David A. Evans, Managing Director11.09.16
Ready for December 17, 2016? That is the U.S. Food and Drug Administration ( FDA ) deadline that requires all clinical and non-clinical studies to use standards in the Clinical Data Interchange Standards Consortium (CDISC) Data Catalog to support new drug submission and biologics license applications.
We recently surveyed nearly 100 global life sciences executives about how they are implementing clinical data standards and whether or not they see value in the standards.
Although most companies see the advantages of complying with the CDISC standards and recognize that the standards offer a number of potential commercial and operational benefits, including reducing costs and speeding time to market of new drugs, many have been slow to adopt the standards.
Beyond migrating or mapping proprietary data to CDISC standards, respondents said that a number of challenges pose significant demands on their already stretched resources, including: Development and support for new standards, processes and infrastructure; developing standards governance structures across functional areas; training people to implement the standards; and putting management processes in place to verify Compliance with the new standards.
The vast majority of respondents cited regulatory compliance as the most important reason for adopting data standards today. A slightly smaller percentage believed CDISC standards will improve regulatory compliance over the long run.
While regulatory compliance is the primary driver of data standardization today, nearly 80% of respondents also see the need for consistent data across the clinical data life cycle, and 66% believe standards enhance operational efficiency. Of the respondents, 94% currently submit to the FDA, 76% to the European Medicines Agency and 54% comply with the Japan Pharmaceutical and Medical Devices Agency.
When it came to selecting CDISC standards, the highest number of respondents chose Study Data Tabulation Model (SDTM), followed by Analysis Data Model (ADaM) and Define-xml. About half of respondents said they integrated SDTM, ADaM and Clinical Data Acquisition Standards Harmonization standards cross-functionally, while 36% have implemented standards separately in functional areas.
Companies are clearly at different starting points and maturity in their journey toward data standardization. Consequently, different implementation issues take precedence depending on where companies are on the adoption curve. Over half of respondents viewed the difficulty in building governance processes as the primary organizational challenge. Other challenges include contending with: Insufficient knowledge of, or experience with CDISC standards, and lack of support of new standards, processes and infrastructure; multiple versions of CDISC standards; difficulty in hiring professionals with CDISC knowledge; and resistance from study teams in moving away from the legacy approach.
Approximately half of the respondents noted that implementation of their selected data standard was cross functional, but more than a third revealed that standards were implemented separately within functional areas.
Nearly half of the respondents have governance challenges, with specific challenges ranging from limited resources within functions to a dearth of cross-functional resources. Many respondents stated that only part-time resources were deployed to their standards organization and that only modest technology support was provided to facilitate governance workflows.
Nonetheless, there is wide recognition that more structured governance will yield potential benefits mostly to improve standards awareness, verify standards compliance, and centralize accountability and authority.
A clear majority of respondents expected metadata management to both improve efficiency and allow faster maintenance of standards. Yet, organization of metadata was fragmented, with some companies using spreadsheet-based standards metadata management, and less than a third using metadata repositories. A surprising number of respondents (18%) indicated that they were not managing standards metadata. Despite the challenge of metadata management, more than two-thirds see the value in consistency of data across studies.
Nearly 63% of those using STDM outsourced data creation and exchange, while approximately a third of companies chose that route for ADaM or Define-xml.
What’s clear from the responses of these life sciences executives is that companies are at different levels of maturity in their journey toward meeting the FDA binding guidance deadlines and that many are struggling with issues related to data standardization capability, metadata management and governance.
David A. Evans
Managing Director
David A. Evans is a managing director responsible for quality governance and regulatory companies for Accenture’s Life Sciences Accelerated R&D Services group. He has over 35 years of experience in the clinical research, regulatory and healthcare industries.
We recently surveyed nearly 100 global life sciences executives about how they are implementing clinical data standards and whether or not they see value in the standards.
Although most companies see the advantages of complying with the CDISC standards and recognize that the standards offer a number of potential commercial and operational benefits, including reducing costs and speeding time to market of new drugs, many have been slow to adopt the standards.
Beyond migrating or mapping proprietary data to CDISC standards, respondents said that a number of challenges pose significant demands on their already stretched resources, including: Development and support for new standards, processes and infrastructure; developing standards governance structures across functional areas; training people to implement the standards; and putting management processes in place to verify Compliance with the new standards.
The vast majority of respondents cited regulatory compliance as the most important reason for adopting data standards today. A slightly smaller percentage believed CDISC standards will improve regulatory compliance over the long run.
While regulatory compliance is the primary driver of data standardization today, nearly 80% of respondents also see the need for consistent data across the clinical data life cycle, and 66% believe standards enhance operational efficiency. Of the respondents, 94% currently submit to the FDA, 76% to the European Medicines Agency and 54% comply with the Japan Pharmaceutical and Medical Devices Agency.
When it came to selecting CDISC standards, the highest number of respondents chose Study Data Tabulation Model (SDTM), followed by Analysis Data Model (ADaM) and Define-xml. About half of respondents said they integrated SDTM, ADaM and Clinical Data Acquisition Standards Harmonization standards cross-functionally, while 36% have implemented standards separately in functional areas.
Companies are clearly at different starting points and maturity in their journey toward data standardization. Consequently, different implementation issues take precedence depending on where companies are on the adoption curve. Over half of respondents viewed the difficulty in building governance processes as the primary organizational challenge. Other challenges include contending with: Insufficient knowledge of, or experience with CDISC standards, and lack of support of new standards, processes and infrastructure; multiple versions of CDISC standards; difficulty in hiring professionals with CDISC knowledge; and resistance from study teams in moving away from the legacy approach.
Approximately half of the respondents noted that implementation of their selected data standard was cross functional, but more than a third revealed that standards were implemented separately within functional areas.
Nearly half of the respondents have governance challenges, with specific challenges ranging from limited resources within functions to a dearth of cross-functional resources. Many respondents stated that only part-time resources were deployed to their standards organization and that only modest technology support was provided to facilitate governance workflows.
Nonetheless, there is wide recognition that more structured governance will yield potential benefits mostly to improve standards awareness, verify standards compliance, and centralize accountability and authority.
A clear majority of respondents expected metadata management to both improve efficiency and allow faster maintenance of standards. Yet, organization of metadata was fragmented, with some companies using spreadsheet-based standards metadata management, and less than a third using metadata repositories. A surprising number of respondents (18%) indicated that they were not managing standards metadata. Despite the challenge of metadata management, more than two-thirds see the value in consistency of data across studies.
Nearly 63% of those using STDM outsourced data creation and exchange, while approximately a third of companies chose that route for ADaM or Define-xml.
What’s clear from the responses of these life sciences executives is that companies are at different levels of maturity in their journey toward meeting the FDA binding guidance deadlines and that many are struggling with issues related to data standardization capability, metadata management and governance.
David A. Evans
Managing Director
David A. Evans is a managing director responsible for quality governance and regulatory companies for Accenture’s Life Sciences Accelerated R&D Services group. He has over 35 years of experience in the clinical research, regulatory and healthcare industries.
