology Imports owl files issued by CDISC from Dec 2013 onwards Use the power of the query to meet key business needs. Changes and impact of changes 32 16

17 Step 3: Terminology Changes such as submission value changes and when did it change 33 Step 3: Biomedical Concept Based on ISO1179 BRIDG Classes & Attributes ISO21090 Data Types 34 17

18 Step 3: Tools SPARQL Query to extract a specified BC 35 Step 3: Biomedical Concept Equivalent BC to that shown for stage

19 Step 3: Notes Version management and namespaces been a tricky area Power of SPARQL Issues with tools and debugging Benefits of BCs and power for impact analysis, great potential Forms, Domains and Study Build to be done by end of year Blogs will be written! 37 Summary Semantic Technology Impact Assessment " Clarity " Structure " Complete " Terminology " Machine readable " Reusable Biomedical Concept Automation End-to-End Traceability Business Outputs Exports to Support Today s Process 38 19

20 Useful Links Topic More on Biomedical Concepts Link h]p:// concepts- a- what- why- and- how/ ISO25964 h]p:// and- iso / ISO11179 h]p:// things- to- all- men- iso / Step 2 h]p:// bit- of- a- tangent/ GitHub Paper from PresentaOon h]ps://github.com/daveih/alba PhUSE website 39 Contact And More Information dave.iberson-hurst@assero.co.uk Blogs Available At