The world is rapidly moving towards the adoption and seamless integration of artificial intelligence (AI), including machine learning (ML) as a subset of AI, throughout our daily lives. As a society, we are just now beginning to see how this technology will become an omnipresent part of life in the coming decades.
Health care, including the pharmaceutical industry, is not immune to this adoption. Conversely, various stakeholders within the health care industry can be found leading the charge with the adoption of AI and ML into strategic planning and business models. In a recent survey of more than 50 executives from health care companies currently leveraging AI technology, greater than 50% of all respondents believe that AI will be ubiquitous within health care by 2025, while more than 25% of all respondents felt that a nearly ubiquitous adoption of AI would occur by 2025.1
As a profession, pharmacy can still face challenges in proving the value it contributes to the health care space as a whole. As time progresses, it is likely that the swift adoption and effective use of AI technology will help to solidify the future value of the pharmacy profession.
Specialty pharmacies that desire to be competitive leaders in the field should be early adopters of available AI and ML technologies. These technologies should be viewed as a forward-looking, long-term investment in an asset that will enable differentiation in the market now and for years to come.
By investing in emerging AI technologies, a specialty pharmacy is sending a signal to the market that it is looking to the future. Through the eyes of manufacturers, prescribers, and payers, such investments will position the pharmacy as a partner that will enable their patients to receive the highest level of precise care, with the greatest potential for positive outcomes at the lowest achievable costs.
How will specialty pharmacy leverage AI and ML to ensure the most beneficial outcomes for all stakeholders? The use of AI will enable an even greater level of personalized, high-touch care for patients. While already a hallmark of specialty pharmacy, this type of care will be augmented by AI technology in the coming years.
AI will enable specialty pharmacies to provide care in a more precise manner to individual patients, with a focus on prevention and personalization that has not yet been seen. This increase in personalization will be symbiotically related to the ability of AI to process and analyze large amounts of data in a hyper-efficient manner.
Improvements in budgeting, lower operational costs, and improved overall organizational efficiency will be seen as a positive result of AI data analysis. For instance, although not directly related to pharmacy, a University of Toronto professor has recently used AI technology to plan radiation treatment for patients.
This advancement allowed for the completion of treatment plans in 4 minutes, itself a fractional amount compared with the previous average of greater than 2 hours, prior to the implementation of the AI technology.2-4 This same concept of exponentially increased organizational efficiency can be applied to pharmacy platforms for patient therapy, including within the specialty pharmacy arena.
Most importantly, the increase in efficiency gained elsewhere throughout the organization will be the catalyst that enables pharmacists (and other clinicians) to devote even more time providing personalized, detailed, high-touch care to their patients. Developing approaches to personalized drug combinations that treat various disease states, working towards increased understanding of disease processes, enabling a better and more efficient design of effective treatment options, and research and development of both diagnostic and treatment options in multiple areas are all ways in which manufacturers will continue to leverage AI and ML in their business models.
Clearly, companies such as these will want to partner with like-minded pharmacies that also use sophisticated technology as part of their strategic and business planning. As an example dating to 2016, IBM’s Watson Genomics (offered through IBM Watson Health) formed an alliance with Quest Diagnostics to leverage AI in the understanding of disease states.
In particular, this partnership seeks to further develop the field of precision medicine with an integration of cognitive computing and genomic tumor sequencing.5 With a focus on developing approaches to personalizing drug combination therapy for acute myeloid leukemia (AML) through an increased understanding of precision medication, Microsoft’s Hanover Project has partnered with the Knight Cancer Institute in the advancement of AI and ML technologies to positively impact outcomes for AML patients.5