How AI, robotics and automation will reshape the diagnostic lab of the future

Laboratory test results supply the foundation for most medical decisions. However, they are likely to feature more prominently in healthcare, given persistent trends in human health. These include ageing populations, higher rates of non-communicable diseases, and upticks in early-onset cancers, obesity, type 2 diabetes and other cardiometabolic and neurodegenerative diseases.

Indeed, tomorrow’s global health hinges largely on the future of diagnostic testing. But what will clinical laboratories look like in the years ahead?

Accuracy, fast turnaround times and access will always be the pillars of quality diagnostic testing. Yet, certain conditions within the healthcare landscape threaten that vital triad. Devising solutions to ensure these pillars remain intact will be essential to advancing human health worldwide.

Over the past decade, the healthcare industry has faced a reverberating shortage of qualified professionals – from lab technologists to nurses and doctors. Burnout fatigue among overworked staff is prevalent, and its ramifications are significant. In traditional diagnostic laboratories, for instance, mislabeled samples, transcription and other human errors compromise patient safety while driving up healthcare costs.

Factor in rising prices and the scarcity of medical resources. In combination, these systemic stressors limit access to care, with the heaviest hit on remote and already-underserved parts of the world. Such ongoing challenges set off cascading consequences for patient care: diagnostic errors, delayed diagnosis and treatment or missed diagnoses completely, adding cost and resulting in poorer outcomes.

So, in today’s challenging environment, how do diagnostic labs better ensure accurate and early detection so clinicians can deliver the most appropriate treatment for the best possible patient outcomes? The smart and strategic use of new and emerging technologies is critical.

Into the mix enters artificial intelligence - (AI)-powered diagnostics (Figure 1): AI algorithms can analyse vast datasets of diagnostic data, medical images, and patient history to improve diagnostic accuracy and identify diseases earlier. These algorithms can enhance analytic capabilities and address the medical data overload that doctors face.

Notably, AI-assisted analysis can help reduce turnaround times. The sooner clinicians receive diagnostic test results, the sooner patients can begin treatment. This is pivotal, as timing is often a differentiator in how an illness responds to therapy. Moreover, AI can be a boon for personalised medicine, enabling realistic, time-efficient analysis of a patient’s unique medical history and genetic data to predict disease risk and tailor treatment plans.

For remote and underserved areas, AI-powered lab systems, with telemedicine, could expand access to care by equipping advanced diagnostics where none were available.

Lab automation is not new. Robots can already handle repetitive tasks, such as sample preparation and analysis, to improve turnaround times and reduce the risk of human error (Figure 2). But AI-powered robots of the future will handle more than the mechanical part of lab automation. They will make intelligent decisions based on the information they see. Such fully automated “smart labs” may be able to operate 24 hours a day, seven days a week and 365 days a year with minimal human supervision, thereby increasing efficiency and providing real-time results.

The advancement of humanoid robot technologies capable of performing intelligent operations without human intervention or a pre-programmed set of rules will enable scenarios wherein such robots are indeed future lab technologists – working round the clock and throughout the year.

Staff shortages, a slowdown in the number of professionals entering the field and the need for existing professionals to remain focused on higher-level tasks will make a monumental difference in the ability of labs to keep pace with demand.

Using digitally connected diagnostics and drawing from vast amounts of data generated during the diagnostic process, smart labs running on AI and robotics will also be able to identify trends, patterns and correlations that might otherwise be missed. That translates into the prediction of disease outbreaks, the identification of high-risk populations and contributions to epidemiological and pandemic research.

AI-based analytical tools that are scalable, easy to use and transparently deployed can help interpret data to improve decision-making, especially during rapidly evolving public health crises. We learned from the COVID-19 pandemic that actionable clinical data can inform prompt evidence-based policymaking and adjustments to healthcare systems.

Multiple obstacles must be overcome when adopting any new technology. The same is true for the diagnostic lab of the future. Access to data and its use poses significant challenges but these will continue to improve as the World Health Organization (WHO) and other agencies work on global health data standards. Notably, we must avoid creating a further divide in healthcare inequity by making the availability of these solutions universal.

While on the face of it, these proposed solutions may seem like machines are taking over our world, in reality, they can support improved quality of life for both patients and lab staff. Using automation, robotics and AI will help address existing problems while providing greater benefits – ultimately improving diagnostic laboratory services. Smart labs will likely become central to healthcare infrastructures as technology advances. By changing how medical tests are carried out and diagnoses made, they may, in turn, attract future workers.

We are at an inflection point and must improve health outcomes globally. Investing in the diagnostic lab of tomorrow will help us sustainably meet the impending shifts in world populations, healthcare systems and the state of global health. The diagnostics industry is ready for a new future. By embracing it, we can better ensure a healthier tomorrow for everyone.