Why Clinical Data Reconciliation Is the Backbone of Trial Integrity

New “Ask Your Biostatistician” Video

Clinical trials generate data from dozens of sources, EDC systems, laboratories, imaging vendors, safety platforms, wearables and ePRO devices. Ensuring all of it aligns is essential for clinical trial data quality, trustworthy analyses and regulatory submission readiness. This ongoing discipline, known as clinical data reconciliation, has become one of the most important components of modern trials, supporting ALCOA and compliance and protecting the integrity of evidence submitted to global regulators.

To explore this essential topic, Navitas Life Sciences has released a new episode of our “Ask Your Biostatistician” series. In this conversation, Bob Chastain (Biostatistics SME) and Dave Maslow (Clinical Data Management SME) share how reconciliation impacts trial accuracy, timelines and inspection readiness. We will not reveal their insights, the best value comes from hearing them discuss it directly.

In our latest blog, we explore more about data reconciliation and how Navitas Life Sciences can support.

Understanding the Foundation of Clinical Data Reconciliation

At its core, clinical data reconciliation, data reconciliation in clinical trials and clinical data integrity involve the structured comparison of information across different platforms to ensure that data is accurate, aligned and analysis ready. As new data enters the system, it is verified against the study database or EDC and external data matching processes to detect misalignments or missing values that may compromise downstream reporting. Once discrepancies are identified, they are logged, escalated and resolved at the site level, creating a complete, verifiable audit trail.

This work spans laboratory data reconciliation, safety data reconciliation, SAE reconciliation, medical records, imaging outputs and vendor feeds, each requiring reconciliation to ensure that what appears in the CRF reflects true clinical activity. When performed well, these processes protect the quality of the dataset and enable confident decision-making across the study.

How Data Is Reconciled Throughout the Study Lifecycle

Reconciliation is far more than a final step before database lock. It is a continuous quality process that evolves with the trial. Laboratory records, for instance, must precisely match CRF entries in terms of patient identifiers, visit dates and test details. Safety / SAE reconciliation ensures that adverse event information in the safety database fully aligns with clinical data entries, protecting both patient safety and regulatory compliance. Medical record validation ensures that source documentation supports the clinical narrative captured in the EDC.

Modern EDC platforms also support clinical data cleaning and reconciliation through automated edit checks, consistency rules and system-driven alerts that flag mismatches. These embedded capabilities reduce manual effort and help teams stay aligned even as trial complexity increases.

Collaboration is essential. Clinical data management services, clinical monitors, safety specialists, vendors and statisticians must work together to resolve discrepancies efficiently. This close coordination ensures that inconsistencies do not accumulate and that each data source contributes accurately to the full clinical dataset.

Regulatory Alignment, Documentation and Continuous Monitoring

Regulators expect data to be complete, traceable and accurate. For this reason, data reconciliation in clinical trials is directly tied to ICH-GCP, FDA and EMA expectations. Timely issue resolution prevents errors from affecting patient listings, TLFs, CSRs, or submissions and ensures the trial maintains clinical trial data integrity.

Documentation is equally important. Each discrepancy, resolution and communication step must be clearly recorded so that inspectors can follow the logic and verify the completeness of the dataset.

Because trials evolve continuously, reconciliation must be ongoing rather than periodic. As new laboratory files arrive, safety updates are generated or external vendor feeds are refreshed, teams monitor and compare incoming data to maintain real-time alignment. This proactive approach prevents late-stage surprises and supports smoother clinical database lock timelines.

How Navitas Strengthens Data Integrity Across Every Study

Navitas Life Sciences brings together experts in biostatistics support, statistical programming and clinical data management services who collaborate seamlessly to maintain clinical trial data quality. Reconciliation is built into our workflows from study startup through submission, ensuring that quality controls are applied consistently throughout the trial.

Our teams design reconciliation strategies tailored to each protocol, incorporating the best of tools, risk-based methodologies and AI in clinical data management insights to detect issues early. Through strong partnerships with platforms such as Medidata and Oracle, Navitas ensures that EDC and external data matching is efficient, compliant and well-documented.

This commitment to excellence has earned Navitas recognition as a Major Contender in the Everest Group’s CDM Operations Assessment, reinforcing the strength and rigor of our global delivery model.

Clinical trials run on data. Data integrity depends on reconciliation. And reconciliation demands the right expertise, tools and collaboration, all of which Navitas Life Sciences provides.

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