In pharmacovigilance, there is growing interest in digital solutions to improve efficiency, quality, and scalability. Two terms often used interchangeably, automation and artificial intelligence (AI), represent distinct approaches with different strengths and limitations.
While both aim to support PV workflows, they operate in fundamentally different ways and are suited to different categories of tasks. Understanding this distinction is key to selecting the right solution for the right problem and avoiding unnecessary complexity where a simpler approach would suffice.
Automation
Automation refers to the use of technology designed to execute predefined tasks in a consistent, repeatable, and controlled way. It is particularly suited for activities that follow clearly defined rules and do not require variation in output. In practice, automation focuses on executing the same task repeatedly without change, often within predefined workflows that are easy to validate and control.
A key strength of automation is its predictability and auditability. Because automated processes follow fixed rules, they are highly reliable and easier to validate, which is especially important in regulated environments such as pharmacovigilance. These systems are typically built to handle routine, structured activities, reducing manual workload while maintaining compliance and consistency.
In pharmacovigilance (PV), automation can be applied across a wide range of operational tasks. Examples include using VBA scripts in Excel to perform repetitive data manipulations, Python or R scripts for more complex analyses, or automated scripts to transform detailed listings into summary tabulations. Tools such as Power Automate can also be used to manage communication workflows, including routing emails or triggering actions based on predefined rules.
More broadly, automation may play an important role in optimizing PV workflows by supporting routine, rule-based tasks such as data processing, reconciliation, and report preparation. By reducing the need for manual intervention in repetitive activities, it can help improve efficiency, minimize errors, and free up time for higher value work requiring expert review and judgement.
Artificial Intelligence
AI, in contrast to automation, is designed to handle more complex and less predictable tasks that require interpretation and flexibility. Rather than following fixed rules, AI systems rely on machine learning to analyze data, identify patterns, and generate outputs, including text creation or recommendations. This enables a level of contextual understanding and flexibility that goes beyond simple rule-based processes.
In pharmacovigilance, AI can support a variety of advanced use cases. For example, a REMS chatbot can be trained on full program documentation to answer user queries, or an SOP librarian can retrieve and contextualize relevant procedures from a large knowledge base. AI can also assist in recommending appropriate types of analyses based on the characteristics of a dataset, helping users make more informed data-driven decisions.
Overall, AI complements automation by enabling more dynamic, knowledge-driven support in PV workflows, particularly where variability and interpretation are required.
Automation or AI?
In practice, automation and AI should not be seen as competing solutions, but as complementary tools. Automation works best for structured, repetitive tasks that follow clear rules and require consistency, making it a dependable and easily validated option in regulated environments. AI, on the other hand, delivers value in more complex, variable scenarios where interpretation, adaptation, or content generation is needed.
For PV teams, the challenge is not choosing one over the other but applying each thoughtfully based on the use case. In many situations, a simple script may be sufficient. In others, AI-enabled solutions can unlock new capabilities and additional insights. A balanced approach helps organizations improve efficiency while maintaining compliance and leveraging advanced technologies where they provide meaningful value.
About UBC
United BioSource LLC (UBC) is the leading provider of evidence development solutions with expertise in uniting evidence and access. UBC helps biopharma mitigate risk, address product hurdles, and demonstrate safety, efficacy, and value under real-world conditions. UBC leads the market in providing integrated, comprehensive clinical, safety, and commercialization services and is uniquely positioned to seamlessly integrate best-in-class services throughout the lifecycle of a product.
About the Authors
Dobrochna Dolicka, Safety Scientist, Global Safety Writing
Dobrochna Dolicka, PhD, serves as a Safety Scientist on UBC’s Global Safety Writing Team. For the last 3 years, she has been responsible for authoring periodic safety reports such as DSURs, PBRERs, and PADERs, as well as conducting other signal management activities. Ms. Dolicka is also working on the development and implementation of automation and artificial intelligence across UBC’s comprehensive pharmacovigilance services. She holds a PhD in Biomedical Sciences as well as a master’s in molecular biology.
Christopher Henry, Safety Scientist, Global Safety Writing
Christopher Henry, PhD, serves as a Safety Scientist on UBC’s Global Safety Writing Team. With a strong biomedical and AI background, Mr. Henry has brought his unique skillset to UBC’s pharmacovigilance team. He is responsible for authoring periodic safety reports such as DSURs, PBRERs, and PADERs, as well as conducting other signal management activities for pharmaceutical products that are still in development and products that are already marketed. Mr. Henry has been leading the development and implementation of artificial intelligence across UBC’s comprehensive pharmacovigilance services. He holds a PhD in Cell Physiology as well as a master’s in health biology, Genetics, Epigenetics, & Cell Fate Control. He has worked at UBC for the past 3 years.
