Smart Search and Modern Medical Information (MI) Deliver Value For Your Teams and the Wider Business

By Dr. Keith Tsui and Dr. Paul Riley

Artificial Intelligence (AI) and Natural Language Processing (NLP) technologies can be used to deliver smart search for healthcare and life science organisations, improving efficiency and providing data insights to customer thinking and behaviour. Here’s how. It’s Monday morning — your list of projects is still there from last week, including plans and initiatives to help you and the team work smarter. You need to get on with these things, you acknowledge, because the battle to manage the growing workload is ever-present, and there is no end to the number of publications and sources of information you need to manage to be able to do your job. But at times, it is overwhelming. Employing more people would help, but that’s not on the horizon. Technology is the answer, the company leaders are saying, when talking about the mountain of work the company needs to get through this year and next. But introducing technology is not straightforward: there are hoops to jump through, people to consult, budgets to secure. And who has time for that?

This issue of excessive workload and keeping up with technology isn’t just found in pharma – it is affecting all industries. Artificial intelligence (AI) was once considered more of a sci-fi term than one you would encounter during your daily life. But AI is now commonplace, accomplishing both simple and more complex tasks to help speed up processes that take humans considerably longer to do. Natural language processing (NLP) may be unfamiliar to many of us, but it is in routine use in many industries, and you are likely benefiting from it regularly. Google Search, for example, uses both AI and cutting-edge NLP technologies. If your company isn’t already using AI and NLP, or at least working out how best to adopt it, you are at risk of falling behind the curve. The pharma industry is adopting digital technology at pace: large and small medical information teams worldwide are already using AI-powered products and services to improve quality and efficiency - the notion that AI & NLP is for other companies, or something to consider next year, is misplaced. The technology is here today, and to not use it may mean that your company is missing out on a valuable business asset. Healthcare professionals (HCPs) are increasingly adopting a multitude of AI-powered technologies to improve the speed and precision of medical interventions for patients. The technology is also used behind the scenes, helping manage surgical schedules, patient appointments, medical records, and more. Its use in other industries is commonplace. The great news for medical information teams is that introducing AI and NLP to your processes doesn’t need to be a journey into the unknown. The technology is tried and tested, and the risks are known, as are the measures to mitigate those risks. That said, the perceived newness of the technology means people worry about whether they can trust the results generated by AI and NLP-powered processes. There are plenty of examples of how AI and NLP have enabled companies to cover more ground in a shorter time; for example, enabling the

review of hundreds of clinical papers in a fraction of the time it would take a medical information professional to carry out the task. And whilst it is true that there is a risk of relevant information being missed or misinterpreted, the testing that occurs during the set-up phase ensures that the risk of this happening is acceptably low – maybe lower than could be achieved by a human having to deal with the same volume of information.

Yet many people in the pharma industry appear reluctant or wary of adopting AI and NLP powered systems; they are only slowly getting used to the idea of AI and NLP as a productivity enabler rather than a novel technology. The opportunities for productivity gains in pharma are substantial, but the industry is conservative and highly regulated, so perhaps it is understandable that companies are cautious about embracing a perceived ‘new’ technology. Outside pharma, in the clinical setting, AI and NLP technology is being used widely by healthcare professionals to help them manage patients. As an example, the medwise.ai platform enables HCPs to quickly find answers to their medical queries at the point of care. Such search platform tools are used by healthcare professionals at integrated care systems in the NHS, who are overwhelmed by the available information and cannot afford to spend time trawling through lots of information to find what they are looking for. The platforms can retrieve the specific piece of information they need within seconds, rather than the minutes or longer it would otherwise take. Such search platform tools can also be introduced by medical information teams to allow you to find the answers to enquiries from within and outside the company much more quickly than before, and you can be confident that every article in your literature repository has been scanned systematically, avoiding the risk that you miss key pieces of information. But there are other aspects of this technology that create exciting new possibilities for pharma. There could be real value in embedding the technology on your platforms – company and product websites, customer-facing information hubs – and making it available for your customers to use for their own searches. You could empower your customers by providing them with a sophisticated search tool of your carefully curated information repository. You could review a summary of your users’ search activity over time to spot patterns or trends in what people are searching for. This information is of value to colleagues in the drug safety, medical affairs and marketing teams. For example, you’ll be able to share reports with your marketing team showing the searches undertaken by HCPs visiting your platforms during the launch period for a new product, helping you to understand what aspects they were particularly interested in, what their concerns are, or if there any ways to improve communication around the product. Perhaps they are asking questions you hadn’t even considered? The adoption of AI and NLP is a normal part of the evolution of medical information. Those with lots of experience in the industry will be familiar with the regular patterns of technology adoption, such as updates to medical information management platforms, regular iterations of electronic compliance systems, and the adoption of chatbots. In the future, AI and NLP technologies may not be prominent topics of discussion, but you can be sure that the products and services that use them are as they become more mainstream and are eventually simply the way things are done. It is inevitable; how else will pharma be able to manage the everincreasing amount of clinical and scientific information? As with any new technology, there will of course need to be a period of training for those people who will be using systems powered by AI and NLP. There will also need to be system validation, as well as reassurance about issues of data privacy, Code compliance, and suchlike. But none of this is new; managing such issues is familiar territory for seasoned drug safety and medical information professionals. For further information about the role of AI and NLP in medical information, or to request our free 30minute training package, please contact keith@medwise.ai Thank you to our colleagues Hannes Rox and Enea Polotti for reviewing the article.

Dr. Keith Tsui, MBBS, MPhil (Cantab)

CEO and Co-founder Medwise AI Ltd

Dr. Paul Riley, MBA PhD CMgr

Medical Affairs Director Glasshouse Health