Derive ADSL datasets from SDTM domains using admiral and dplyr.
npx skills add https://github.com/RConsortium/pharma-skills --skill admiral-adsl
Please help me install this Agent Skill. Skill: admiral-adsl Source: https://github.com/RConsortium/pharma-skills/tree/main/admiral Command: npx skills add https://github.com/RConsortium/pharma-skills --skill admiral-adsl
This Skill automates the derivation of ADaM Subject-Level Analysis Dataset (ADSL) from SDTM domains, simplifying the process of creating subject-level data for clinical trial submissions.
Generate an ADSL dataset from the provided SDTM input files using the admiral-adsl skill.
High-intent search queries and answers about installing and using this skill.
You derive an ADSL dataset by automating the transformation of SDTM DM, EX, DS, DV, and MH domains into subject-level analysis data, generating standard variables like treatment dates, demographics, and population flags.
ADSL derivation requires SDTM DM, EX, DS, DV, and MH domains as input to automatically generate subject-level variables including treatment dates, disposition events, demographics, and population flags for clinical trial submissions.
Yes, you can use admiral with dplyr and lubridate to automate ADaM subject-level dataset creation, streamlining the derivation of ADSL from SDTM domains while reducing manual data preparation errors.
The best way to generate population flags and treatment dates is to automate ADSL derivation from SDTM domains, which systematically produces standard subject-level variables required for clinical trial submissions.
Yes, you need pharmaversesdtm along with admiral, dplyr, and lubridate to derive ADSL from SDTM data, as these libraries provide the necessary functions and example data for clinical trial processing.
Automating ADaM ADSL derivation is limited to processing standard SDTM DM, EX, DS, DV, and MH domains, requiring properly structured input files and the specified R package dependencies to function correctly.
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