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Regulatory Intelligence: How AI will change regulatory operations

In this interview, Pharma IQ hears from Rick Finch Global Head of Life Sciences Consulting Services, Clarivate Analytics, on how Ai is becoming essential for regulatory affairs to manage growing levels of complexity in their role.

Rick: When you look at the broader context of how AI is being used across the pharmaceutical industry you can see what is really driving interest.

In the drug discovery process, we’ve seen AI have tremendous potential and impact on the efficient analysis of complex data sets to drive drug development. Comparatively, human identification of new molecules has been slow and far less effective. We’ve seen digital health technology and AI change the operation of clinical trials, from patient recruitment to digital endpoints and decentralized trials. On the business development and licensing side, we’ve seen companies use predictive models to streamline their business development spend. And on the commercial side, AI is being use to guide both sales and marketing efforts.

Within regulatory affairs, you also have many of the same influencing factors which has driven interest in other parts of the industry. There is a substantial increase in the volume of datasets available. There are also opportunities from cheaper and faster processing capabilities and there is a drastic improvement in the ability of AI algorithms.

This is coupled with the increasing complexity of the regulatory role. The number of drugs under clinical investigation is on the rise, along with the amount of publications from regulatory agencies. The number of new technologies in development, both drugs and digital, that regulatory must actively monitor is also increasing.

So there is a combination of headway being made in AI across adjacent spaces and a growing need from regulatory to automate, manage and keep up with the influx of data. When you consider the capabilities of AI technology, it’s a perfect match to address this problem.

On its best day, AI allows the regulatory function to increase the speed, accuracy and quality of how they execute certain functions.

For example, quality assurance professionals are tasked with continuously monitoring and updating their internal standard operating practices (SOPs) in reaction to regulatory changes across dozens of markets. AI can automate this process by ingesting regulatory changes and updating relevant SOPs. This is cost-effective, quicker and less prone to human error. This also allows the quality function to then focus on high value activities, such as addressing the corrective and preventative action (CAPAs) backlogs.

Another example is extracting data from unstructured documents. Valuable information can be found once data is extracted and transferred. For example, using a text mining tool you could look in detail at chemistry manufacturing and control documents to find products with the same chemical impurities in their manufacturing process.

AI tools are effectively being used to give regulatory affairs new insights into their own decision making ability, to help to improve their operating processes and spot recurring patterns.

Rick: There’s a great debate around whether AI will replace the human element of various tasks and responsibilities. I’m of the other school of thought that AI will actually empower employees and give them tools to improve the execution of their responsibilities.

It will allow them to automate the more mundane, manual tasks. But, they will also be able to act with greater certainty and at a greater pace on the data they have available to them. This will then allow then to make decisions more effectively and respond quickly to market changes.

These tools aren’t replacements, they are enablers. It certainly involves change, but if a company takes the right implementation approach, they’ll find their employees are far more interested in AI adoption than they may expect.

In the coming years, regulatory intelligence will be a must have to give companies the competitive advantage needed. These tools will help them track and compare regulations, learn from issues affecting their competition and predict key approval timelines.

Data mining, synthesis and analysis are all growing priorities for companies within the pharmaceutical industry. If companies want to succeed and not fall behind, they need to look into how AI can allow them to work quickly, effectively and with greater accuracy.

Rick: I would say there are three key factors.

First, you need the right set of data. Focus is needed on the data foundation, in particular how to; build the right data, integrate different data sources and combine structured data with raw, unstructured data. Realistically, AI is only as powerful as the data that goes into it.

Secondly, companies need to look at their operating models. It would be naïve to just implement an AI tool without considering its full impact on operations. AI has the potential to break down functional silos and allow teams to collaborate and communicate more effectively, but there must be a deep dive into how the operating model needs to change to achieve this.

Finally, you have to focus on culture. There must be an analysis on the challenges AI is going to present and how organizations can evolve their culture to reap the benefits of new technology and datasets. AI is a disruptive technology, but when companies focus on culture, change management and training they are more likely to be successful in the introduction and adoption of new tools.

Rick Finch, Global Head of Life Sciences Consulting Services, Clarivate Analytics will be joined by Darin Oppenheimer, Executive Director for Regulatory Affairs at Merck in an upcoming webinar to discuss how to use AI to transform regulatory operations. Secure your place now.

Written by: Natasha Taylor

Published on: 09/24/2019 .

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