PhlexTMF v23’s optional add-ons bring AI into everyday TMF workflows, with an estimated 20% efficiency gain from automated document corrections and selected cross-check reviews completed in half the time.
THE CHALLENGE
Much of the effort in TMF management is necessary, but it adds up quickly. That effort grows with every site, staff member, and supporting credential in a study.
Here's where it adds up:
Rotated pages, blank pages, and broken hyperlinks trigger avoidable corrections
Query resolution and resubmission can delay document approval
Cross-checking for required documents, versions, and gaps across records is resource-intensive
THE SOLUTION
PhlexTMF v23 applies AI-powered automation to selected TMF quality-control and completeness activities through two optional add-ons, built by TMF experts and backed by 26 years of experience. That means your team can focus more time on high-value work, while maintaining confidence in TMF quality.
Built into the workflow, not added around it, v23 includes:
Automated Document Remediation: Identifies and corrects certain document issues during QC, and flags patient identifiers and financial information to users.
AI-assisted Cross-checking: Uses information in one document to determine whether other required documents are present and accurate.
AUTOMATED DOCUMENT REMEDIATION
Quality issues are surfaced within the document QC workflow, and certain issues can be corrected without requiring user action.
Page rotation: Corrected automatically, without manual rework
Blank pages: Removed automatically during QC
Hyperlinks: Broken links corrected before they hold up approval
Patient Identifiers & Financial Information: Identified, with users informed of resulting actions
Less correction, query resolution, and resubmission work can improve processing efficiency and help prevent delays in document approval.
With 5,000 documents a month, avoiding 150 resubmissions could add up to about 4.5 working days of time savings.
AI-ASSISTED CROSS-CHECKING
Cross-checking confirms that a TMF contains the right documents, in the right versions, with nothing missing between related records. It's essential work, and it becomes more demanding as studies grow.
v23 takes a smarter approach by using the information already captured in one document to check for the other documents that should accompany it.

Confirm credentials are on file for listed personnel
Start from an FDA Form 1572 or delegation log
Extract personnel names from digital and handwritten documents
Search for associated CVs, medical licenses, GxP certificates, contracts, and data privacy agreements

Match logged visits to their required documents
Start from a site's monitoring visit report log
Extract visit dates automatically
Check for the required confirmation letter, visit report, and follow-up letter
Create and link the corresponding events
At about 30 minutes saved per site per quarterly review, the potential savings grow with every site in your study:
| Study Profile | Est. Annual Time Saving |
| Small Study (10 Sites) | ~20 Hours |
| Mid-sized Study (50 Sites) | ~12.5 Working Days |
| Large Study (150 Sites) | ~7.5 Working Weeks |
Automate avoidable correction and resubmission work.
Help prevent delays by cutting down on corrections and query resolution.
Complete selected review and completeness checks faster, with savings that grow as study size increases.
Identify missing or inconsistent documentation more efficiently.
The TMF community recently came together in Denver for the CDISC US Interchange, and members of the Phlexglobal team came home with plenty to reflect on. Across sessions, hallway discussions, and
CDISC US was a great opportunity to meet customers, colleagues, and fellow industry experts face to face – both for the first time and re-connecting after a year or more away. There was a fantastic
When my Trial Master File (TMF) career began, the TMF Reference Model did not exist. Every customer had a different way of organising the contents of their TMF, and it was rarely interpreted
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