2021-01-22 DEUN CDISC UG Presentation Topics 2021

Global Regulatory Submissions

The CDISC electronic data submission to the Japan regulatory body (PMDA) has been made mandatory from April 2020. Being one of the giants in Pharmaceutical market, development and approval of drug in Japan is a crucial step for pharmaceutical companies.
The objective of this paper is to render intelligible for submission of SDTM data for a beginner. It would give an insight about the aspects to be considered through the course of study start-up, conduct and study closeout focusing on the key areas, challenges and potential solutions.
This paper would also highlight the differences between PMDA and FDA submissions, which would aid the teams to understand the specificities of Japanese pharmaceutical market better.

Impact of CDISC standards on business optimization 

The process of data transformation for data collected during the clinical trials whether via Electronic Data Capture (EDC) or via external systems (e.g. ePRO, etc.) is usually done once the clean and monitored data has been extracted from the EDC system. Many EDC systems are not fully equipped yet to export the data in SDTM format, so the team of programmers maps and transforms the clinical data into industry standards such as CDISC SDTM. This process is time consuming and requires close monitoring of timelines.

But what does it mean to be able to extract the data in SDTM format from EDC system?
In our collaboration with Anju Life Sciences Software, we could configure SDTM exports within TrialMaster EDC solution as soon as the data collection model is defined and eCRF is set-up. Once data is available, the SDTM exports can be run immediately.

In our presentation we will go over the case study to demonstrate all pros and cons of the process as well as lessons learnt.

COVID-19 Impact

The current COVID-19 pandemic has affected many industries around the world and the pharmaceutical industry is one of them. It is being presented with significant challenges related to conduct and handling of ongoing Clinical trials.
CDISC is a global committee that deal with the standardization of research data related to Life sciences and describes how to structure the data. In order to handle the current situation, CDISC has reformed its guidelines with updates in specific SDTM domains.
This paper would be covering the impact and changes in the SDTM standards that has been implemented in the ongoing studies along with future implications. On these lines we would further elaborate on the study procedures being missed and capturing additional information related to COVID-19 which would help analyze data more effectively with few examples.

Global Regulatory Submissions

It is always intriguing when creating submission packages for regulatory submissions. There are so many points one needs to be aware of to have the package ready as per the published guidelines and some intricate scenarios in order to provide all the obligatory data in the manner as expected so it aids in simplifying the review and approval processes which in turn can expedite the molecule to mass production timeframe and help those who are in need of the drug or therapy or device, etc.

This sounds exciting right, well what if we have these submission requirements change when submitting for different divisions of FDA and how does this paradigm shifts or changes when what we are testing is a Vaccine, well then this is what our presentation is all about.

In this presentation, we will be covering some of the intricacies and obligatory requirements, which will be of help for all individuals from all level of experiences.

Real World Data / Evidence

I started exploring about Real World Data\Evidence and how to use it in the part of clinical trial regulatory submission as a supplemental which can support studies. I feel, I have gathered information which is required and in this paper I want to share my complete exploration. It covers, what is Real World Data, sources of RWD, Sample Real World Databases\APIs and how to extract data from them using SAS. Mapping of Real World Data (FHIR Standards) to CDISC standards, Different regulatory bodies (FDA, EMA) guidelines on Real World Data submission as part of Clinical Trial Data and etc.

OTHER TOPICS TOWARDS CDISC STANDARDS

iomedical concepts (BCs) are units of knowledge created by a unique combination of characteristics that exist independent of any standards implementation. They define observations made about a subject, such as a measurement of an analyte in a subject sample. CDISC began exploring the use of biomedical concepts based on the ISO 11179 standard in the CDISC 360 project, and continues to expand their use and refine the process of concept-based standards development. This presentation will discuss CDISC's approach to biomedical concepts, progress to-date, and the future of concept-based development for enhancing standards content in the CDISC library.

CDISC Core

• Purpose of the NSV Registry
-Ensure the development teams use the NSVs consistently.
-Help identify NSVs for promotion to the model/IG.
-Allow CDISC users to access the NSV information so they can use them within their organizations

Methods:
• Identification of gap in consistency
• Steps Taken
• Where it began – SUPPQUALs
• Points about SUPPQUAL role
• Evolution of SUPPQUAL and NSVs
• Evolution of the NSV Registry
-Where to find
-What the status fields mean
-How to search
• Governance and Approval Process
-NSV sub-team reviews
-Part of Internal Review and Public Review of the TAUGs

Conclusion:
NSV Registry provides a place to find NSVs that are currently being used across CDISC users and standards development teams for example creation within TAUGs. This is a great place to locate a variable to represent a concept that none of the standard variables available cover and will allow for consistent use of Non-standard Variables. Using NSVs from the CDISC Registry ensures consistent use of NSVs.

Standards governance

With the popularity of wearable devices and precision medicine, data is becoming increasingly complex. It is being collected from many sources and can take on various formats. The sheer volume of collected data has also grown exponentially. Now, more than ever, it is critical to build a clinical data pipeline that preserves data integrity and standardization for use across a clinical data portfolio.
Along with the challenges of today's complex data, the pathway from acquisition to submission is not straight forward. There are many different systems that aggregate and prepare data, all of which can impact its integrity.

What are some of the latest tools managing data through this process? What are their benefits? How are they upholding data integrity? Through the perspectives of industry experts, this session will discuss the approach and benefits of integration, as well as the value of building an effective clinical data pipeline.