The pharmaceutical industry is looking at artificial intelligence (AI) to have a major impact on the future of medicine as relationships between pharma corporations and AI researchers are already flourishing in the hopes of one day providing a faster and more reliable digital health care service to patients around the nation.
AbelsonTaylor Associate Director of Interactive Development Chris Mauck recently published an article outlining the many aspects in pharma for which AI is currently being used. This includes discovering new drugs with “blazing speed,” identifying and diagnosing diseases, clinical trials, personalized treatments, risk prediction and sales-force assistance. Mauck stated that other uses will soon be discovered as well, specifically in sales.
“Quality data collection and analysis tools can be a game-changer for optimizing the sales call,” Mauck told FDA Health News. “Companies like Aktana are working with Veeva Systems and their customers to improve the effectiveness of sales calls. Aktana parses these data and can use them to provide recommendations for future communications and sales calls based on previous sales calls, transactional data about the HCP office visit call durations, interactions with email communications, and more. When used properly, you can see how this can lead to an invaluable benefit to the sales reps in delivering the right message to the right customer at the right time.”
Mauck has been involved in web development and programming for over two decades. He currently leads a team of developers at AbelsonTaylor specializing in web, mobile app and convention-experience spaces for pharmaceutical and health & wellness clients. Future goals for he and his team are to work together with these clients to implement AI solutions into their existing ecosystems.
“As an agency, we’re looking to increase our footprint in the AI space by working with our engagement strategy and analytics teams to collect as much data as possible and build simple systems that learn from these data, which can help to inform the future models that can be used to train AI systems,” Mauck said. “The types of data collected in exercises like these are mainly experiential in nature.”
Mauck aims to introduce more manufacturers to adopting AI systems and, through their adoption, applying those same systems in hospitals and other health clinics. However, he notes that it will take a long time before anything can be fully operational.
“Pharmaceutical labs and manufacturing companies can leverage years of amassed data to inform future projects, whether they be new medications, medical devices, procedures and more,” Mauck said. “Following the manufacturers would be the hospital systems and health care facilities, then filtering down to individual physicians for almost daily use. As far as a timeline is concerned, the first phase has begun. It just isn’t used consistently across the major companies yet. More localized usage will likely come over the next eight to 10 years in hospitals, and over the next 10-15 years will become commonplace in physician offices that understand the benefit or – by that time – the necessity of AI.”
Mauck also said that when the time comes, it will have to be up to physicians to decide if they are willing to allow AI into their workplace. He understands that when experimenting with AI in any health care profession, there are risks with too much personal information being exposed, but he has discovered that the systems only need a little basic information from clients in order to apply proper care.
“You don’t need to know that the person in the study was Mary Smith from Bakersfield, California,” Mauck said. “Simply knowing a patient’s age, gender, race, and general health history can greatly benefit predictive models regarding future health risks for others in the same category.”
AbelsonTaylor will continue to work on developing tools, the understanding of AI within in the industry, and fostering its acceptance until these systems can successfully assist with a person’s overall health needs.
“Digital transformation takes time, talent and investment,” Mauck said. “Those that have already begun work in the AI space are seeing benefits not only to the manufacturing and discovery processes, but also to tools used for diagnosing and treating conditions. Invest in teams, give them some parameters, but let them create and discover for you and your company.”
