For pharmacovigilance teams, few deadlines carry more weight than expedited safety reporting.
When published literature identifies a serious and reportable adverse event associated with a marketed product, regulatory agencies such as the FDA and EMA require Individual Case Safety Reports (ICSRs) to be submitted within strict reporting timelines. Serious, unexpected adverse events typically must be reported within 15 calendar days, and fatal or life-threatening cases carry an even tighter window: as little as 7 calendar days.
While 15 days may seem like ample time, and 7 days barely any at all, much of that window is consumed before a case is ever ready for submission.
The clock starts long before a case reaches the safety database
Every potential case begins with literature surveillance.
But identifying a relevant publication is only the beginning. Before a literature-based case can be submitted, safety teams need to determine whether it meets reporting criteria and turn information written for a scientific audience into a complete, review-ready safety case. That may require accessing full text, resolving missing or ambiguous details, translating content, structuring case information, and completing the appropriate medical and quality reviews.
Each step takes a portion of a reporting window that is already counting down.
The opportunity, then, isn’t to eliminate the rigor behind the process. It’s to reduce the time spent on repetitive work so safety professionals have more of that window available for the decisions that require their expertise.
Where AI creates an advantage
Artificial intelligence cannot replace the clinical judgment required in pharmacovigilance.
What it can do is accelerate the administrative work that happens before experts make those decisions.
Rather than asking reviewers to manually evaluate every publication, AI can rapidly analyze search results and prioritize the articles most likely to contain reportable safety cases. It can identify key clinical entities such as suspect drugs, adverse events, patient information, and reporters, then prepare structured information for review.
This allows pharmacovigilance professionals to spend less time processing literature and more time evaluating the cases that matter most.
How CRScube helps teams move faster
CRScube’s AI literature intake, available through cubeSAFETY, brings automation into the earliest stages of expedited safety reporting, helping teams move from literature surveillance to case review with fewer manual steps.
Instead of treating search, screening, case identification, and data entry as separate activities, the technology helps create a more continuous path from publication to safety database. AI can surface potentially relevant cases sooner, organize key safety information for review, and reduce the amount of information that must be manually transferred between steps.
The result is a workflow designed to help teams:
- Surface potential safety cases sooner so relevant publications can move into review without unnecessary delay.
- Reduce repetitive screening and data handling that can consume valuable time early in the reporting window.
- Move structured case information forward more efficiently while keeping validation in the hands of authorized users.
- Preserve more time for medical review and submission quality before regulatory deadlines arrive.
Throughout the process, pharmacovigilance professionals remain in control. AI prepares the work, while authorized users review and validate each case before it enters the safety database.
More time where it matters most
The goal of AI literature intake isn’t simply to process articles faster. It’s to help organizations protect the time available for expert review within a fixed regulatory reporting window.
By reducing repetitive screening, data extraction, and manual data entry, AI gives pharmacovigilance teams more time to evaluate complex cases, ensure submission quality, and meet expedited reporting timelines with confidence.
As safety requirements continue to evolve and global literature volumes increase, organizations need technology that supports both efficiency and compliance. As part of the CRScube family of clinical research solutions, Mednet is helping bring AI-powered pharmacovigilance capabilities to organizations looking to simplify safety reporting while maintaining the quality and regulatory rigor the industry demands.