Jetacor generates CDISC-compliant ADaM datasets from your latest SDTM extraction — making analysis-ready data available for continuous data monitoring, ADaM validation, exploratory analysis, and regulatory submission, whenever your team needs it.
From the first patient enrolled to the final regulatory package, clinical teams depend on analysis-ready ADaM datasets for safety reviews, interim analyses, exploratory work, and ongoing data monitoring. Today, each of these activities requires manually running SAS programs against the latest SDTM extraction — a process that is time-consuming, dependent on programmer availability, and repeated every time new data comes in.
When analysis datasets are generated automatically from your latest SDTM extraction, every downstream workflow that depends on ADaM data moves faster — and can run as frequently as your data is updated.
Ongoing safety monitoring and efficacy reviews require analysis datasets that reflect the most current state of the trial data. When a new SDTM extraction is available, teams need ADaM datasets updated to match — so that safety signals, enrollment trends, and endpoint data can be reviewed against what was actually collected, not a weeks-old snapshot.
With Jetacor, generating ADaM on a new SDTM extraction is a single workflow. Upload the latest extraction, run generation against your existing specification, and analysis-ready datasets are available for the monitoring review. The same derivation logic that produced the previous cut is applied consistently to the new one — ensuring continuity across reviews without manual re-programming.
ADaM validation — comparing generated datasets against expected output, checking CDISC conformance, and verifying derivation traceability — requires analysis datasets to be available, well-structured, and accompanied by the specification that defined them. When datasets are generated manually, validation scheduling depends on programmer output timelines, creating coordination bottlenecks.
Jetacor generates ADaM datasets alongside a validation-ready package. Every generation run produces the datasets, the specification metadata used to produce them, and an automated CDISC conformance report — so your validation team has everything needed to begin independent review without waiting for programmer handoff. Dataset structure, variable attributes, and derivation logic are all traceable back to the specification.
Biostatisticians and data scientists regularly need analysis datasets for exploratory work that extends beyond pre-specified analyses — subgroup investigations, signal detection, hypothesis generation, and ad hoc requests from clinical teams. Every one of these requires ADaM. Today, an exploratory question that arrives on a Monday may not have the datasets it needs until late in the week.
Jetacor makes ADaM available on demand. Any team member with access to the platform can upload the current SDTM extraction and a specification to generate analysis datasets for the domains they need. Exploratory analyses that previously waited on the programming queue can now begin as soon as the question is formed — without interrupting the production programming workflow.
Every pharmaceutical company and CRO has its own ADaM programming conventions, population flag definitions, derivation standards, and internal specification templates. A platform that generates generic, one-size-fits-all ADaM datasets does not fit into these environments — it creates rework rather than reducing it.
Jetacor is designed to be configured to your organization's requirements. Derivation logic, variable standards, population criteria, and domain conventions are driven by your specification — the same document your programmers already maintain. Jetacor applies your standards, not a generic default. The result is ADaM output that looks like your team produced it, because your specification defines how.
Jetacor was built by clinical data practitioners for the workflows that clinical data teams actually run. It understands ADaM conventions, SDTM domain structures, and the derivation standards that define CDISC-compliant datasets — without requiring configuration beyond the specification you already maintain.
The generation workflow reflects how ADaM programming actually works — specification in, datasets out — without requiring engineering expertise to operate.
Every generation run is traceable — inputs, derivations applied, domains produced, and validation results are captured and available for review.
We are onboarding a limited number of beta participants. Beta access is provided at no cost. Early participants help shape the platform before general availability.
Every analysis — whether for a safety review, an interim look, an exploratory question from the clinical team, or the final submission package — depends on ADaM data. Making that data available on demand, consistently, from the latest SDTM extraction, changes what clinical teams can see and when they can see it.
We are onboarding a limited cohort of beta participants from pharmaceutical, biotech, and CRO organizations. Beta access is provided at no cost.
Why request access?