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Clinical Data Management (CDM) Case Study with SDTM support

A CDM Case Study for the creation of clinical trial databases for a large Scandinavian pharmaceutical company

Quanticate has been working successfully with a large Scandinavian pharmaceutical company over the past 12 months in the area of clinical data management (CDM); focused on the delivery of clean quality clinical trial databases in a system mandated by the Sponsor with additional statistical programming support in the creation of SDTM templates.

The Sponsor’s requirements had not been fully understood by the Interactive Voice/Web Response System (IXRS) and Electronic Data Capture (EDC) system providers, leading to frustration and delay. Quanticate took a lead in working with the technology vendor to set expectations and to manage future requirements in two clinical trials. The on-going problems were resolved through technology enhancements developed by our team of experts. The establishment of a governance structure between Quanticate, the Sponsor and the technology vendors, enabled us to proactively anticipate and manage challenges associated with any future protocol amendments.  Feedback from the Sponsor was very positive due to our pro-activeness and investment in the partnership.

Innovations brought to the Sponsor

  • Establishment of a robust governance structure between the Sponsor, the technology provider and Quanticate: this led to transparency between all three companies which enhanced the understanding of the technology provider for the Sponsor needs. This transparency led to the Sponsor understanding how its in-study protocol changes resulted in implementation challenges for the technology provider. The technology provider had been very cognizant of the costs of implementing these changes to the extent they were merging multiple changes resulting in delays that were unacceptable to the Sponsor.  The transparent governance driven by Quanticate led to the mutual understanding by the Sponsor and the technology provider of the need to marry timelines and budget.
  • The tracking of all deliveries using an established project management (PM) system was implemented, to identify any potential issues as early as possible. Regular comparison of actual and baseline hour reports for specific tasks are run, to identify  exactly where additional support should be sent, or assignment(s) revised. The PM system controls all on-going projects, enabling the project manager to recognize potential risk of staff becoming overloaded.
  • Revision of the existing quality control (QC) SOP, and creation of a new SOP for peer review to improve quality. The latter is a third-party review process where the lead statistician follows risk-based methodology to check all key elements of the biostatistic deliverable. Training was provided on the updated QC process, which included a practical guide on the application of the QC SOP in real-life cases; implementation of QC dashboards giving in-depth access to comprehensive quality data at overall/portfolio/project level and equipping user in bunch of interactivity. All Quanticate programmers have a routine QC assessment which is used as one of key sources for improving and developing our staff.
  • The latest concept is ‘library of templates’ which is crucial part of our overall EDC -> SDTM mapping process. It is based on very active cooperation between Data Management and Programming and the final outcome are sets of corresponding EDC modules and sections of annotated CRF.

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Improved performance in quality of data and timelines

  • Quanticate have built three databases for a single program within a span of 12 weeks for the Sponsor.  While 12 weeks is a standard timeline for a database build, the challenge is that the build needed to be sequential since a change in one database would impact the other two.  There have been numerous changes based on the Sponsor’s needs and these are being accommodated and managed in a manner that is exceptional.  This can be attributed to our project management skills and our expertise in the systems which help us quickly respond to the changing circumstances.
  • The Sponsor wanted information to flow from the EDC system to the Sponsor’s Clinical Trial Management System (CTMS). The two technology providers were unable to accommodate this interface in less than six months, which would negatively impact study timelines. The Sponsor requested assistance from Quanticate’s in-house technical experts, and within one day of discussing the scope, Quanticate had a proof-of-concept tool developed to transfer data between the two vendor systems. Quanticate’s speedy development was permitted through using best-of-breed Open Source components combined with our strong data experience. Once the proof-of-concept was confirmed by the project team to meet their needs, formal user requirements were documented and approved. Within one week, the solution was ready for full validation. This included the Audit Logging, Reporting, Alerting and Summarisation that Clinical Systems Validation and SDLC Best Practice mandates.  Within two weeks, the system was deployed into production. The Sponsor was delighted as the solution met their requirements and was faster and more cost-effective than the offering from the two well-known large vendors.
  • Monthly SDTM transfers to the Sponsor throughout the active life of the study have been provided to allow on-going Medical Monitoring of data. This process has involved bespoke programming solutions to automate the production and validation of SDTM datasets, which has resulted in reducing cost to the Sponsor whilst maintaining the high standard of QC we apply to all deliverables. The system that has been put in place also allows for ad-hoc requests for data (for example, for Data Monitoring Committee meetings) to be accommodated at relatively short notice compared to a more standard programming set-up.

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Streamlining data collection and reports

The traditional approach to data cleaning is that CDM do not review the data until after it has been source data verified by monitors on site. Quanticate is taking the approach to clean data once it is entered by the site. This supports risk-based monitoring, enabling the monitors to review any CDM issues prior to their next monitoring visit. This results in more efficient data monitoring and streamlining of data cleaning. Due to this data cleaning approach, the Quanticate Biostatisticians can confidently transfer semi-clean monthly SDTM datasets. In parallel, CDM transparently ensure that the Sponsor clinical operations group are fully informed of data cleaning status. This is done by weekly and ad hoc reporting to ensure clinical operations resource is focused where required.

The concept of library of templates in our EDC to SDTM mapping process has been previously mentioned but it is just the beginning of a larger project. Quanticate is developing tools which inject annotations from aCRF directly into the mapping specification which together with other enhancements makes delivery of define.xml 2.0 very easy. Therefore, all of Quanticate’s processes are designed in a way which optimizes production of define.xml 2.0.

Other projects include our new EDC user acceptance tool which will be supporting both CDM & Programming departments. CDM will improve the edit check process while Programming will start receiving data extracts quicker and this extract will contain all common data scenarios. In addition, this is the area where we anticipate benefits of applying Machine Learning techniques.

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