AI has already made its mark in healthcare with applications in medical imaging, drug discovery, and virtual wards among others. It’s often referred to as the “new electricity”, analogous to how electricity revolutionized industries by increasing efficiency and reducing costs. The transformation of the automobile industry from steam power to electric power represents a paradigm change enabled by electricity. Similarly, AI has the potential to bring about a paradigm shift in healthcare.
Currently, AI applications in healthcare are mostly stepwise, improving single processes or applications. However, these are just the initial steps towards embracing a new technology. AI has already demonstrated its ability to change paradigms in other industries; for instance, the taxi industry and the gig economy have been transformed by AI applications for automatic directions and traffic routing.
In 2021, the UK government laid out a 10-year strategy to transform the life sciences sector and capitalize on the advances seen during the COVID-19 pandemic. With 300,000 people working in the life sciences sector and four of the world’s top 10 universities in life sciences, the UK is poised to be at the forefront of this transformation. However, the slow processes for getting drugs into clinical trials and challenges in navigating the approval and reimbursement process in the NHS indicate that more can be done to streamline and increase efficiencies in regulation and market access.
The Pharmaceutical industry is increasingly receptive to AI. Alongside clinical advances, AI can speed up regulation and market access data gathering and decision-making. However, there are still unanswered questions about transparency, privacy, and data ownership. The NHS AI lab has been set up to develop AI capability within the organization and the NICE AI and Digital Regulations Service has been developed to support innovators in navigating the regulatory system.
AI can create paradigm shifts in how clinical evidence is created, analyzed, and interpreted. There’s a future vision where AI supports clinical trial selection and recruitment, thereby reducing risk for participants. Through detailed analysis, AI may be used to understand and target treatment directly to the patients who will benefit most, thereby reducing unwanted side effects and unsuccessful outcomes.
This shift would require a different way of thinking, moving from individual drug candidates going through lengthy and costly trial and approval processes to portfolios of drugs designed to treat different target populations. This shift, inspired by the COVID-19 pandemic, would spread risk across portfolios and provide better choices and outcomes for patients.
The transformative potential of AI in healthcare is significant. As it continues to evolve, it has the potential to improve efficiencies, enhance patient care, and revolutionize the industry as a whole, much like how electricity transformed industries over a century ago.
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