Using Artificial Intelligence in Pharmacovigilance

Oct 12, 2021

As we briefly discussed in the previous chapter, Artificial Intelligence (AI) is used to simulate the processes of a human brain with the help of computer systems. It encompasses various technologies, including rule-following, reasoning – using rules to reach rough or specific conclusions, learning, and self-correction.

Implementation areas of AI

In the area of pharmacovigilance electronic systems, AI technologies could be implemented in case collection, consolidated reporting, and signal and quality management.

For example, using machine learning algorithms to automate medical coding according to MedDRA dictionary for medical terms or WHODrug dictionary for medical products.

The image below demonstrates how AI based on a neural network is used to detect and manage signals, find duplicates, and auto-code in the Flex Databases Pharmacovigilance system.

Additionally, AI is used in safety signal detection, including:

  • multimodal signal detection,
  • signal detection using neural networks,
  • predictive signal detection.

In general, AI and other automation technologies in pharmacovigilance allow to eliminate human errors, standardize processes, shorten the processing cycle, and reduce manual work.

Examples of AI technologies 

TechnologyShort description Use cases of pharmacovigilance electronic system 
Machine learning (ML)Machine learning (ML) is a subset of AI, allowing the creation of algorithms that can learn and make predictions based on the data. Instead of following a predefined set of rules and instructions, these algorithms are taught to identify patterns in big data and improve over time and with more data. This technology helps identify potential signals. Case collection, periodic reporting, signal management, and risk management.
Neural networkSystem replicating a neural structure of a mammal’s brain. Neural networks usually consist of multiple layers which are formed by numerous nodes. This technology helps identify potential signals. Case collection, periodic reporting, signal management, and risk management.
Semantic searchSemantic search is meant to improve search accuracy and deliver relevant results by understanding user intentions and search query context. Case collection, periodic reporting, signal management, and risk management.

AI use cases

Use case 1Automated case collection and evaluation of serious adverse events (SAE) from online comments on Indian websites. 

Traditional safety data collection is challenging in this area, however, using of artificial neural networks and sentiment analysis allows to automatically identify characterizations of the researched objects in the emotionally coloured text.

Use case 2. Predicting the safety profile of a developed drug

Researchers combined in vitro data with safety information from FAERS database, and created machine learning models, allowing to predict future adverse events based on the data point from other databases, such as PubMed.

More about Pharmacovigilance

Video: The way we save time on case intake in Flex Databases Pharmacovigilance module

In this video we talk about the way Flex Databases Pharmacovigilance module helps to save time on case intake.

Learn more
Answering 6 most frequently asked questions about Flex Databases Pharmacovigilance module

lients. That’s why to save your time and give you a deeper understanding of how our Pharmacovigilance module work, we are happy to answer the six most frequently asked questions about the system.

Learn more
Synchronizing safety data from EDC/eCRF with Flex Databases Pharmacovigilance

Flex Databases is ready to arrange the automated data flow from any eCRF/EDC used by Sponsor or CRO to our Pharmacovigilance module.

Learn more
Challenges of pharmacovigilance automation

Despite the obvious benefits of introducing new technologies in electronic systems for pharmacovigilance, it is necessary to consider the difficulties that a company will face:

Learn more

Have we picked your interest?

Tell us more about yourself and we will organize a tailored live demo to show how you can power up your clinical trials processes with Flex Databases.