Our Consultative Approach Expert guidance, not just execution.
We serve as strategic CDM partners throughout the study, helping sponsors understand their options, evaluate tradeoffs, and make informed decisions about data collection, technology, standards, integrations, data review, and database lock. Our team brings practical industry experience to anticipate risks, explain downstream impacts, and guide each sponsor toward an approach that fits the study and development program.
Whether a sponsor has an established data management organization or needs more hands-on guidance, we adapt our level of support while maintaining clear recommendations, transparent communication, and accountability for delivery.
Get the optimal solution for your clinical trial, one built to take your study from protocol review and study startup through database lock and archival, as quickly and efficiently as possible, without compromising data quality or integrity. We offer end-to-end data management, from protocol review and CRF design through database build, ongoing data review, database lock, and archival. Our global team collaborates with clinical operations, biostatistics, statistical programming, medical, and safety teams to keep data and downstream deliverables aligned, developing partnerships rooted in quality, efficiency, and transparency. The result: cost-efficient data management, faster time to database go-live, a functioning and intuitive clinical database, expedited database lock, and ultimately, accurate and clean clinical trial data.
HOW IT WORKS
From first-patient-in to database lock, here's how we keep your data clean and your timeline on track.
01
We ask questions to drive key interim and final deliverables to completion, based on our niche knowledge of what is needed and the steps to achieve each milestone.
02
From protocol review through database lock, we establish clear requirements, coordinate cross-functional review, build and test the database, manage data review and reconciliation, and plan lock activities. We make dependencies and decisions visible so sponsors understand what is needed, who owns it, and how each activity affects study timelines and downstream deliverables.
Veristat Expertise in Clinical Data Management
We work smart. Databases are designed with the end-users in mind.
Fit-for-Purpose Technology and Database Design
Databases designed for end users. We design databases around protocol requirements and end-user workflows, using conditional logic and other platform capabilities, where appropriate, to present relevant fields and reduce unnecessary data entry.
Fit-for-purpose technology. We evaluate study complexity, endpoints, integrations, timelines, and end-user requirements to help select the EDC and supporting technologies best suited to each trial, rather than applying a single-platform approach.
Standards and Data Quality
SDTM-aligned from the start. Our CRF designs use the most up-to-date SDTM implementation guides, so your data is standards-ready long before you reach submission.
Standards-based CRF design. We maintain a library of standard CRFs developed using CDASH standards. These provide a consistent starting point and are tailored to each study's protocol, endpoints, and other requirements, supporting efficient database development, consistent data collection, and streamlined downstream mapping to SDTM for regulatory submission.
Risk-based data review. We tailor data review activities to the study's critical data, endpoints, and identified risks, combining programmed validation, targeted manual review, reconciliation, and documented escalation processes to focus attention where it matters most.
Connected, Cross-Functional Delivery
Documentation that respects your sites' time. Our CRF Completion Guidelines provide practical instructions tailored to the protocol, database, and data collection requirements.
Biostatisticians who stay in the room. We think proactively about our downstream stakeholders and how to balance each team member's needs throughout the entire data management lifecycle. Our biostatisticians play an active role not just in initial CRF development, but in any mid-study changes that may impact programming and subsequent timelines and deliverables.
Connected data that supports earlier decisions. We plan for data across EDC, laboratory, safety, eCOA or ePRO, RTSM, imaging, and other study-specific sources, defining the transfer, integration, validation, and reconciliation requirements for each study. Through integrated reporting and dashboards, we provide sponsors with timely visibility into data quality, query status, study progress, and emerging trends, so they can make informed decisions throughout the trial, not only at database lock.
Responsible Innovation
Building the next generation of Clinical Data Management with responsible AI. Veristat is actively advancing a phased program to embed AI-assisted automation across the CDM lifecycle, from database design and build through data review and reconciliation. Initial priorities include accelerating database development, strengthening operational reporting, identifying potential data issues earlier, and reducing repetitive manual review. These capabilities are being introduced through controlled pilots and a defined quality and governance framework, with experienced CDM professionals retaining responsibility for review, testing, approval, and decision-making.
Veristat's Offerings
Explore our clinical data management services:
Consulting
Strategic program planning, protocol review, EDC selection, etc.
Data Validation Programming and Testing
Development and testing of programmed edit checks, along with study-specific specifications for automated and manual data review.
Case Report Form (CRF)
Design. Built utilizing the most up to date SDTM implementation guides.
Database Design, Development, and Maintenance
A functioning, intuitive database built to support your trial from go-live through lock.
CDM service offerings
CDM strategy, planning, and study documentation
Protocol review and CRF design
EDC selection, database design, build, and maintenance
Edit check programming, database testing, and user acceptance testing
Data review, cleaning, and query management
Medical coding using MedDRA and WHODrug
SAE and other safety data reconciliation
Laboratory and external data integration, validation, and reconciliation
EDC training and study support
Database lock, archival, and data transfer
NEXT STEPS
What's Next in the Drug Development Process
Standards Implementation.
Ensure your data meets SDTM and ADaM standards for regulatory submission.
Data-Driven Strategies to Advance Development and Approval of ...
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Four Pillars of Success in Neurology Trials
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Guiding an Emerging Biotech's First Phase I Oncology Trial
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Clean data is not simply a checkpoint. It is the foundation for reliable analysis and decision-making.
The direction of your clinical program depends on the data behind it. Veristat builds and manages clinical trial data with downstream decisions in mind, creating a clean, reliable foundation for statistical analysis, regulatory submission, and a clearer understanding of what your program should do next.
Veristat maintains a library of standard CRFs developed using CDASH standards. These standards-based CRFs provide a consistent starting point and are tailored to each study’s protocol, endpoints, and other requirements. This approach supports efficient database development, consistent data collection, and more streamlined downstream mapping to SDTM for regulatory submission.
Veristat manages database changes through an established Mid-Study Update process. Proposed changes are documented and assessed with the appropriate cross-functional stakeholders for potential impacts on data collection, validation rules, integrations, existing data, statistical programming, timelines, and downstream deliverables. Approved changes are developed and tested in a controlled environment, undergo user acceptance testing as applicable, and are implemented through documented change control with appropriate communication, training, and updates to study documentation.
Veristat defines and manages the transfer, integration, validation, and reconciliation requirements for external study data. The approach is tailored to each study’s data sources, systems, transfer methods, review requirements, and downstream uses.
