✨ Data Cleaning Overview

Data Cleaning refers to manipulation of the input dataset to create an analysis-ready dataset for the calculation of PK parameters. These manipulations include the addition of new columns to the dataset, conversion of BLQ samples to analyzed values, and preparation of exclusion columns to exclude individual subject profiles or individual records. All data cleaning steps are performed sequentially and at the end of each step the output is saved and included in the final output. Users can verify the results in the output.

Users can review specific rules from the menu on the left side of the documentation site. For each rule you will find an explanation of the rule, a guided walkthrough of setup for the rule, and the JSON structure for that rule.