Intelligent automation uses machine learning and other cognitive technologies to continuously collect, process, and analyse data. These continual streams of data allow systems to suggest data-driven insights to a business. Ideally, from this, the organization can make informed and strategic decisions.
How much of this theory is manifest in practice? Assessing these trends for Digital Journal is Michelle Gyzen, Senior Director, Regulatory Affairs and Drug Development Solutions (RADDS), IQVIA.
Gyzen considers developments within the pharmaceutical field, seeing automation as being set to be the next big thing: “The desire for rapid adoption of intelligent automation technology will be widespread in 2024. While tools like artificial intelligence (AI) show a lot of promise for the pharmaceutical regulatory industry, many are not quite ready for all the challenges that will follow.”
Despite the enthusiasm there are reservations and obstacles for the adoption. Gyzen puts these forward as: “There are considerable risks to adoption that may have deep compliance implications. Human efforts are the greatest asset in the journey to automation in terms of compliance and validation, and organizations will see this first-hand in the upcoming year.”
Keeping ahead of the change curve is also important; this not only makes good business sense it also helps a firm to sit in the right side of the regulator.
Here Gyzen tells companies: “As new systems and automated technologies are built, global health authorities will need to respond accordingly. In the next few years, we will see greater collaboration and consolidation with how health authorities will accept submissions.”
Turning his attention to the drivers of these changes, Gyzen draws out: “There will be a big push for component content management, and possibly the reinvention of the electronic common technical document (eCTD). Though it may not happen in 2024, the industry will take some strides to eventually see end-to-end automation for eCTD submissions.”
These technologies can also help to streamline the process of passing on reports and other forms of communications with national regulators, like the US FDA. Gyzen opines: “The most exciting aspect is the potential of the combination of AI, machine learning and large language models to help decipher and manage health authority communications. By leveraging an organization’s intelligence and existing information, organizations will be able to efficiently respond to health authority queries with the assistance of AI.”
One barrier is with the attitudes and expectations of the regulators. Gyzen points out that one of the main challenges is cultural: “The regulatory industry is typically hesitant to embrace innovative technologies. However, in the past year, there was a new understanding and appreciation for what can be achieved and optimized. This will push organizations to look towards the phased implementation of automated tools for the regulatory field. In the same vein, we expect organizations to take a more thoughtful approach, really taking time for change management, retraining and repurposing staff as automation enhances their work.”
