Pharma predictions 2: Voluminous data and the role of AI

Variations on standard tablets, which can be distinguished by both colour and shape.— Photo by Ragesoss (CC BY-SA 2.0)

Many industries face the prospect of information overload and as data becomes bigger, more complex and often less structured, capturing such data and making sense of it becomes ever-more challenging.

Looking at some of these challenges and notifying the trends to Digital Journal is Simon Johns, who is the Director of Medical Information and Marketed Product Safety at the regulatory intelligence firm IQVIA.

Johns  begins by looking at information growth: “The continuously growing volume of Medical Information case inquiries will not cease in 2024, especially as it is effectively the only inbound communication channel remaining for pharmaceutical companies.”

Medical information is a wide ranging term, meaning any information regarding an individual’s medical history, mental or physical condition, or medical treatment or diagnosis by a healthcare professional. Such data is not only critical to patient health it is also of great value for companies.

Can the complexity and voluminous nature of this information be moderated by the use of technology, specially AI?

In answering this important question, Johns things the changes will be for the better: “Artificial intelligence (AI) will be relied on to help manage the growing case volume. Although AI is not a novel concept within the pharmaceutical industry, the introduction of new systems and tools – like generative AI – will push companies to revisit their current applications to automate traditionally manual tasks.”

This will lead to some sectoral changes. Predicting the fork these will take is not straightforward. Seeking to understand the patterns, John observes: “In 2024, the industry, specifically within the Medical Information area, will see shifts to multi or even omni channel models to ensure that healthcare professionals and patients have available means of communication with pharmaceutical companies when necessary.”

Citing an example, Johns uses bots: “AI chatbots will first be applied to this area in the form of warm transfers – if a call centre is experiencing a surge in calls and all human agents are occupied, AI agents will emerge as a backup. These chatbots would then be able to transfer the inquiry to a human agent when available or needed. Fully automated processes will be phased in. Against some beliefs that this process will replace agents, AI will be a tool for agent assistance and faster response.”

The world of pharmaceuticals is heavily regulated and therefore the adoption of nay technology needs to be performed in a controlled manner, extending to the nece3ssity of keeping things compliant. Johns coincides with: “Maintaining compliance is a priority for pharmaceutical organizations, and while the gradual integration of AI processes may seem like a large endeavour, organizations will begin to see the benefits in the upcoming year.”