Managing drug and device safety effectively and efficiently has become more and more challenging, as companies face an enormous increase in the number of incoming cases. This has created the need for companies to streamline elements of the pharmacovigilance/multivigilance process with automation.
There are three main categories of automation available to safety professionals, each of which can be applied to different components of case management and signal management. Two of them, rules-based automation and robotic processes, can be applied to repetitive and static tasks that otherwise consume valuable staff time. The third, artificial intelligence (AI), is a powerful tool that enables companies to process larger volumes of data, identify signals and cases, and significantly
improve the entire safety process.
Understanding the role played by each type of automation can help in the planning of their implementation for specific needs and growth rates, including a transition to safety case processing that is increasingly touchless. This transition is best implemented in a phased approach in order to achieve tangible results, especially when adding AI abilities to augment human-based systems. Thus, the conversion of many components of case processing to touchless operation can begin, allowing humans to focus their efforts on the areas that require the most detailed attention.