3 Effective Practices To Manage Clinical Trial Data Through Metadata Repository


3 Effective Practices To Manage Clinical Trial Data Through Metadata Repository

The healthcare landscape is progressing continuously. More investments, research, and innovation are dedicated to the industry to ensure that quality healthcare products and services are accessible to a bigger population. According to the National Institutes of Health (NIH), a big chunk of their 2021 budget was invested in medical research. 

A prominent part of medical innovation is the discovery of new diseases, treatments, and medication through an evidence-based exploration known as a clinical trial. Developers and researchers taking part in clinical studies are upheld by high standards imposed by regulatory bodies, making clinical data quality a pivotal component of its success. 

In this article, you'll learn how researchers maintain or improve their clinical data management (CDM) practices with the help of a metadata repository.

What Is A Metadata Repository?

Data is the most significant measure of a clinical trials success. Without science supported by accurate data, a clinical study could fail. Clinical researchers can use a metadata repository to house all types and complexities of data. Essentially, it is a database that stores data about other data.

According to Formedix, building an efficient metadata repository is beneficial in clinical research in many ways, such as building studies faster, improving their quality, and reducing the overall costs of the study build. However, you can only attain these benefits if you use your metadata repository correctly.

With this in mind, here are some ways to manage your clinical trial data with a metadata repository:

  1. Choose The Right Clinical Data Repository Software 

Clinical study software assists the entire research from conception to finish, which involve processes such as collection and analysis of clinical study data, metadata management, CRF (case report form) design, and protocol management. For a well-rounded tool for your clinical study, consider choosing from these three types:

  • Integrated Clinical Study Automation Software: This type of clinical trial software focuses on automating certain parts of a clinical trial. It is an integrated, cloud-based tool that assists with metadata management, standards governance, and more, with built-in Clinical Data Interchange Standards Consortium (CDISC) compliance and validation features.
  • Electronic Data Capture System EDC: An EDC allows users to collect patient data during clinical research. They focus on data collection, analysis, storage, and integration with electronic health records a leading advantage over other software types.
  • Clinical Trial Management System CTMS: Lastly, the CTMS software is used for planning and analyzing clinical trials end-to-end. Although they cater to the entire clinical research process, a CTMS is often integrated with the first and second software types. 

Regardless of which type you choose, keep in mind that they're all automated and work well with metadata repositories. Therefore, you can achieve improved data quality, clinical trial efficiency, and fewer resources consumed. 

  1. Establish Governance

A successful clinical trial should be governed by standards, principles, and regulations to achieve quality studies, prevent misconduct, and promote good practice. A critical part of data governance is metadata management. 

Some challenges in clinical data management are due to some ill-fitting organizational standards. Building a seamless governance process offers understanding and control of your clinical trial workflow, increasing the compliance and accuracy of your clinical metadata. 

A huge benefit of data governance is its customizability for your company's process, allowing researchers to create an organizational life cycle for standards that evolve over time. Since organizational measures are kept in one place, they can also be reused for new clinical studies to fit research-specific requirements. Reusing these resources can help maintain data quality and consistency. 

  1. Improve Your System's Traceability 

The strength and reliability of a clinical study highly depend on the source data and reproducibility of clinical processes conducted. How is this specific piece of information derived? Where did you store the new data? An essential step of building an excellent clinical study is possessing traceability, which means you should trace your data on the entire workflow, including its origin, location, and application.

Using a metadata repository is an excellent practice in maintaining and improving clinical data traceability. Document statements can be drawn back to the raw data when information is stored and tracked in this database. 

Meanwhile, the pharmaceutical landscape uses blockchain technology to improve the traceability of medications in the clinical trial supply chain. This allows patients and associated individuals to join the network to record data, moving logged information to appropriate systems with access to view, edit, and store the specific data. Aside of enhancing traceability, using the blockchain mechanism in clinical trial supply chains boosts the study's validity and assures completeness of the entire process. 

Key Takeaway 

Streamlining a clinical trial process isn't as easy as you might think. Thanks to technological advancements like the design and implementation of metadata repositories, healthcare institutions can perform safer and better-quality clinical trials that appropriately target diseases and health conditions. By implementing these practices into your own clinical studies, hopefully, you'll be able to deliver more progressive solutions to health challenges in the present and future.

Updated 10:35 AM UTC+8, 28 Sep 2022
Ken Karlo Staff
Ken Karlo Staff
A KenKarlo's staff that's responsible for publishing articles related to technology, press release, news, guest posts, and other category.

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