This video provides an overview of the CDISC SDTM and ADaM standards, highlighting the importance of standardization in clinical data management. The key steps discussed include creating an annotated case report form (aCRF), developing SDTM mapping specifications, and generating SDTM datasets for submission. Key moments: 00:17 The instructor explains the class schedule, duration, and the importance of blinding in clinical trials. They also discuss the informed consent form and the screening process for clinical trial participants. -Explanation of class schedule, duration, and importance of blinding in clinical trials. -Discussion on the informed consent form (ICF) and its significance in clinical trials. -Explanation of the screening process for clinical trial participants based on inclusion and exclusion criteria. 08:05 Randomization is crucial in selecting subjects for studies to ensure a diverse mix of participants. Control and treatment groups play key roles in clinical trials, with the FDA emphasizing standardized reporting for approval and analysis. -Importance of randomization in selecting study participants for diversity and unbiased results. -Significance of control and treatment groups in clinical trials for comparison and evaluation of outcomes. -FDA's focus on standardized reporting formats for efficient approval and analysis of study reports. 16:11 The organization known as 'C-Disk' plays a crucial role in setting and maintaining standards for data management in clinical research, benefiting researchers, pharmaceutical companies, and technology vendors alike. -C-Disk ensures data clarity and simplicity for researchers, leading to quicker outcomes and easier data management throughout clinical research stages. -For pharmaceutical companies, C-Disk streamlines the approval process by focusing on fast and simple report submission for swift market delivery of drugs. -Technology vendors like us benefit from C-Disk standards by efficiently processing and analyzing vast amounts of data extracted from clinical trials, ensuring proper data management. 24:14 A Case Report Form (CRF) is crucial in clinical trials as it contains all study information, ensuring data collection aligns with protocols and regulatory standards, promoting effective data collection and safety of data sharing among teams. -Importance of Study Protocol and Data Collection. Protocols guide data collection, ensuring compliance with study requirements, including study design, dosages, and blinding, vital for effective data collection and regulatory adherence. -Components of a CRF. A CRF includes study title, investigator details, subject ID, inclusion/exclusion criteria, dosage information, and signatures, essential for documenting individual subject data in clinical trials. -Role of Raw Data in Clinical Trials. Raw data sets, like SAS data sets organized by domains, serve as inputs alongside CRFs and metadata, providing comprehensive subject information for analysis and reporting. 32:20 Understanding the importance of maintaining variable names in compliance with regulations is crucial in data management. Ensuring variables adhere to specific rules like character limits and special characters is essential for data integrity and consistency. -Importance of variable naming conventions in data management. Adhering to rules like character limits and special characters ensures data integrity and consistency. -Differentiating between CRF and ACRF in clinical data management. ACRF contains more detailed information and requires validation by the team lead. -Process of creating and validating ACRF in clinical data management. SAS programmers play a role in generating ACRF, which is then validated by the team lead. 40:26 The video discusses the process of creating an Excel file to store information from a CRM system, identifying variables, and converting the Excel file into an XFDF file for annotation. -Creating an Excel file to store CRM information and identifying variables are crucial steps in the process. -Converting the Excel file into an XFDF file for annotation involves determining color formats, priorities, and domain placements. -The roles of a clinical research associate and a clinical data management team in producing data are highlighted in the discussion. 48:31 Understanding the steps involved in programming for SDTM implementation is crucial for SAS programmers. It involves mapping specifications, variables selection, and creating SDTM specification Excel based on ACRs. -Importance of mapping specifications and variables selection in SDTM programming. It ensures accurate data representation and table creation in SAS. -Creating SDTM specification Excel based on ACRs for proper data organization. It includes details like variable types, lengths, and source information essential for programming. -Role of TLs, protocol documents, and SDTM implementation guides in SDTM programming. They provide necessary information for creating SDTM specification Excel. 56:34 The process of creating SDTM output involves steps like preparing annotated CRF, mapping specifications, programming plan, and converting SAS datasets to XPT files for submission using software like Pinnacle 21. -Importance of teamwork in SDTM creation. Team members leverage existing guidelines and collaborate on programming plan allocation for efficient workflow. -Conversion of SAS datasets to XPT files. Explanation of using software like Pinnacle 21 for creating XML files for submission as study results. -Validation and submission process. Emphasis on creating validation nodes, defining XML files, and submitting study results for SDTM output. 1:04:36 The video discusses starting with SDTM mapping specification, understanding different domains in SDTM, and the importance of SDTM guidelines for programming. It emphasizes the need to follow guidelines for domain and variable names, data types, formats, and core rules. -Importance of understanding different domains in SDTM like special purpose domains, interventions, events, and findings, along with trial design models. -Explanation of SDTM guidelines including writing domain and variable names, allowed data types and formats, core rules, identified variables, and timing variables. -Planning to complete SDTM guidelines in upcoming classes and then moving on to special purpose domains for programming.
GREAT WORK!!!!!! THANKS!!!
This video provides an overview of the CDISC SDTM and ADaM standards, highlighting the importance of standardization in clinical data management. The key steps discussed include creating an annotated case report form (aCRF), developing SDTM mapping specifications, and generating SDTM datasets for submission.
Key moments:
00:17 The instructor explains the class schedule, duration, and the importance of blinding in clinical trials. They also discuss the informed consent form and the screening process for clinical trial participants.
-Explanation of class schedule, duration, and importance of blinding in clinical trials.
-Discussion on the informed consent form (ICF) and its significance in clinical trials.
-Explanation of the screening process for clinical trial participants based on inclusion and exclusion criteria.
08:05 Randomization is crucial in selecting subjects for studies to ensure a diverse mix of participants. Control and treatment groups play key roles in clinical trials, with the FDA emphasizing standardized reporting for approval and analysis.
-Importance of randomization in selecting study participants for diversity and unbiased results.
-Significance of control and treatment groups in clinical trials for comparison and evaluation of outcomes.
-FDA's focus on standardized reporting formats for efficient approval and analysis of study reports.
16:11 The organization known as 'C-Disk' plays a crucial role in setting and maintaining standards for data management in clinical research, benefiting researchers, pharmaceutical companies, and technology vendors alike.
-C-Disk ensures data clarity and simplicity for researchers, leading to quicker outcomes and easier data management throughout clinical research stages.
-For pharmaceutical companies, C-Disk streamlines the approval process by focusing on fast and simple report submission for swift market delivery of drugs.
-Technology vendors like us benefit from C-Disk standards by efficiently processing and analyzing vast amounts of data extracted from clinical trials, ensuring proper data management.
24:14 A Case Report Form (CRF) is crucial in clinical trials as it contains all study information, ensuring data collection aligns with protocols and regulatory standards, promoting effective data collection and safety of data sharing among teams.
-Importance of Study Protocol and Data Collection. Protocols guide data collection, ensuring compliance with study requirements, including study design, dosages, and blinding, vital for effective data collection and regulatory adherence.
-Components of a CRF. A CRF includes study title, investigator details, subject ID, inclusion/exclusion criteria, dosage information, and signatures, essential for documenting individual subject data in clinical trials.
-Role of Raw Data in Clinical Trials. Raw data sets, like SAS data sets organized by domains, serve as inputs alongside CRFs and metadata, providing comprehensive subject information for analysis and reporting.
32:20 Understanding the importance of maintaining variable names in compliance with regulations is crucial in data management. Ensuring variables adhere to specific rules like character limits and special characters is essential for data integrity and consistency.
-Importance of variable naming conventions in data management. Adhering to rules like character limits and special characters ensures data integrity and consistency.
-Differentiating between CRF and ACRF in clinical data management. ACRF contains more detailed information and requires validation by the team lead.
-Process of creating and validating ACRF in clinical data management. SAS programmers play a role in generating ACRF, which is then validated by the team lead.
40:26 The video discusses the process of creating an Excel file to store information from a CRM system, identifying variables, and converting the Excel file into an XFDF file for annotation.
-Creating an Excel file to store CRM information and identifying variables are crucial steps in the process.
-Converting the Excel file into an XFDF file for annotation involves determining color formats, priorities, and domain placements.
-The roles of a clinical research associate and a clinical data management team in producing data are highlighted in the discussion.
48:31 Understanding the steps involved in programming for SDTM implementation is crucial for SAS programmers. It involves mapping specifications, variables selection, and creating SDTM specification Excel based on ACRs.
-Importance of mapping specifications and variables selection in SDTM programming. It ensures accurate data representation and table creation in SAS.
-Creating SDTM specification Excel based on ACRs for proper data organization. It includes details like variable types, lengths, and source information essential for programming.
-Role of TLs, protocol documents, and SDTM implementation guides in SDTM programming. They provide necessary information for creating SDTM specification Excel.
56:34 The process of creating SDTM output involves steps like preparing annotated CRF, mapping specifications, programming plan, and converting SAS datasets to XPT files for submission using software like Pinnacle 21.
-Importance of teamwork in SDTM creation. Team members leverage existing guidelines and collaborate on programming plan allocation for efficient workflow.
-Conversion of SAS datasets to XPT files. Explanation of using software like Pinnacle 21 for creating XML files for submission as study results.
-Validation and submission process. Emphasis on creating validation nodes, defining XML files, and submitting study results for SDTM output.
1:04:36 The video discusses starting with SDTM mapping specification, understanding different domains in SDTM, and the importance of SDTM guidelines for programming. It emphasizes the need to follow guidelines for domain and variable names, data types, formats, and core rules.
-Importance of understanding different domains in SDTM like special purpose domains, interventions, events, and findings, along with trial design models.
-Explanation of SDTM guidelines including writing domain and variable names, allowed data types and formats, core rules, identified variables, and timing variables.
-Planning to complete SDTM guidelines in upcoming classes and then moving on to special purpose domains for programming.
CDISC - Clinical Data Interchange Standards Consortium
SDTM - Study Data Tabulation Model
can u upload explation of project too...?
Can you share the documents related to entire lecture along with dataset
How much is fee for SAS programme