Clinical Data Management and Integrated Data Delivery
Capture, manage, and deliver high-quality clinical data that supports faster, more confident decisions with Altasciences’ integrated data management capabilities.
Clinical data management is essential to ensuring patient safety, demonstrating efficacy, and enabling successful regulatory submission. From study start-up through database lock, the quality, integrity, and accessibility of your data directly impact development timelines and outcomes.
Altasciences goes beyond traditional data management by connecting data strategy, cross-functional collaboration, and analysis readiness within a unified development approach. This ensures your data is available, compliant, and structured to support efficient analysis and decision-making across your program.
Smarter, Earlier Decisions Through Integrated Data
Altasciences enhances data management by collaborating cross-functionally to develop strategy with the end in mind. As part of our integrated platform, data management is closely aligned with biostatistics, PK/PD, and clinical operations. This ensures that data supports not only collection and reporting, but also ongoing study oversight and analysis.
Through this approach, we can:
- Provide data visualization to make strategic decisions
- Support timely interim analyses and cohort decisions
- Ensure datasets are analysis-ready throughout the study lifecycle
- Reduce delays caused by data discrepancies or late-stage corrections
- Maintain consistency across clinical, laboratory, and external data sources
Data is also structured to support advanced analysis, ensuring that insights can be generated efficiently as your study progresses.
This allows for early identification of any erroneous data, therefore minimizing any potential errors post-database lock. This, in turn, helps facilitate high-quality statistical outputs that assist the development of clinical study reports and submission packages.
Built to Accelerate Early-Phase Development
Supporting early-phase programs is central to our mission to safely accelerate drug development.
Our data management teams bring experience across a wide range of study designs, therapeutic areas, and development settings, supporting programs from first-in-human through early patient trials and clinical proof-of-concept studies.
We design data strategies aligned with the complexity and pace of each program, ensuring that safety, clinical, laboratory, and external data are consistently captured, integrated, and available to support study oversight and decision-making to enable:
- Rapid database build and deployment
- Timely and accurate data capture and review to support monitoring and study progression decisions
- Integration of clinical, PK, biomarker, and third-party data sources
- Early identification of trends, inconsistencies, and emerging risks
- Consistent data standards and structure across studies and phases
Tailored Data Management Services Across the Study Lifecycle
Customized data management services are available on a per-project or full-time equivalent (FTE) basis, according to your needs. Using a range of electronic data capture (EDC) platforms, we create project-specific solutions that enable real-time data review, accelerate decision-making, and maintain a strong focus on participant safety and data quality.
Our experts offer:
Study Planning and Set-Up
During study start-up, our data management experts work closely with you and study teams to establish efficient processes, ensure regulatory alignment, and lay the foundation for high-quality data collection throughout the trial.
- Protocol review to align data collection strategy with analysis requirements
- Development of Data Management Plans and validation strategies
- CDASH-aligned case report form (CRF) and eCRF design
- EDC, RTSM, and EPRO platform selection tailored to study requirements
Database Design and Build
Our team designs and configures study databases that support efficient data collection while minimizing complexity for sites and study personnel. Leveraging proven methodologies and reusable components, we help accelerate study start-up timelines without compromising quality.
- Protocol-specific database design and configuration
- Efficient build timelines aligned to study start-up (typically 4 to 6 weeks)
- Reusable CRF libraries to accelerate development
- Validation and testing prior to go-live
Study Execution and Data Review
Throughout study conduct, we provide proactive data review and oversight to ensure data integrity, support participant safety monitoring, and facilitate informed decision-making. Our collaborative approach helps identify and resolve issues quickly while maintaining study momentum.
- Timely and accurate data capture, cleaning, and validation
- Ongoing query management and resolution
- Collaborative data review sessions with study teams
- Integration of external vendor and laboratory data
- Ongoing data visualizations and provision of site-level query metrics
- Rapid availability of interim data outputs, including safety and biomarker insights
Data Integration and Analysis Readiness
As studies progress, we prepare data for efficient statistical analysis by ensuring consistency, completeness, and alignment with study objectives.
- Alignment with biostatistics for analysis readiness and timely database lock
- Creation of standardized and derived datasets
- Structured datasets to support advanced statistical and modeling analysis
Submission-Ready Deliverables
We provide comprehensive, regulatory-ready deliverables designed to support submissions to global health authorities. Our team follows industry standards and established quality processes to ensure datasets and supporting documentation are complete, accurate, and inspection-ready.
- CDISC-compliant datasets such as SDTM and ADaM
- Annotated CRFs and define.xml
- Data validation using Pinnacle 21
- Complete, regulatory-ready data packages
Our team has worked with numerous regulatory agencies, including the FDA, Health Canada, European Medicines Agency (EMA), United Kingdom MHRA, and ANVISA. Altasciences’ data management experts draw on the regulatory expertise of our organization to ensure that all aspects of clinical trial data management comply with the relevant regulatory requirements.
Explore Altasciences’ Full Range of Supporting CRO Services
Related Resources
FAQs
How does clinical data management impact study timelines and decision-making?
Effective clinical data management ensures that study data is captured, reviewed, cleaned, and made available for analysis as quickly as possible. Timely access to high-quality data supports faster interim analyses, cohort progression decisions, safety reviews, and overall study oversight, helping sponsors maintain development momentum and avoid delays.
How do integrated clinical data management services improve data quality?
An integrated approach aligns data management with biostatistics, PK/PD, and clinical operations from the start of a study. This collaboration helps identify potential data issues earlier, reduces discrepancies and rework, and ensures datasets are consistently structured to support analysis, reporting, and regulatory requirements.
Can Altasciences’ clinical data management support the integration of data from multiple sources?
Yes. Modern clinical studies often require the integration of data from multiple sources, including laboratories, biomarkers, PK assessments, wearable devices, imaging vendors, and other third-party systems. Our clinical data management teams help ensure these data sources are standardized, reconciled, and integrated into a single, analysis-ready dataset.
How does clinical data management support regulatory submissions?
Clinical data management plays a critical role in preparing submission-ready datasets and documentation. This includes developing CDISC-compliant datasets such as SDTM and ADaM, performing data validation, supporting database lock activities, and preparing regulatory deliverables such as define.xml files and annotated CRFs to facilitate efficient regulatory review.
What should I look for when selecting a clinical data management partner?
Sponsors should look for a partner with expertise in early-phase development, strong regulatory knowledge, flexible technology solutions, and the ability to integrate data management with other key functions, such as biostatistics, PK/PD, and clinical operations. A collaborative, cross-functional approach can improve data quality, accelerate analysis, and support more informed development decisions.