How can generative AI benefit the industry?

“When it comes to generative AI, the innovation capability is really the limit. It can be employed for any use case you can imagine. But to give some concrete examples in the life science space, there are huge benefits to reap anytime that there are repetitive tasks involving large datasets. You can basically develop a generative AI companion that does the checking, the searching, the rectifying of data for you.” 

“In the commercial content management space, for example, our clients are actively testing generative AI use cases in areas such as medical and regulatory reviews. You may have a companion that looks through the promotional assets, verifies that the claim can be found in the reference, and basically serves up options for a human reviewer to verify, which expedites the review.” 

“Another example is if you superimpose a generative AI companion on top of material that has already been reviewed by humans in manual processes; The AI companion will find things that should have been rectified, and it allows you to be more effective.” 

“The discovery phase is another area where generative AI has huge potential. It can scan molecules for chemicals for their active properties and speed up the whole discovery process. You can most certainly use your companion for writing protocols, and for managing your clinical trial site and getting up to speed and reporting the data in the right way –  which in turn might speed up patient recruitment and shorten the time to reporting the clinical trial results.” 

How can generative AI speed up the time to market for new medications?

“In this highly regulated environment, the monitoring and quality-checking tasks are so critical and so time consuming that they can actually delay communications and slow the time for medications to reach the market.” 

“Generative AI can make every step of the process smoother. But let’s say you’ve come as far as getting regulatory approval for your product, and now you need to finalize the communications that will be used to launch the product to healthcare professionals. Generative AI can help you expedite the communications and thereby get your product to market faster.” 

“If you think about it, every month that a product is delayed impacts patients as well as the manufacturer in a very significant way, so anything you do to get there faster is hugely beneficial.” 

What’s a challenge your clients grapple with when it comes to setting up a generative AI system?

“If you don’t have good data quality your generative AI companion is not going to work very well. It requires rigour, which is actually very healthy. Some of our clients tell us that they don’t really have a good handle on everything in their channels.”

“There are plenty of examples where it becomes clear that as their digital ecosystems have grown, their data is more and more fragmented and there’s a lack of data governance and clear visibility over the data. Generative AI models represent an opportunity both to speed everything up, but also to clean the house a little bit. Basically, this is a chance to begin to upgrade to a higher level that’s more efficient and more effective.” 

Do you have any exciting examples of AI-powered projects you’ve worked on? 

“One of the exciting products we’ve been working on in the healthcare area is a virtual AI clinician, which is accessible via an app. The virtual clinician is a very good assessor that can diagnose 900 common medical concerns and alleviates the burden of easy, first-line diagnoses on the healthcare system. Cognizant developed the virtual AI clinician for a health authority, and the system has handled 5,000 patient conversations during the testing phase.” 

“The AI clinician is not meant to be a replacement of a real doctor, but it is able to give patients a kind of first assistance with relevant information, and guide patients with mild symptoms to help themselves at home. It is of course important to be very careful in how this is used, and the AI clinician must very clearly inform the patient that if they continue to have symptoms or develop new symptoms, they need to seek medical care.” 

“The virtual AI clinician is still in the testing phase and is not yet perfect, there are still some inaccuracies and it doesn’t have perfect recall. But it already gives us a taste of the future of digital therapeutics.” 

How can Cognizant help life science companies on their generative AI journey? 

“Cognizant has a network of over 350,000 experts in areas such as data, cloud, AI design thinking, user experience, and software quality. This positions us uniquely to assist life science clients on their AI journey. Our approach covers disciplines to provide solutions that combine cutting edge AI with strong data management and scalable cloud infrastructure. Through our expertise in design thinking and user experience we develop impactful AI-driven applications tailored to meet the needs of our clients. Our focus on software quality ensures that these solutions are reliable, secure and compliant, with industry standards. This comprehensive strategy enables life science companies to innovate quickly, improve research and development processes, streamline operations, and ultimately achieve better outcomes for patients.”

Authors: Lone Harboe, Life Science Consultant, and Dr. Kathrin Kind, Chief Data Scientist

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