In the most recent episode of our podcast, The Life Science Rundown, The FDA Group's Nick Capman spoke with Sunil Gupta, a seasoned expert in pharmaceutical data, to shed light on the nuances of SDTM (Study Data Tabulation Model) compliance and its pivotal role in clinical trial processes.
Sunil brings a wealth of experience from his three decades in the pharmaceutical industry, focusing on areas like SAS programming, submissions, and leveraging new technologies for clinical trials.
Sunil emphasizes the shift from manual processes to technology-enhanced methods in clinical trials and strongly believes in the value of automation and standardization for improving clinical trial processes.
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Sunil is an expert in CDISC and SAS programming, offering specialized teaching and mentoring services. He emphasizes real-world examples and utilizes a CDISC reference file to ensure compliance with CDISC and FDA guidelines.
Sunil is also the founder of SASSavvy.com, a pioneering SAS® Blog membership subscription service. This platform simplifies the search and application process for SAS® programming challenges.
A few key points from the discussion:
Standards and compliance
Sunil stresses the importance of data quality and compliance in FDA submissions. He emphasizes that compliance involves ensuring standardized data entry and structured formats. The discussion underscores the shift from diverse data submission formats to standardized processes such as SDTM, where common variables like demographic information are uniformly defined.
Sunil also notes the need for organizations to understand and adapt to updates in implementation guides, which are informed by feedback from functional companies and CROs.
Challenges in compliance
Sunil identifies several challenges:
Documentation and communication: The need for proper training and secure access in the regulatory environment.
Updates and monitoring: Ensuring updates to programs and datasets are documented, justified, and monitored proactively.
Consistency and proactivity: Another challenge lies in synchronizing efforts across teams and being proactive in addressing potential issues.
Pitfalls to avoid
Sunil warns against common pitfalls such as:
Misinterpreting compliance reports: There is a risk of taking compliance reports at face value without verifying the details, which could lead to overlooking false positives or negatives.
Neglecting granular verification: He advocates for verifying findings at the subject level to ensure accuracy in data analysis.
Overlooking study endpoints: It’s vital to monitor primary and secondary endpoints, particularly in studies designed for efficacy and safety.
Resources for compliance and standardization
Sunil recommends resources such as cdisc.org and phuse.global for updates and guidelines in the field. He also advises attending webinars and workshops offered by these organizations for continuous learning.
The future of compliance tools
Looking ahead to 2024, Sunil is enthusiastic about integrating compliance tools into the SDTM generation process. He predicts a growing role for applications and metadata in compliance and standardization, improving awareness and addressing issues early in the data lifecycle.
Final thoughts
Sunil concludes by stressing the importance of using available resources, mentoring, and collaboration within the industry. He highlights his engagement in mentoring, teaching, and contributing to open-source platforms like SASsavvy. He encourages reaching out to him for guidance and mentions his active participation in upcoming conferences and webinars.
An SDTM compliance checklist
Here's a simple checklist to assess your adherence to SDTM standards and compliance based on Sunil’s insights:
Have we implemented SDTM as our standard format for clinical trial data?
Are regular training sessions on SDTM guidelines being conducted for all relevant staff members? Do these training sessions cover the latest updates and nuances of the SDTM standards?
Have we formed a dedicated team to oversee and ensure SDTM compliance throughout our data management processes?
Is there specialized software in place for automatic checks against SDTM compliance standards? Are the results of these software checks regularly reviewed and acted upon?
Have we developed a detailed SDTM compliance checklist for routine audits of our data?
Is there a specific Quality Control process in place focusing on SDTM compliance before data submission?
Do we consult with external SDTM experts for complex projects or specific compliance challenges?
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Clinical Data Standards in Focus: SDTM Compliance with Sunil Gupta