As the common saying goes, the only constant in life is change. On similar lines, rapidly evolving technology and the use of machine intelligence is playing a vital role in the changing human life. We moved from the age where we used to think about “Can machines think?” to primitive forms of artificial intelligence (AI) by delegating responsibility to machines.
A recent Intelligence Unit report stated that one of the biopharmaceutical services companies driving AI in clinical trials, found that big data innovations reduced time for recruitment in clinical trials by 37% and that drugs developed with new AI tools were 16% more likely to reach market launch1. McKinsey estimates that big data and machine learning in pharma and medicine could generate a value of up to $100B annually, based on better decision-making, optimized innovation, improved efficiency of research/clinical trials, and new tool creation for physicians, consumers, insurers and regulators.
There are some common challenges in the pharmaceutical sector. These include a lack of consistency in the deliverable outcomes and challenges in meeting committed timelines as well as in hiring and onboarding the right talent pool with apt skillsets. Repetition of errors is another impediment as is getting work schedules in the pharmaceutical manufacturing sector and dashboards in research and development (R&D), among other challenges.
Advances in pharmaceutical R&D and manufacturing technologies is demanding more productive outcomes with consistent quality. AI is economical and more productive than traditional way of working with existing processes and manpower.
The US Food and Drug Administration (FDA) is encouraging AI-based devices and algorithms for treating medical conditions. This was evident with the recent FDA news release dated May 24, 2018, ‘FDA permits marketing of artificial intelligence algorithm for aiding providers in detecting wrist fractures’. During this occasion, FDA’s acting deputy director for radiological health, Office of In-Vitro Diagnostics and Radiological Health in the FDA’s Center for Devices and Radiological Health, said that “Artificial intelligence algorithms have tremendous potential to help health care providers diagnose and treat medical conditions”.
Another FDA news release dated April 11, 2018, stated that ‘FDA permits marketing of artificial intelligence-based device to detect certain diabetes-related eye problems’. These aforementioned permits from the FDA are pathfinders for futuristic revolution in pharmaceutical R&D and the majority of pharma giants will go into this direction. AI will play a key role in steering this change in dynamics.
Meeting the current requirements would only be possible by upgrading current processes and balancing strategies in areas, which are redundant, and by optimizing human skills through AI.
The pharmaceutical industry can thrive by connecting its empathy and creativity through regulatory insights. The balance between repetitive, routine, and optimizing strategies with its empathy needed/not needed will give a better judgment to proceed in this area.
Figure 1 represents optimization of AI strategies with empathy and creativity. AI in pharmaceutical sector includes tracking initiatives, routine process steps, analytical works, data evaluators, data feeders, data monitors, and operational efficiency among others.
The right balance between platform automation and use of AI will give a significant benefit in tracking day-to-day R&D and manufacturing activities within the pharmaceutical sector. The AI revolution in pharma R&D can be achieved through automation in workflow tracking, collation of data, quality checks, and formatting linking it to AI in pharma.
Considering the fast changing technology, AI in pharma is massively transforming the pharmaceutical world, but it cannot bring along empathy and creativity. In the larger context, we need to consider AI as an opportunity. It is helping to liberate us from routine jobs and has the potential to remind us what it is that makes us human.
The need of the hour is wise investment in technology drivers such as digitalization and automation of processes at the right time by creating the platforms, which can deliver the right results by utilizing aforementioned tools through AI. This will enable the development process to be stronger and get faster outcomes.