Resource Filtering Tool
Blog Post
Should I up-version study SDTM and ADaM when it becomes time to submit a marketing application?
Do I need to up-version to the most recent versions of the standard from the current Catalog when preparing to submit clinical study data? How can I figure this out? Check out the latest blog from Rho to find out.
Blog Post
Best Practices for Hardcoding Clinical Trial Data
In clinical trials, the accuracy and integrity of data are paramount. While the goal is to handle data systematically and programmatically, there are occasions when hardcoding becomes necessary. Note the following considerations for when to hardcode and the importance of documenting these decisions.
Blog Post
Bringing a Medical Device or Drug to Market-Part 2: How to Use the Request for Designation (RFD) Process to Classify Your Product
Distinguishing between a medical device and a drug may be challenging to define for some products. We turn our attention to a crucial tool that Sponsors may use to have the FDA classify your product: the Request for Designation (RFD). In this blog, we’ll describe what an RFD entails and its significance in the regulatory realm, providing a comprehensive overview of the process.
Blog Post
Blinded Variance Estimation Sample Size Adjustments
Interim sample size adjustments and their many approaches are a frequent discussion point between Sponsors and statisticians during protocol development. One such approach is a blinded assessment of variance, favored by some Sponsors for its lack of alpha penalty. We will discuss how this method works, the pros, the cons, and if this approach might be appropriate for your protocol.
Presentation
Food Allergy Research with CDISC Standards
In February 2024, the FDA approved a treatment for the reduction of allergic reactions to multiple foods based on results from the NIH-sponsored OUtMATCH study. Many federal studies like this one do not require CDISC standards, however in this case SDTM and ADaM were required because OUtMATCH used a commercial product and intended to submit the results for agency approval.
This presentation discusses the ways in which the SDTM tabulation process improved the overall data quality for the study, summarizes a strategy for mapping all the data collected during a food challenge data into standard SDTM domains, and explains the ADaM structures used to capture endpoints. Overall, it provides an example of a study in which the CDISC standards played a key role throughout the process and provides more specific details on applying the standards to research on food allergy treatments.
Presentation
Optimizing Clinical Research Efficiency through SDTM Dataset Splitting
In the fast-paced world of clinical research, efficiency is a key priority. Splitting SDTM domains into multiple datasets can serve as a valuable tool, streamlining the process of creating and reviewing large, complex data domains.
Presentation
Navigating Complexities: Integrating Data from Ongoing Studies in Regulatory Submissions
Integrating data for regulatory submissions requires organizing and consolidating information from multiple studies for a project. The activities could include aligning variables from studies using different versions of CDISC standards and/or creating new variables to support integrated analyses. BUT, what happens when another layer of complexity is added? What if an ISS or ISE will include data from ongoing studies? What are key considerations when dealing with ongoing data?
Blog Post
Implementation of ICH M12 Guidance in 2024: What’s New for Drug Interactions?
The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) adopted a harmonized drug-drug interaction (DDI) guidance (ICH M12) in May 2024. The next step is for this guidance to be implemented by ICH members; the FDA and EMA have already implemented the guidance. Read our blog for key highlights of the 2024 ICH M12 Guidance.
Blog Post
FMQs vs SMQs
Sponsors often rely on Standardized MedDRA Queries (SMQs) to group adverse events for detection of safety signals across clinical trials. Additionally, the FDA has introduced their own version of adverse event groupings – FDA MedDRA Queries (FMQs). So, what’s the difference?