The lab at the forefront: How new healthcare technologies impact diagnostics

Within the ever-evolving world of healthcare, technological advancements like artificial intelligence (AI) are no longer ‘potential’ or a ‘pipe dream’.¹ In recent years, the emergence of technologies like AI, machine learning, wearables, and virtual reality have become the norm in the current healthcare landscape.^2,3,4

One of the main benefactors of this recent transition within the healthcare field, especially in terms of assisting diagnostic processes, is clinical laboratories.⁵ But how far have the integration of these technologies come? And which technological medical innovations are showing the most promise? 

LabLeaders answer both these questions and more, analyzing the impact that new and innovative healthcare technologies are likely to have on the field of diagnostics in particular.

While healthcare may always be changing, one thing has remained constant throughout: laboratories are pivotal in the implementation and utilization of new, innovative, and emerging technologies.⁶

In fact, diagnostics is one of the biggest areas within healthcare where countries invest their budget. In England, for example, the NHS spends over £6 billion annually on over 100 diagnostic services and, over recent years, has invested nearly £250 million on digitalizing diagnostics care.^7,8

It’s not hard to see why — new, innovative, and emerging healthcare technologies not only empower labs to deliver more precise, timely, and comprehensive results, but they also contribute to making more informed clinical decisions and, ultimately, delivering improved patient care.^1,2,3,6

Let’s take a closer look at the key technologies at the heart of this transition.

One of the biggest recent developments within healthcare has been the integration of AI and machine learning — computer technologies revolutionizing how laboratories can both process and interpret data. 

Within the field of diagnostics, in particular, AI and machine learning-based algorithms can now be used to detect abnormalities and high-risk conditions more effectively and at a lower cost.⁶ AI’s role in cancer diagnostics has been particularly groundbreaking, for instance, offering patients a much less invasive alternative to traditional biopsies.^3,9

AI’s use can also identify potential issues a lot more quickly; when reviewing breast cancer mammograms, AI-based algorithms achieved 99% accuracy and finished 30 times faster than human radiologists.⁹

AI’s ability to analyze huge amounts of medical data has also caught the attention of technological behemoths like Google. Working with DeepMind, Google is currently in the process of developing AI technologies that can help improve our understanding of diseases by accurately predicting the 3D structures of proteins.¹⁰ While still in its relative infancy, there’s hope that these developments could lead to the creation of better diagnostic tools in the future.¹⁰

Machine learning models can also analyze historical medical data and imaging scans to provide more accurate patient care.³ By continuously analyzing large datasets, these models can not only identify and forecast disease progression but also help to create more personalized treatment plans around specific patient needs.

Certain other companies are also looking into how machine learning technology can be integrated into predictive medical diagnostic software.⁴ They aim to develop software that can survey biopsy results and perform routine clinical tasks to detect and diagnose HER2 cancer more efficiently.⁴

While AI and machine learning may steal a lot of the limelight, new lab technologies like automation and robotics are also playing a crucial role in the digital transformation of laboratory operations. 

By being able to automate clinical processes, laboratories can continue delivering a high-quality level of service while also balancing factors like cost efficiency, quality goals, patient safety, and increasing industry demands.^11,12

Automated systems are now capable of handling routine tasks such as sample preparation, data entry, and even complex analyses, reducing the potential for human error, increasing workplace efficiency, and, ultimately, improving laboratory processes.^3,5,13,14 This, in turn, enables laboratory personnel to focus on more complex and interpretative tasks, resulting in faster turnaround times and improved levels of diagnostic accuracy.⁶

Advances in robotics can also help in many of the same ways. While robots are already being used to handle repetitive tasks, such as sample tracking and analysis, the integration of AI with robotics could soon allow laboratories to become fully automated, gather real-time diagnostic results 24/7, and free up time for lab personnel to focus on more valuable work.¹⁴

Molecular diagnostics is another area where technology is having a huge impact — especially for molecularly-focused laboratories. Techniques like next-generation sequencing (NGS) have revolutionized the way diseases can be diagnosed, enabling laboratories to detect genetic mutations, identify pathogens, and tailor treatments to individual patients’ genetic profiles.¹⁵

NGS allows entire genomes to be sequenced rapidly and economically, providing laboratories with a comprehensive overview of a patient’s genetic makeup.¹⁶ By having this information available, lab personnel can investigate gene expression patterns and detect genetic alterations with a high level of precision.¹⁶ This may prove incredibly valuable in the diagnosis of rare genetic disorders, or the development of personalized treatment plans for patients.¹⁵

Integrating new healthcare technologies into laboratory processes is not just about improving efficiency and accuracy. By adopting these innovations, laboratories will be able to offer more precise, reliable, and timely diagnostics, leading to improved patient care.^5,6

The continued advancement of technologies like AI, automation, and molecular diagnostics look set to further empower laboratories to push the boundaries of what’s possible within diagnostics well into the future. As these technologies continue to evolve, so too will the capabilities of clinical laboratories, ensuring their seat at the forefront of innovation.