ADNCA Explained: The Next Generation of Non-Compartmental Analysis and the Top Questions Answered

ADNCA was purpose-built to close the gap between raw clinical data and analyzed PK outputs. As a validated ADaM subclass, it includes over 50 NCA related variables—capturing everything from dosing and timing to exclusion logic. That means no more ad hoc formatting or last-minute manual adjustments.

Common Question: Is ADNCA just a renamed ADPC?
Answer: No. ADPC is informal and lacks structure. ADNCA is a formal CDISC standard with clearly defined structure, variables, validation rules, and traceability—making it suitable for submissions and cross-study consistency.

ADNCA aligns directly with FDA and global regulatory expectations. Submitting NCA results in this format helps reviewers validate your outputs faster, reducing the risk of information requests (IRs) and delays.

Common Question: Is ADNCA required?
Answer: Not yet—but regulators are beginning to expect it. Submitting ADNCA now signals diligence and transparency, setting you up for faster reviews and fewer surprises.

Expanded Integration Across the Workflow with P21 Tools

Phoenix® users performing PK analysis can enhance efficiency by leveraging integrated Pinnacle 21® (P21) tools that automate the entire PK workflow—from data collection to submission. P21 Data Exchange ensures high-quality, vendor-compliant data aligned with sponsor specifications, streamlining conversion to SDTM, the foundational dataset for PK analysis. The P21 Clinical Metadata Repository (CMDR) enables reuse and governance of metadata and standards like SDTM and ADaM, supporting consistency across studies. With the P21 Mapping Tool, users can efficiently create and manage specifications to convert collected data to SDTM and SDTM to ADaM, including datasets like ADNCA, reducing manual effort and error. Finally, P21 Enterprise (P21E) validates ADNCA and other ADaM datasets to ensure regulatory compliance, using the same platform as the FDA and PMDA, enabling seamless and automated validation.

ADNCA works natively with Phoenix WinNonlin®, Certara’s flagship PK analysis platform. To ensure Phoenix understands your data, you’ll need to perform a one-time mapping of CDISC ADNCA key column names within Phoenix. Once this initial setup is complete, there’s no need for complex mapping or manual data entry—just plug in your ADNCA dataset and go.

Phoenix templates also enable automated generation of tables, figures, and listings (TFLs), supporting efficient interim and final analyses.

Common Question: Can I use ADNCA before database lock?
Answer: Yes. Many teams use ADNCA structures with preliminary data to begin analysis early, then refresh for final submission—accelerating timelines without compromising quality.

The structure of ADNCA supports streamlined, repeatable analysis. Variables like MRRLT (Modified Relative Time) and TRTRINT (Treatment Interval) allow for consistent time handling and multiple dose regimens—whether you’re analyzing parent drugs, metabolites, or both.

Common Question: Can ADNCA handle exclusions and outliers?
Answer: Absolutely. Exclusion flags and metadata rules are clearly defined in the dataset, allowing you to exclude subjects or timepoints while maintaining transparency for regulators.

By adopting ADNCA now, you’re not just keeping up—you’re getting ahead. The standardization ADNCA provides simplifies collaboration, improves traceability, and minimizes rework across studies and teams.

Common Question: What’s the best way to build ADNCA specifications?
Answer: Create a metadata repository and reuse specs across studies. ADNCA’s consistent structure makes it easy to standardize your approach, saving time and reducing errors.

From simplifying data structure and accelerating timelines to improving regulatory confidence, ADNCA is reshaping how we approach non-compartmental analysis.