Artificial intelligence, or AI, is still a bit of a buzzword. Those unfamiliar with AI applications may defer taking advantage of them in business, whether out of intimidation or a lack of confidence that the technology can address some of their most pressing pain points.
But for the life science industry, AI already impacts how day-to-day conversations take place. Functional teams across the pharma spectrum already share insights with each other, but those conversations are often inefficient, time-consuming and incorrectly targeted.
These discussions can be smarter and more productive. And this is where AI comes in – turning conversations and observations into actionable insights.
Through AI-powered technology like natural language processing (NLP), teams can use AI to monitor several conversations and more quickly understand the points that will inform strategic decisions.
AI allows pharma teams to facilitate a more in-depth, analytical overview of dozens of information streams. By doing so, it massively reduces the chances of missing any essential information. By creating deeper, more actionable insights, AI enables teams to strategically focus on education to help healthcare providers understand their products better.
The role wearables play
While AI may seem complex, it’s much easier to break down when considered in association with some now-ubiquitous items – sports watches, for example. Not only can these devices report on basic things like the number of steps taken each day, but they can also read and measure oxygen levels and heart rates, providing the wearer with actionable insights. In a health context, this immediacy allows patients instant access to data, and may inform the need to go and see a medical professional by allowing individuals to pick up on emerging issues.
In this way, AI technology may indirectly reduce the administrative load required in medical settings, speeding up the time it takes for a patient to access treatment. Wearable technologies have opened a door to understanding what is happening to patients in real time and keeping them on the right path.
In it for the patient?
In its simplest form, AI allows pharma teams to pull together different scientific understandings that they can apply to various strategies based on the insights they collect. The technology allows pharma teams to concisely collate insights from their researchers to help bring drugs safely to market.
As mentioned above, technologies like NLP allow teams to access information more quickly, leading them to effective strategic decisions. NLP eliminates some of the manual processing tasks associated with collating and interpreting information, reducing the risk of missing essential information, such as an important side effect in a research summary.
NLP means teams can monitor conversations happening between organisations and healthcare providers or patient advocacy groups. This allows pharma teams to truly understand the conversation around various stages of product development, ultimately adding value in the process of getting a new therapy to consumers.
“AI and other technologies are helping to highlight the patient voice”
The role social media is playing
AI and other technologies are helping to highlight the patient voice, and one place where this intersection is becoming more prominent is on social media. Social media listening or monitoring allows pharma teams to understand what their patients are saying and what their needs are in terms of disease state, treatment, quality of life, and other key points.
It’s important for life science teams to harness the power of this information from social media. When teams use social listening (formulating the unstructured data provided on internet conversations into actionable insights) to analyse these discussions, it can help to really understand the patient voice and then amplify this voice back into the drug or device development process. Patients may not be aware of this part of the process, but their conversations can ultimately have a positive effect on the treatments, support, and other resources pharma organisations can offer.
Social media also captures more of patients’ raw emotions and feelings. When they discuss these matters with a doctor, the insights end up becoming very structured with the doctor acting as a third-party mediator between the patient and pharma company. Instead, social media allows for a freer flowing conversation, which can create some of the strongest insights when posts and social media conversations are monitored through processes like social listening.
What is next for AI
If you look back at the past ten years, pharma teams have seen science change first-hand as products come and go. But among all the remarkable innovations, one of the most significant has been the evolution of the patient voice. Patients are becoming more aware of the products in the market, are more curious about how exactly how these can help treat them, and are passionate advocates for their own health.
Some uses of AI collate all the information you need in the moment, at speed. It then works to show why that information or impact is important – getting the strongest piece of data from a sea of information. It works to ensure important insights won’t fall through the cracks, saving professionals time and giving added security to the decisions they make.
