At Metis Consulting Services, we are thrilled to announce that This Summer, 2023, is the launch of our Data Management division. The increasing focus on the importance of data in the pharmaceutical and biotech industry is driving a need. It is crucial to have robust processes for collection, cleaning, and managing study data effectively. This is where Data Management (DM) comes into play.
What is Data Management?
Data management encompasses the set of processes to ensure the collection, cleaning, and management of research data in a manner that aligns with internal protocols and regulatory requirements. The main objective is to provide high-quality information that is complete, statistically sound, reliable, and error-free.
Why is Data Management vital for sponsor organizations?
Sponsor organizations bear the responsibility of providing vast quantities of data to demonstrate the effectiveness, efficacy, and safety of their medicinal products. From the early stages of development, data is crucial in justifying the transition from bench to human trials. Good Clinical Data Management (cGCDM) practices aim to provide duplicate-free, complete, and up-to-date versions of critical enterprise data entities, including products, compounds, studies, investigators, partners, and clients.
Responsibilities of Data Management
Data Management encompasses a range of responsibilities. We design and validate clinical databases. DM is responsible for developing coding, reporting, workflow, and data transfer plans. We resolve database issues and select appropriate electronic data capture systems to streamline data collection.
Phases and Cycles of Data Management
The data management process can be divided into three phases: start-up, conduct, and closeout. However, it is essential to note that there are also steps before, after, and in between these phases.
Before the start-up phase comes the planning stage. This is where decisions are made regarding the database to be used, the team involved in decision-making, clean build requirements, data review processes, and more.
The cycles of data management include:
- Setup: Prepare the overall plan, database, and forms.
- Collect: Gather data throughout the study period.
- Assure: Confirm the plan, tools, and data meet requirements, including data quality.
- Review: Identify and monitor issues or risks.
- Preserve: Ensure data remains accessible for future use and integration.
- Analyze: Identify information present in the data and employ suitable analysis tools.
- Lock: Present consistently presentable data.
Best Practices for Effective Data Management
Implementing methodologies and best practices is integral to successful data management efforts. Some key techniques include:
- Building strong file naming and cataloging conventions
- Carefully considering metadata for data sets
- Ensuring proper data storage
- Maintaining thorough documentation
- Cultivating a strong data culture
- Upholding data quality, trust, security, and privacy
- Investing in quality data management software
The Importance of High-Quality Data
Clinical trials rely on data to generate answers to research questions, providing evidence to support hypotheses. The quality of the data is paramount for its suitability in statistical analysis. Continuous culling during the study ensures accurate and easily analyzable data by removing deviations and errors in entry. This process guarantees complete data with minimal variation and adheres to statistical levels determined by individual teams or compliance requirements.
Adhering to Industry Standards
Of course, adherence to industry standards is critical to ensure the integrity and compatibility of collected data. There are many Standards, such as CDISC (Clinical Data Interchange Standards Consortium), CDASH (Clinical Data Acquisition Standards Harmonization), and SDTMIG (Study Data Tabulation Model Implementation Guide for Human Clinical Trials.) Each of these can play an instrumental role in harmonizing the consistency and interoperability of data across various stakeholders.
At Metis Consulting Services, our Data Management division is firmly committed to helping organizations streamline their data processes and enhance data quality. Metis’ DMS aids in ensuring compliance with regulatory standards and internal protocols. Our team of experts has your organization in mind when they come to you. It will not be a One Size fits all approach. They are equipped with the knowledge and experience to design tailored data management plans, resolve database issues, and select efficient data capture systems.
Feel free to contact us to learn more about how we can support your data management needs.
Want to learn more?
Want to learn more about the intricacies of data management in the pharmaceutical industry? Tune into our Podcast “Queens of Quality” for in-depth discussions with industry experts and gain valuable insights into the world of data management in the Pharmaceutical Industry. Don’t forget to stay connected with us on “LinkedIn” for the latest updates.
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