Pharmacovigilance teams with manual literature screening find the process extremely exhausting and time-consuming. Regulatory bodies like EMA, FDA, and MHRA have noticed this and enforced regulatory standards for efficient and automated literature screening. With these bodies pressing MAHs (Marketing Authorization Holders), literature screening has become a critical compliance frontier where manual processes risk non-compliance.
With AI reshaping each industry, the question isn’t whether AI will disrupt literature screening in PV; it’s about how fast you can catch up. Literature screening is seeing a substantial change now by adopting AI with automation, and it’s here to stay.
In this article, we’ll expand on the types of literature screening and how AI has disrupted it by adopting automation.
What is literature screening in pharmacovigilance?
Literature screening in pharmacovigilance is the detection and assessment of products or medicines listed in journals and articles. It surfaces adverse drug reactions (ADRs) and safety issues from scientific literature.
Types of literature searches
Literature screening is typically of two types. One is an exhaustive search. It goes through all articles and journals, capturing a broad spectrum of available literature. The second one is a selective search focusing on specific databases and key publications.
Let’s go through them:
- Exhaustive search
An exhaustive search aims to go through all sorts of literature available for a specific substance. This means searching databases, websites, and at times also manually searching books or journals to ensure no data is missed.
This type of research is done when performing meta-analyses, where several studies are combined to provide a more assertive answer.
- Selective search
Instead of looking for all journals and articles to find answers, selective search focuses on going through high-impact literature, which has the potential to change policies.
Though it’s less comprehensive than exhaustive searches, it is quicker and more impactful when there is a time constraint.
Why is literature screening pivotal in pharmacovigilance?
Assessing data from scientific and medical literature is the cornerstone of patient safety. PV teams are dependent on literature screening to surface adverse drug reactions (ADRs) and safety issues from both exhaustive searches and selective searches.
With literature screening, we get an insight into side effects or varied patient reactions to assess the safety of medical products. In 2026, it’s advancing. It’s transitioning into greater automation, stricter traceability requirements and enhanced regulations. Literature monitoring is significant because medical professionals can become aware of the latest research findings.
What are the bottlenecks in manual literature screening?
As per EMA (European Medicines Agency), the current literature screening is mostly manual. Thus, the time spent by PV professionals in literature review is 950 hours/month if they take 2 minutes to read the abstract and 15 minutes to read the full article. It sums up to ~6000 articles/month.
This means the process is:
- Slow and less time-effective: Manual searches are time-consuming and resource-intensive due to the growing volume and complexity of data.
- Licensing cost for translation: The PV budget for getting a license for a full-text article and thus getting it translated is pretty high, making it a tedious and cost-intensive process.
- Regulatory compliance: In a lot of scenarios, manual processes lead to non-compliance due to oversight of misinterpreted data.
- Siloed team: When PV professionals work in silos, it leads to inconsistency, leading to significant compliance issues.
- Duplicate data management: Since the literature is sourced from multiple resources, it can lead to erroneous conclusions and false signals, resulting in non-compliance.
- Incorrect search strategy: Implementing a balanced, correct search approach with constant updates is critical.
How AI is improving literature monitoring in 2026
AI is transforming literature monitoring in PV in 2026 by addressing critical bottlenecks. It’s helping with making the process faster, emphasizing accuracy and regulatory compliance.
| Area of improvement | AI implementation | Outcome |
| Automating screening | Automation eliminates repetitive and manual screening, allowing teams to focus on signal detection and risk evaluation. | Reduced erroneous side effects. |
| AI-generated summaries | Generates instant article summaries highlighting safety findings. | Prioritize safety-relevant references for fast decision-making. |
| Multi-language support | AI helps automate the translation of articles in multiple languages. | Global literature coverage without a language barrier. |
| Signal detection | Uses predictive analytics to find out safety issues before widespread occurrence. | E.g., discover cardiovascular risks associated with a drug. |
| One-Click Case Processing | Automatically converts articles into ICSRs with structured case extraction | Articles converted to ICSRs in one click with automatic AE/drug extraction |
Guidelines of FDA and EMA on literature monitoring
The FDA and EMA provide guidelines on how literature screening should be done in the realm of PV. These are not just recommendations. These are regulatory requirements for MAH (Marketing Authorization Holders). It is crucial to understand and implement them. As time passes, these guidelines are frequently updated, so one must keep a vigilant eye on when and how these updates come.
The FDA provides comprehensive guidance on conducting effective literature searches through multiple agency documents. The key resource being the FDA’s Guidance for Industry on good pharmacovigilance practices, which includes detailed instructions and recommendations for literature monitoring.
The EMA’s GVP guidance, especially Module VI, outlines MAHs’ responsibilities for literature monitoring: the scope and frequency of searches, criteria for selecting sources, and how to report findings.
Your PV team can no longer afford to review literature in the traditional style. The market is evolving with AI and automation, and even regulatory bodies like the FDA and EMA emphasize process automation. Patient safety information is measured more quickly and accurately.
Summing it up
If you’re looking for literature screening services, we can get it done for you automatically.
We offer:
- AI-supported screening: Identify publications concerning the customer portfolio, supported by advanced AI models trained for pharmacovigilance.
- Adverse reaction assessment: Comparison of reported reactions against existing knowledge bases, such as SPCs and reference safety information, to surface any new revelations.
- Human-in-loop: Expert review of AI-screened literature to ensure correctness.
- User support: Structured presentation and tagging of literature to support efficient analysis, decision-making, and documentation for regulatory compliance.
So, take the first step and connect with us now for a FREE consultation.