Beyond manual entry: Rethinking the safety reporting workflow

Safety reporting depends on accurate transcription.

A published article may contain adverse events, suspect drugs, patient history, treatment timelines, lab values, and reporter details. Pharmacovigilance teams need to turn that information into a structured Individual Case Safety Report (ICSR) without losing meaning or introducing errors along the way. That literature-to-case translation is where manual workflows create risk.

When safety teams need to search, screen, extract, re-key, draft, validate, and prepare cases across separate steps, the same information is handled repeatedly. Each handoff creates an opportunity for missed details, inconsistent narratives, delayed review, or data entry mistakes. cubeSAFETY addresses these challenges by connecting AI literature intake, document import, narrative drafting, and point-of-entry validation in one safety reporting workflow.

1. AI literature intake

Literature intake is often described as a search and screening process. The workflow continues once a relevant article is found. Safety professionals need to identify whether the publication contains a valid case, extract the right safety information, understand the clinical context, and enter each detail into the correct place in the safety database.

AI literature intake in cubeSAFETY reduces manual handling from the beginning of this process. cubeSAFETY performs targeted literature searches using configured drug names or active ingredients. Once literature is identified, AI reviews the content and assesses whether the document contains the information needed to create a valid safety case.

After user review and confirmation, cubeSAFETY extracts the relevant information and populates the safety database. This removes repetitive re-keying from the intake process and gives safety teams structured case data to review from the start. By reducing the amount of information that needs to be manually transferred from literature into the safety database, the process creates a more controlled starting point for case creation.

2. Document import

Literature is not the only source of safety information. Pharmacovigilance teams also receive case information through CIOMS forms, partner files, and other external documents. When these sources are handled manually, teams face the same risks of repeated data entry, transcription mistakes, and inconsistencies between the original document and the safety database.

cubeSAFETY supports multi-source import, allowing case information from CIOMS forms and external files to be converted into structured, E2B-compliant formats. This gives PV professionals a consistent way to bring information from different source documents into the safety workflow without repeatedly copying data from one document to another.

By reducing manual transcription across different intake routes, cubeSAFETY helps maintain the quality and consistency of case information before it moves into the next stage of reporting.

3. AI narrative drafting

The case narrative is one of the most important parts of an ICSR. It needs to summarize the patient journey clearly, reflect the clinical sequence, and remain consistent with the structured case data. Manual narrative drafting takes time, and different reviewers may approach the same case in different ways.

AI narrative drafting in cubeSAFETY generates standardized clinical summaries directly from case data. This gives safety teams a consistent starting point for review and reduces the time spent drafting narratives from scratch.

This creates another layer of consistency in the reporting process, with the narrative built from the structured information already available in the case rather than being recreated manually.

4. Rules validation

Even when case information has been entered correctly, validation remains an essential part of safety reporting. Missing or inconsistent information can lead to rework if issues are only identified during final submission checks.

 cubeSAFETY enables validation at the point of data entry, through agency-specific built-in rules checks. Aligning with agency requirements, the system flags missing or inconsistent information on-screen. This allows teams to address issues before they become submission problems, rather than returning to the source, correcting the case, updating the narrative, and validating it again later.

Together with AI-powered intake, document import, and narrative drafting, point-of-entry validation creates a more controlled path from source information to submission-ready reporting.

Human-in-the-loop

AI does not replace pharmacovigilance expertise. Safety professionals still review the article, confirm whether a valid case should be created, assess the medical context, and approve the final case data.

What cubeSAFETY changes is the amount of manual work surrounding those decisions. Instead of spending time re-keying information, drafting from a blank page, or finding validation issues late in the process, users review structured outputs generated from the source material and apply their expertise where it matters.

We keep human oversight at the center of all our workflows.

A clearer route to submission-ready ICSRs

Error-free safety reporting is enabled by increasing quality in every step of the pharmacovigilance process.

cubeSAFETY provides a single environment to enable a frictionless, error-free safety reporting.

For pharmacovigilance teams, this creates a cleaner route from raw literature and source documents to submission-ready ICSRs, with fewer avoidable errors and a reporting process based on trust.