CDISC standard has become a set of global data standards that can be used in clinical study, covering the full life cycle of clinical researches. After nearly 20 years of development and continuous version upgrades, CDISC standard can improve the quality and efficiency of clinical research and drug review, and to facilitate all stakeholders involved in researches to exchange the study data and communicate the outcomes. CDISC standard has been or is to be adopted as standard format in data submission by multiple regulatory authorities, and more widely implemented by the global pharmaceutical community. CDISC standard is gradually adopted in China. The feasibility and roadmap of CDISC standard as the Chinese data submission format requirements are undergoing exploration and piloting further.

Download full-text PDF

Source

Publication Analysis

Top Keywords

cdisc standard
24
data submission
8
standard
7
cdisc
5
[overview cdisc
4
standard implementation
4
implementation china]
4
china] cdisc
4
standard set
4
set global
4

Similar Publications

Faced with heterogeneity of healthcare data, we propose a novel approach for harmonizing data elements (i.e., attributes) across health data standards.

View Article and Find Full Text PDF

Introduction: The value of Source Data Verification (SDV) has been a common theme in the applied Clinical Translational Science literature. Yet, few published assessments of SDV quality exist even though they are needed to design risk-based and reduced monitoring schemes. This review was conducted to identify reports of SDV quality, with a specific focus on accuracy.

View Article and Find Full Text PDF

[Interpretation of the CDISC therapeutic area user guide for traditional Chinese medicine- acupuncture].

Zhongguo Zhen Jiu

November 2024

Second Affiliated Hospital of Guangzhou University of CM, State Key Laboratory of Dampness Syndrome of TCM, Guangzhou 510120, Guangdong Province, China; Guangdong Hospital of TCM, Guangzhou 510120; Science and Technology Innovation Center, Guangzhou University of CM, Guangzhou 510405, Guangdong Province.

Improving research data quality is a crucial aspect of high-quality clinical research of acupuncture and moxibustion. The Clinical Data Interchange Standards Consortium (CDISC) has developed a series of standards to support the collection, tabulation, and analysis of clinical research data. To enhance the efficiency and quality of clinical research in acupuncture, as well as to facilitate the integration, sharing, and secondary analysis of data from multiple similar studies, CDISC has developed and released the CDISC therapeutic area user guide for traditional Chinese medicine acupuncture (TAUG-TCM-Acupuncture).

View Article and Find Full Text PDF

Toward widespread use of virtual trials in medical imaging innovation and regulatory science.

Med Phys

December 2024

Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Departments of Radiology and Electrical & Computer Engineering, Medical Physics Graduate Program, Duke University, Durham, North Carolina, USA.

Article Synopsis
  • * Virtual trials (in silico trials) offer a viable alternative by employing computational models, but there’s a pressing need for a unified framework that the medical imaging community can adopt.
  • * Essential requirements for these virtual trial frameworks include ensuring credibility through rigorous assessments, enhancing reproducibility with thorough documentation, and improving accessibility via user-friendly tools and data-sharing solutions.
View Article and Find Full Text PDF

The CDISC Standard for Exchange of Nonclinical Data (SEND) data standard has created new opportunities for collaborative development of open-source software solutions to facilitate cross-study analyses of toxicology study data. A public-private partnership between BioCelerate and the FDA/Center for Drug Evaluation and Research (CDER) was established in part to develop and publicize novel methods to facilitate cross-study analysis of SEND datasets. As part of this work in collaboration with the Pharmaceutical Users Software Exchange (PHUSE), an R package sendigR has been developed to enable users to construct a relational database from a collection of SEND datasets and then query that database to perform cross-study analyses.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!