Permissions: Administrators with the View and Study Configure privileges can add new studies to elluminate.

To configure data blinding, users need both the Blinded Data Configure and Study Configure privileges. The Blinded Data Configure privilege enables users to create, edit, import, export, and delete blinding configurations, but does not grant access to view unblinded data.

Important: Study Attributes should be configured prior to adding a new study. For more details, see the Configure Study Attributes article in the Administration section.

Studies are created within elluminate as a centralized environment to collect, organize, manage, and access all relevant data. New studies can be created manually or from an existing template.

Add a New Study

1. From the Studies page, click + Add Study in the master header. 

   Note: Studies may also be added using a template. Select Add From Template from the Templates icon. See the Create and Manage Study Templates article for more details.

   

2. If Add From Template is selected, the Select Template window opens.
3. Select the template to use and click Select.
   

The Add Study window opens. Five tabs are used to define the study configuration: Configuration, Standards, Dictionaries, Settings, and ETL.

Tip: Click Save only after completing all five tabs. Saving closes the Add Study window. If the study was saved before completing all tabs, go back into the study and edit it.

Complete the Configuration Tab

Use the Configuration tab to configure key study details.

Note: Drop-down menus provide study attribute selections configured for the URL.

Note: Only Study Name and Compound are required on this tab. However, selecting a Compound, Therapeutic Area, and Program is recommended to ensure proper grouping in the CDA and CTOA Analytics apps.

1. Study Name: Enter the required name (2-24 characters, must begin with a letter or number; underscores, hyphens, and spaces are allowed after the first character; special characters are not allowed). Invalid entries will highlight the field in red and disable saving.
2. Compound: Select from the drop-down menu (required).
3. Description: Enter a description of the study.
4. Phase: Select from the drop-down menu. 
5. Indication: Enter the indication.
6. Therapeutic Area: Select from the drop-down menu.
7. Program: Select from the drop-down menu.
8. Program Type: Select the applicable checkbox(es) to indicate whether the study includes randomized and/or stratified subjects. 
9. Blinding: Select from the drop-down menu. For blinded studies, select an option that indicates the study is blinded.
10. Control: Select from the drop-down menu.
11. Study Type: Select from the drop-down menu.
12. Primary Endpoint: Select from the drop-down menu.
13. Healthy Subjects: Select Yes or No.
14. Select the Standards tab.

Complete the Standards Tab

On the Standards tab, select the applicable CDISC standards for the Data Quality module and the study. Use the drop-down menus to choose from the available versions in Pinnacle21. 

• SDTM Standard (CDISC Study Data Tabulation Model)
• SDTM CT Date (SDTM Controlled Terminology)
• ADaM Standard (CDISC Analysis Data Model)
• ADaM CT Date (ADaM Controlled Terminology)
• Define-XML Standard 

Note: The selected standard versions are used for Data Quality only. Custom standards, non-CDISC standards, or versions not listed on this screen can be applied separately in Mapper or Validator.

Click the Dictionaries tab.

Complete the Dictionaries Tab

Use the Dictionaries tab to select the MedDRA version, UNII Date, and NDF-RT Date for the study. Use the drop-down menus for each selection.

Click the Settings tab.

Complete the Settings Tab

Configure study operational settings on the Settings tab. 

Note: When creating a new study, only modules or products for which the client holds an active license will be available to enable and will appear in the Add / Edit Study window under the Settings tab. 

• Active (default): This study is visible to authorized users (without Administration or Study Configure privileges) on their Home Page. 
• Ongoing (default): This study is active. Toggling off designates it as legacy, stopping scheduled imports 30 days after the 'Ongoing / Legacy As Of' date. Only eClinical Administrators can change this setting. 
  • Ongoing As Of: This defaults to the study's creation date; update it using the calendar picker or by typing.

• Blinded Data: Toggle this on if the study has blinded data. Use the Data Blinding tab to configure blinding.

  Note: Only licensed modules will be listed; the URL must also have the applicable module enabled.

• Data Central: Toggle this on to enable it. This allows the system to identify new and updated records since the last import. 
  • eIQ Review: Toggle this on to enable it.
  • elluminate Assist: Toggle this on to enable it, then select the SDTM Data Store from the drop-down menu. If no data store is selected, it defaults to the Reporting data store.
  • Protocol Deviations: Toggle this on to enable it. 
  • RBQM & RACT: Toggle this on to enable it.

• Data Quality: Toggle this on to enable it, allowing for validation of the study data structure against CDISC Standards.

  Note: The Data Quality module will use the standard selected on the Standards tab.

• Pinnacle 21 Enterprise Validation: Toggle this on if Pinnacle 21 Enterprise will be used to validate study data structure. (At the URL level configuration, the client provided Api Key and Web Host were added.)
  • Click the Configure icon on the right. The Pinnacle Enterprise Validation Study Configuration window opens. Enter the client provided Pinnacle 21 Enterprise details: Project, Study, and Data Package, then click Save. 
    

• Clinical Data Analytics: Toggle this on to view the standard data visualizations for this study in the Clinical Data Analytics (CDA) application. This app is available in the Analytics module.
• Clinical Trial Operational Analytics: Toggle this on to view the operational data visualizations in the Clinical Trial Operations (CTOA) or CTOA-Advanced after an ODM import. This app is available in the Analytics module.
  • Data Store for Queries: This drop-down defaults to ODM_Mapped. If the study does not use Rave, select the Data Store that will be used for Queries. If Data Central is enabled, and queries are enabled, this must match the Data Store Queries Table. See the Data Central section for more details on Data Central configuration.
• Sample Management Analytics: Toggle this on to enable it. This app is available in the Analytics module.
• Source Data Analytics: Toggle this on to enable it. This app is available in the Analytics module.
• Statistical Computing Environment (SCE): Toggle this on if your organization has contracted for the use of elluminate's SCE product.
• Data Classification: Toggle this on if your organization has contracted for an eIQ license.
• Mapping Automation: Toggle this on when your organization has contracted for Mapping Automation and SCE is enabled.
• Click the ETL tab.

Complete the ETL Tab

ETL (Extract, Transform, and Load) is used for mapping key study variables and overrides for each Data Store, and for activating the Data Variance and Reporting Database for each Data Store. The validate icon verifies entries in the Domain Specific Keys table for validity and uniqueness, displaying a warning if a configured field does not exist in some domains or if a key is not unique across domains. Users can also set a 0-100% threshold to limit the number of records with changes in an imported dataset for a successful import.

• Schema Prefix: This will be automatically populated after study creation.
• Study Import Control
  • Enable Changed Data Records Threshold: Check this to enable study import control.
  • Threshold (%): Enter a threshold between 0 and 100% to limit the amount of records with changes in an imported dataset for successful import. 
    • When importing into a study with a configured change percentage, files with enabled Data Change Tracking and properly configured keys are compared against the previous import of the same file. This determines if the change between the current and previous imports exceeds the configured threshold. 
    • If the threshold is exceeded, the import completes with a warning that the change exceeds the allowed limit and the file was not imported.
    • Files with a percentage change below the threshold are imported without warning.
• Reporting Database
  • See the Configure and Manage the Reporting Database article for details on configuring the Reporting Database.
• Show all data stores: Check to list all Data Stores in the Key Study Variables table.

• Key Study Variables: Keys define a minimal set of fields for each domain or data store, uniquely identifying each record across all domains within that data store. Defined keys are required to enable change tracking within Data Central during data import. Change tracking (issue creation, comments, annotations, and review marking) is disabled for duplicate keys. Domain data in Data Central becomes read-only if keys are duplicated or undefined at import. Keys can be validated in both study and Data Central configurations; key overrides can be configured in the study configuration.

  Important: It is important to configure key variables for the data stores before the first import to support features such as Data Variance.

  • Keys must be configured for each data store in a study, but only after data import. Key definition is only required for studies not using Rave, TrialMaster, InForm, Veeva, InForm Repeating, Veeva Lab, Rave Lab, Preclarus Lab Samples, or Preclarus Lab Results; these systems automatically define keys.  
  • Data Variance can be enabled when creating a study. Enabling it for a data store adds a Data Variance icon to its domain listings in Data Central. This allows users to specify a date range and identify new, updated, or deleted records in those domains.
  • Overrides: Before adding overrides, ensure automatic key definition is working correctly. Enter a comma-separated list of non-changing, non-nullable fields present in the domain and applicable across all domains in that data store. Ideally, these fields can be combined to uniquely identify records (e.g., Site and Subject ID).
  • Validate: Click to verify the entries in the Key Study Variables table for validity and uniqueness. A detailed warning will display if a field does not exist in a domain or if the key is not unique across domains.

After configuring the 5 tabs, click Save. 

Complete the Data Blinding Tab

Data Blinding in elluminate offers structured control over the visibility of sensitive study data within the platform. elluminate enforces data visibility through configured rules and user privileges, allowing authorized users to access data while restricted users see masked values or hidden records. Blinding can be applied at the field level, masking specific data elements within a domain, or at the row level, hiding entire records based on predefined conditions.

Blinding applies to both source and derived data. Source domains use configured blinding rules to protect imported data. Derived domains created through transformations, such as Mapper transformations, require their own blinding rules to ensure sensitive values remain protected in downstream outputs. elluminate does not apply different system behavior based on single-blind or double-blind study types. Blinding rules control data visibility based on user privileges.

Note: Blinding does not modify the underlying source data. The platform dynamically controls how data is displayed based on user privileges and configured blinding rules.

Configure Data Blinding after saving a study; this tab is unavailable when adding a new study. It is best to configure blinding before importing data.

Only users with the Blinded Data Configure privilege can access the Data Blinding tab.

Data blinding can be configured at the field and row levels.

On the Configuration tab, ensure a blinding option is selected (e.g., Single Blind, Double Blind). 

On the Settings tab, ensure Blinded Data is enabled.

Note: A Rave account must be blinded to ensure ODM_Mapped data is blinded.

Add Each Field Individually to be Blinded

1. From the Data Blinding tab, click the Add icon.  
   
2. Data Store: All Data Stores is selected by default. Use the drop-down to select an individual Data Store listed under Data Mart or Staging Area where the field to be blinded resides.
3. Domain: Enter the Domain name, select it from the drop-down, or use wildcard options.
4. Field: Enter the Field name, or select it from the drop-down, use a comma-separated list, or use wildcard options.

5. Mask: Optionally, enter the specified Mask. 

   Tip: This field can be left blank or a value can be entered. If left blank, the column for the blinded field displays as null (blank). If a value is entered in the Mask field, all blinded data that are null continue to display as null (blank), and all other values display as the specified mask. If the specified mask cannot be converted to the field data type (e.g., 'xx' for date, datetime, int, or decimal), the system masks values as '1/1/0001' for date and datetime and '-1' for all numeric types. Mask values applied to string or character fields that exceed the original field length are truncated.

6. Row: Click the Row Level Condition icon in the Row column to add row-level blinding. For more details see the Configure Row-Level Blinding section below.
   
7. Enter the SQL condition. See the examples below.
8. Click Save.
9. Repeat these steps to add more fields.
10. Click Save.

To remove a row, click the Delete Blinded Field icon to the right of the field.

Configure Row-Level Blinding

Row-Level Blinding uses a SQL-based approach that requires only conditional statements to select the data records to blind. While SQL-based, isolating these conditions simplifies configuration for users without SQL experience.

Note: For SQL-experienced users, the Row Condition statement should contain the filter conditions following the ‘WHERE’ clause in the query. For example, ‘SELECT * FROM table WHERE [row conditions]’.

‘AND’ and ‘OR’ statements are supported. Use parentheses ‘( )’ to group conditions and control evaluation order, similar to the order of operations in mathematics.

Examples:

Best Practices When Configuring a Study

• Configure Study Attributes. Before adding a study in elluminate, go to Platform Administration → Configuration to set up Study Attributes. Configured attributes populate the drop-down menus used when adding a study and enable proper grouping in the CDA and CTOA Analytics applications.
• Use 'Add From Template' whenever possible. Study templates provide reusable blueprints for new studies and prepopulate common choices across the five tabs. Templates enable straightforward setup, consistent standards and dictionaries across trials, and reduced configuration drift. Maintain a small, curated library of study templates and version the library as organizational needs evolve.
• Enforce a concise, searchable naming convention. Follow elluminate rules for Study Name: 2 to 24 characters, must start with a letter or number, and only underscores, hyphens, or spaces are allowed after the first character. The study name becomes the schema prefix in the elluminate database; keep the name short, simple, and effective.
• Complete all five tabs before saving. elluminate recommends filling out the tabs (Configuration, Standards, Dictionaries, Settings, and ETL) and saving only after all tabs are complete to avoid closing the Add Study window in the middle of setup. Many settings depend on each other; for example, enabling Clinical Data Analytics on the Settings tab requires selecting an SDTM standard on the Standards tab.
• Select standards & dictionaries deliberately and document them. Choose SDTM and ADaM standards with corresponding Controlled Terminology (CT) dates and dictionary versions. Record the selections and avoid changes during the study unless governed by change control. Maintaining consistent standards, controlled terminology, and dictionaries ensures data quality, analytics, and external validation (e.g., Pinnacle 21 Enterprise) results.
• Configure blinding before the initial data import. Save the study to enable the Data Blinding tab. Select a blinding option on the Configuration tab, enable Blinded Data on the Settings tab, and configure blinding rules before importing data. This helps ensure sensitive source data are blinded from the start and reduces the risk of exposing unblinded values in downstream features and outputs.
• Blind all instances of sensitive variables. Apply blinding anywhere a sensitive field appears or is derived, including copies, recodes, flags, joins, and aggregates. This helps maintain consistent masking across source and derived data. For example, if ARM is blinded in staging, also blind ARMCD and related treatment labels in SDTM and Reporting.