For pharmacovigilance teams, keeping pace with the growing volume of safety-relevant literature is an ongoing challenge.
Once a product reaches the market, thousands of new publications, case reports, conference abstracts, and medical journals become potential sources of important safety information. Marketing authorization holders (MAHs), the pharmaceutical companies licensed to market a given product, are expected to monitor global literature for adverse events at least weekly, identify reportable cases, evaluate emerging safety signals, and maintain complete documentation for regulatory inspection.
It’s an essential responsibility, and for many organizations it still depends on highly manual, repetitive processes. With the volume of scientific literature continuing to grow alongside expanding product portfolios, pharmacovigilance teams face the challenge of identifying the relatively small number of publications that require action within an ever-increasing body of literature.
The challenge isn’t finding information. It’s processing it efficiently, accurately, and consistently. That’s where AI-assisted literature intake can make a meaningful difference.
How CRScube’s AI literature intake simplifies safety reporting
For many organizations, literature intake remains a largely manual process. Teams search multiple literature databases using carefully constructed strategies, review hundreds, or even thousands, of returned articles, determine whether a publication contains a potential Individual Case Safety Report (ICSR), obtain full-text articles, translate foreign-language publications when necessary, extract clinical information, and manually enter qualifying cases into the safety database.
CRScube’s AI-powered literature intake, available through cubeSAFETY, streamlines this process with a single, connected workflow. Rather than relying on separate tools for searching, screening, and data entry, the platform can automatically:
- Perform scheduled literature searches using configured drug names and active ingredients
- Analyze publications to determine whether they meet the criteria for a valid safety case
- Extract relevant clinical information for review
- Populate approved data directly into the safety database after user verification
Throughout the process, authorized users remain in control. AI automates the repetitive work of searching, triaging, and preparing data, while pharmacovigilance professionals review and validate each case before it enters the safety database. This human-in-the-loop approach helps improve efficiency while supporting quality, compliance, and regulatory confidence.
Why a connected workflow matters
The traditional literature intake workflow involves a series of repetitive, manual steps. Safety teams conduct scheduled searches across literature sources, review returned publications, determine which may contain a reportable safety case, extract relevant clinical information, and then enter that data into the safety reporting system.
AI changes where that effort is spent. With cubeSAFETY, configured searches for drug names or active ingredients can run automatically. AI analyzes the resulting literature to identify potential safety cases and extracts relevant information to prepare a first draft of the case. Pharmacovigilance professionals then review and verify the information before approved data is populated directly into the safety database.
The result is more than faster literature review. By connecting literature intake directly with signal detection and safety reporting, cubeSAFETY reduces manual data entry and the handoffs between separate systems that can introduce transcription errors, quality issues, and reporting delays. Safety professionals can spend less time moving and processing information and more time applying their expertise to case assessment, signal evaluation, and patient safety.
More time for what matters
The purpose of literature intake has never changed: identify potential safety risks as early as possible and protect patient safety. What has changed is how much of that work can now be automated.
By reducing repetitive work across literature intake and case preparation, cubeSAFETY allows pharmacovigilance teams to devote more of their expertise to medical assessment, signal evaluation, and other activities that require human judgment.
As literature volumes continue to grow, intelligent automation is becoming less about doing more with fewer people and more about enabling safety professionals to work at the top of their expertise. As a CRScube company, Mednet is helping bring these AI-powered pharmacovigilance capabilities to organizations looking for a more connected approach to clinical research and safety. With literature intake, signal detection, and safety reporting brought together within cubeSAFETY, teams can reduce friction across the safety workflow while maintaining the human oversight, quality, and regulatory rigor pharmacovigilance demands.