How can AI enhance patient adherence to prescribed medications and maximise the therapeutic potential of new and existing drugs?

AI alone won’t solve the challenges of medication adherence – it’s the convergence of AI with advances in point-of-care testing, remote diagnostics, digital health solutions, and passive biomarker monitoring that will truly transform patient care. These technologies allow us to build a complete and real-time picture of a patient’s health. AI and machine learning (ML) can then analyse this data to understand individual behaviours, perceptions, and physiological responses to medications. This enables us to determine not just whether a patient is taking their medication but also why and how – and critically, whether the medication is working as intended.

The most significant breakthrough will come from using AI to personalise medicine at the individual level. Most drugs are developed and tested in controlled clinical trials with highly homogeneous patient groups, which don’t fully represent real world populations. By integrating AI-driven insights with real-world patient monitoring, we can optimise dosages, minimise side effects, and maximise therapeutic benefits – ensuring each patient gets the most effective treatment tailored to their needs over time.

Can AI Lead to Better Health Outcomes and Improved Efficiency in Healthcare Systems?
Absolutely. Healthcare systems, particularly those like the NHS with a cradle-to-grave patient ID system, hold vast amounts of valuable data at a population level. AI can analyse these datasets to uncover patterns, predict risks, and optimise care delivery which leads to better outcomes and cost efficiencies. However, AI’s impact is only as good as the data it’s trained on.