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The Future of Clinical Trial Validation

Eliminate double programming, increase submission quality, and guarantee confidence with Full Study Traceability from raw data to submission.

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Double programming is flawed

Double programming, considered the gold standard for validation, is fundamentally flawed. It assumes that if two programmers independently produce the same result, it must be correct. In reality, good specifications are hard to write, misunderstandings common, and true independence is often compromised by discussions, code sharing, and deadline-driven shortcuts. Even two programs producing the same output do not guarantee SAP and specification adherence.
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The consequences are serious. Double programming wastes time, money, and resources, forcing programmers to duplicate effort instead of improving quality, efficiency, and performing additional analyses. It is outdated, inefficient, and needs to be replaced.

The source of truth of a trial is its code interacting with data

Replacing double programming requires a paradigm shift. Existing standards provide no insights into data transformations, requiring additional documentation like define-XMLs, SDRGs, and ADRGs to explain derivations in natural language that are difficult to maintain and therefore prone to errors. While CDISC adherence addresses cross-industry variations in reporting, it fails to provide full transparency in how derivations and results were created for any specific study.

The source of truth of a clinical trial is its code and interaction with data. Code defines how raw data is imported, analyzed, and used to create results. However, derivations are obfuscated by proprietary macro systems, spread across many files and 1000s of lines of code, and often left unchecked by peer review. A new validation process must integrate specifications, data, metadata, and code. The solution lies in true end-to-end traceability, linking all specifications, data, and transformations, from raw data to outputs. This results in increased review speed and accuracy for a confident decision making process to the benefit of human health.

Introducing Code Traceability

Code Traceability is a technology that captures every variable, dataset, format, codelist, result, and transformation in a study. It revolutionizes how we understand, communicate and validate clinical trial analyses. Code Traceability provides a complete computational representation of a study, mapping every transformation and tracking every dependency. Through our platform’s interface, it enables you to achieve absolute transparency into how specifications, data, derivations and results interact.

Instead of searching through 1000s of lines of code across multiple files, Code Traceability retrieves the exact code that generates a specific dataset, variable, or result, transparently linking variables with their sources, transformations, and destinations. Every variable can be traced step-by-step from its raw origins through SDTM and ADaM transformations, to its final output in TLFs, dramatically reducing the time spent understanding derivations and results. Onboarding, root cause analyses, communication, fixing problems, and validation become much easier.

Code-traceability enabled AI

To automate validation, our AI leverages Code Traceability to compares a variable derivation against its specification to classify it as validated or failed, alongside a confidence score. To maintain exceptionally high quality and reliability, our AI only offers validation suggestions when its confidence levels are high. In addition, Verisian detects and flags data anomalies and outliers, through a combination of advanced analytics and the latest AI methods.

Data traceability

Code Traceability enables Verisian to extend traceability to where code and data intersect, providing transparency down to individual patients and data points. Data Traceability allows reviewers to immediately understand patient strata, subgroup allocation, and filtering criteria, ensuring clarity in TLF outputs and their underlying data. With Verisian, no data transformation remains a black box, every step is documented, traceable, and transparent.

Full Study Traceability

Combining Code and Data Traceability, Verisian delivers Full Study Traceability, integrating specifications, code, data, metadata, and results. Structured review and validation become fast, transparent, and easily communicable. Analysis issues can only have two possible origins: the data or the code transforming it. With Verisian, these issues are identified in seconds, and all upstream root causes and downstream impacts instantly transparent. Any issue discovered can be managed seamlessly in the Validation Tracker and is directly tied to its exact position in the trace, making communication and fixes easy, even across stakeholder groups.

Validated by Verisian: the new validation process

The Validated by Verisian process is built on Specification Validation, Results Validation, and the Validation Tracker. By fully leveraging Full Study Traceability, it allows programming teams to eliminate double programming, enhance quality, reduce costs, and accelerate validation timelines.

The benefits of Validated by Verisian

Beyond eliminating double programming and the resulting 40% cost savings, Validated by Verisian provides the following immediate benefits.

Programming efficiency

Up to 95% time reduction in root cause analysis, issue resolution, and stakeholder communication

Faster time-to-market

Fewer regulatory inquiries and accelerated submissions through greater submission quality

Onboarding and continuous improvement

Drastically improve onboarding, knowledge transfer, training, and programming quality across the organization

Flexibility and scalability

Confidently move resources across trials with faster onboarding and maintain quality control as you scale with external partners

Faster approvals through Augmented Submissions

For regulatory authorities to validate study outcomes, they must first onboard to understand the analyses. This challenge is growing as the volume and complexity of trials increases. CDISC standards like SDTM and ADaM help to structure data, while define-XMLs, SDRGs, and ADRGs attempt to provide traceability. However, these documents merely duplicate information that should be self-evident in the data and code and are prone to inconsistencies and a lack of detail.
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The Verisian Validator replaces this fragmented approach through full Study Traceability, providing regulatory authorities unparalleled transparency into specification, documentation, data, code, and their interactions and validity. A Validated by Verisian badge signals that the most rigorous of validation processes was used before submission. It provides regulators with ultimate transparency from raw data to results and every single step in between, through an intuitive and information-complete interface, ultimately making legacy submission documentation obsolete.
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By enabling regulators to use the same validation tooling used by sponsors to ensure validity and gain submission confidence, regulatory reviews become faster, better, and require fewer inquiry-response cycles. This helps to bring safe and effective therapies to patients with greater speed and confidence.

To learn more about the Validated by Verisian process, download our white paper for an in-depth look at the key concepts.