Presentation is loading. Please wait.

Presentation is loading. Please wait.

3.1.1. Protocol Author ProcessPeople TechnologyExternal data standards No structured/unambigous link between scientific concepts within protocol and variables.

Similar presentations


Presentation on theme: "3.1.1. Protocol Author ProcessPeople TechnologyExternal data standards No structured/unambigous link between scientific concepts within protocol and variables."— Presentation transcript:

1 Protocol Author ProcessPeople TechnologyExternal data standards No structured/unambigous link between scientific concepts within protocol and variables used within downstream activities (data collection & analysis) New/Changing & not available Inconsistency ? No tools to support linking (emerging electronic protocol generator cannot work effectively with this) No formal process to build the link in an unmabiguous way Limited ressources Additional burden on protocol authors with benefits to other people Different knowledge & understanding between scientist & developper Different translation of concept into variables by different data managers

2 3.1.2 Data manager/collector ProcessPeople TechnologyExternal data standards Growing set of variables ( for clinical trial) with inconsistency, redundancies No possibility to share data across companies (CROs, in/out- licensing) and with medical record No agreement on terminology/code list (e.g. MEDDRA, SNOMED, LOINC, CDISC Vocab...) No „umbrella“ organisation to decide on variable definition across pharma and health care No tools to store definition of variables accepted across the industry (use caDSR but UI not friendly) No formal process to share variable definition across industry “inventivity” of people in different contexts Mindset that EHR integration is far away or „the problme to be solved“ by HC actors Not yet enough pressure in need for increased efficiency in data collection (changing!) No shared definition of what a variable is No unambigous link between concepts within protocol and variables (see section 3.1.1) No tool to exchange variable definition (possibility to use ODM ?) CDASH ????? Minimal re-use of content No standardiwed proprietary extensions No structured metadata

3 3.1.3 Statistician/reporting ProcessPeople TechnologyExternal data standards No consistency in the way variables are used across studies No information on how variables were linked together in data collection No tools to store relationship between variables at a conceptual level (e.g. SYSBP may be collected with site and position) No process to enforce collection of meta-data when collecting data No process to ensure consistency in data collection across studies Data collection tool do not support collection of meta- data ??? Additional burden on data collection team with benefits to other people Protocol Team focus on ONE protocol and overlook need for data integration for submission (ISSE and ISE) and further data mining CDISC SDTM does not manage different groupings in different contexts (e.g. SYSBP with/without qualifiers) CDISC SDTM limited to safety BRIDG is the conceptual model linking variables No agreement on terminology/code list in clinical standards

4 3.1.4 Data curator/miner ProcessPeople TechnologyExternal data standards No consistency in the way variables are used across studies/projects No information on how variables were linked together in data collection No tools to store relationship between variables at a conceptual level (e.g. SYSBP may be collected with site and position) No process to enforce collection of meta-data when collecting data No process to ensure consistency in data collection across studies Data collection tool do not support collection of meta- data ??? Additional burden on data collection team with benefits to other people Protocol Team focus on ONE protocol and overlook need for data integration for submission (ISSE and ISE) and further data mining CDISC SDTM has limitations and scope is only clinical safety Different standards – CDISC, SEND, HL7 – require mapping Same as statistician/reporting with scope across R&D Growing mindest of the need of secondary use of data BRIDG is the conceptual model linking variables across standards No agreement on terminology/code list in R&D Data requires significant manipulation in order to be pooled, or may be difficult to pool consistently.

5 3.1.6 Application/eCRF developer ProcessPeople TechnologyExternal data standards No underlying “enterprise” data model, linking all variables together with clear semantic => inconsistencies across applications and across trials BRIDG can be used as the basis of the „enterprise“ data model with some adaptation to company ISO data types should be used more widely No tools to store definition of variables accepted across a company (across all domains) No formal process to hamronize application variables across studies/application Lack of experience in available standards HL7 very complex and difficult to learn in pharma No common terminologies across applications – and across industry

6 3.2.1 FDA reviewer ProcessPeople TechnologyExternal data standards No possibilities to compare efficacy and safety profiles across companies / products No possibility to combine clinical trial data and pharmacovigilance data or other data SDTM/SAS transport file good only for safet and for one company HL7 CDISc content messages need to rely on a repository of concept/variables used in the message No tools to store definition of concept and variables accepted across a company (across all domains) ???? ????? No tools allowing to store and manage mapping between HL7 CDISC content and SDTM view SNOMED is HSSSP standards, but not used in the industry

7 3.3.1 Data Standards definition ProcessPeople TechnologyExternal data standards Inconsistencies across different standards within CDISC BRIDG being developped to ensure common semantic across standard No tools to alowing to have easy access to all standards and to make consistency check (.e.g no easy way to find how CDAHS define a variable versus SDTM) Silo mentality No clear perception of the need of fully consistent data standards CDISC standard developement process good for ONE standards - does not enfore consistency check ACROSS standards ?

8 3.3.2 CMDR steward ProcessPeople TechnologyExternal data standards Ensure quality of CDISC MDR in an environment where there are inconsistent and sometime conflicting definitions of concepts and variables ODM could be used to support import/expert within CMDR No tools to support sharing of standard content across organisation No certification authority of cross industry standard content Change in mindset: data are critical asset, data standards are not a competitive advantage and should be shared across in the industry No FORMAL process for sharing data standards content across industry No tools to support storgae and sharing of standard content across organisations


Download ppt "3.1.1. Protocol Author ProcessPeople TechnologyExternal data standards No structured/unambigous link between scientific concepts within protocol and variables."

Similar presentations


Ads by Google