The integration of technological advancements is shaping the growth of the clinical diagnostics industry, and it is poised to transform patient needs by empowering clinical decision-making.
By Sonali Patranabish
A shift from a curative to a preventive mindset has spurred the integration of technology and digitisation into clinical laboratory diagnostics. Today, AI-powered diagnostic capabilities are being leveraged to expedite disease diagnosis and evaluate risk factors in the healthcare realm. AI models across various clinical diagnostic platforms have proven to outperform human decision-making.
Traditional laboratories, hence are seeking to integrate such cutting-edge technologies into their existing systems seamlessly to improve operational efficiency, workflows and laboratory footfall.
Time plays a crucial factor in gauging the effectiveness and efficiency of a diagnostic laboratory. The turnaround time is a benchmark and a differentiator that sets automated laboratories apart from their counterparts. In the wake of the need for early diagnosis and improved patient outcomes, today diagnostic laboratories have embraced digitisation and integrated cutting-edge technology into the otherwise traditional laboratories in response to the sample volumes.
USP of automated labs
Managing colossal amounts of data and samples without compromising quality, precision, and efficiency has been the USP of automated and digitised laboratories. Improved workflows, better operational efficiency, better productivity, and individualised solutions are benefits of automating laboratories in the 21st century. In recent times, the automation portfolio of laboratories has expanded, incorporating customised systems and improved connectivity.
Key drivers behind digitising laboratories
Automation and digitisation have become a game changer for the diagnostics sector, considering this a warranty to success. It opens up many avenues and opportunities to power their growth story while serving as a critical enabler in scaling operations. Clinical laboratories have undergone a rapid transformation; Laboratory 4.0 has risen amidst the revolution in healthcare-personalised medicine.
Dr Venkataswamy Eswarachari, Lab Director, MedGenome, opines that laboratories' increased uptake of digitisation is due to the rising demand for personalised medicine.
He states that digitisation helps laboratories provide patients with a holistic perspective of clinical data. “This integration is particularly critical in personalised medicine, where precise analysis of complex datasets is essential for selecting the most appropriate therapy for an individual,” states Dr Eswarachari.
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Automation and digitisation have become game changers for the diagnostics sector, which considers them a warranty to success. They open up many avenues and opportunities to power their growth story while serving as critical enablers in scaling operations.
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The pandemic has also been a wake-up call for laboratories to upscale their operations. The need of the hour during the pandemic was to shift gears and step up laboratory operations using improved software and instrumentation.
Professor Praveen Sharma, Scientific consultant at Snibe Diagnostics, said that the rapid growth in the automated segment of clinical laboratories has been due to increased public attention towards healthcare. He further adds that the rapid growth of the Indian automated diagnostics sector has been due to increased clinical demand and the evolving unique needs of the population.
Today, laboratories have moved beyond the number game and are no longer seen as data-generating factories. Laboratories are donning the hat of decision makers and find themselves engaged in more complex and analytical roles rather than routine reporting tasks of figures and data.
Dr Venkataswamy further adds that compliance with regulatory standards has been one of the major causes for the uptick in automated laboratories. He states, “Automated systems help
laboratories meet strict requirements for sample processing, data management, and patient confidentiality by maintaining secure records and audit logs.
Additionally, automation liberates resources for innovation, facilitating the development of new diagnostic methods.”
The rise of intelligent laboratories
Laboratories have strategically shifted their expansion plans not only in terms of geographical outreach and product portfolio but also in terms of upgrading and powering their laboratory performance and productivity by integrating advanced analytical technologies to improve the operational efficiency of laboratories.
Due to the rising disease burden, there has been a concomitant rise in laboratories adopting automation and digitisation.
Abbott has recently introduced the GLP systems track to streamline laboratory operations by reducing errors and minimising manual steps by 80 per cent.
These systems have many benefits, including improved lab workers, safety, workflow, and productivity. Mumbai-based Kokilaben Hospital has included Total Lab Automation (TLA) powered by Roche Diagnostics to enhance patient care. The TLA platform aims to transform traditional lab operations by leveraging data analytics and robotics. The TLA at Kokilaben ensures better turnaround time, accurate results, and real-time monitoring.
AIIMS has also upgraded their laboratory facilities. The SmartLab at AIIMS offers a cohort of laboratory testing services as part of their end-to-end total laboratory automation platform.
The SmartLab samples close to 5000 to 6000 samples.
Dr Rajesh Bendre, National Technical Head and Chief Pathologist Apollo Diagnostic, Mumbai, states that innovative labs use robotics for repetitive tasks and intelligent decision-making and require minimal human supervision. He further adds that these smart laboratories are automated with cutting-edge technologies and data-driven systems to improve efficiency, productivity, and smooth flow of operations.
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Mumbai-based Kokilaben Hospital has included Total Lab Automation (TLA) powered by Roche Diagnostics to improve patient care. The TLA platform aims to transform traditional lab operations by leveraging data analytics and robotics. The TLA at Kokilaben ensures better turnaround time, accurate results, and real-time monitoring.
Ruby Hall Clinic, a chain of multispeciality hospitals in India, has launched TLA as part of its diagnostic services, a first in Pune. This technology will enable improved accuracy, eliminate manual errors, and significantly reduce operational costs.
Robots in labs also help to streamline laboratory processes by automating a gamut of applications while minimising errors, handling repeated tasks and ensuring timely diagnosis while not compromising on accuracy.
Quidelortho’s Vitros Automation Solution, a robotic automation system for blood testing, was recently launched at the Sri Ramakrishna Hospital, Coimbatore. This AI-powered diagnostic tool has revolutionised clinical diagnosis by delivering reliable and accurate blood test results, elevating patient experience to another level. This innovative technology is high in precision, efficiency, and consistency while empowering doctors to make informed and prompt decisions regarding patient treatment.
While apprising Indiamed Today on the efficiency advantage of automated laboratories, Dr Bendra said, "By opting for electronic lab notebooks (ELNs) and laboratory information management systems (LIMS), institutions can ensure a higher standard of data quality while cutting down the time spent on manual documentation.”
Channels for affordable diagnosis
Integration of AI, data analytics, ML and robotics AI and the IoT have proved to be major disruptors in laboratory automation. The diagnostic space post-pandemic has witnessed significant changes by embracing tech-based solutions as part of laboratory operations. Disruptive digital technologies like AI, ML and IoT have significantly impacted diagnostics. These technologies have created channels for affordable diagnosis, early diagnosis, better disease management and improved patient outcomes.
Dr Eshwarachari states that these technologies boost laboratories' efficiency, accuracy, and security, propelling the advancement of next-generation diagnostic services.
“These innovations have transformed data analysis by detecting patterns in large datasets, accelerating processes, and improving accuracy. The IoT plays a crucial role by enabling real-time monitoring and control of laboratory environments,” states Dr Eshwarachari.
AI has become a powerful and supportive tool, aiding clinicians in making better clinical decisions. For instance, the qTrack dashboard is an AI application launched by Qure.ai that uses deep learning to analyse chest X-rays for abnormalities. AI serves as an essential tool often used by hospitals for screening TB, lung, and breast cancer cases. A non-profit organisation, Wadhwani A, I has also been creating AI-based solutions for TB detection.
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The IoT plays a crucial role by enabling real-time monitoring and control of laboratory environments. AI has become a powerful and supportive tool, aiding clinicians in making better clinical decisions.
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At a recent AI summit held in Mumbai, NVIDIA’s MD Vishal Dhupar commented that AI healthcare companies are adding value to the existing diagnostics space in India.
The plethora of tasks that AI can accomplish seems mind-boggling. Prediction and precision stand out as prime features of AI-based diagnostic tools. Deep learning algorithms churn out an analysis of images from X-rays, CT scans and MRIs and analyse them very intuitively, way beyond human capabilities.
AI-enabled diagnostics offer life-saving attributes, like early disease prediction, prediction of disease outbreaks, patient response to treatments by analysing patterns and more. AI has also been integrated even into allergy testing technology.
Metropolis Healthcare has launched an AI-powered allergy component testing that enables clinicians to make proactive decisions to create an individualised treatment regimen for their allergic reactions.
Given the rising incidence of disease and cancer, AI has become a default option as part of emerging medical technologies like X-rays, CT scans, MRIs, angiograms and even mammograms.
Siemens Healthineers, a leading medical diagnostics company, has been instrumental in setting up an integrated diagnostic testing analyser, Atellica CI at Mahajan Imaging and Labs.
Enabled with AI, this autoanalyser can test 200 samples across 20 disease conditions in just 14 minutes while ensuring accuracy and precision, reducing errors and ensuring enhanced operational efficiency. Digital microscopy enhanced with AI is a pause for a country struggling with a shortage of pathologists and trained microbiologists. A shortage of pathologists and trained laboratory technicians has urged this sector to transform.
The integration of AI has revolutionised pathology while ensuring precision and accuracy. Intelligent microscopy enabled by AI-based analysis has been supporting patients battling cancers, anaemia, malaria, dengue and other critical and infectious diseases. AI-powered microscopy is indeed magnifying andaugmenting microscopy using real-time data analysis.
Miclays, an AI-integrated digital microscopy platform developed by Medprime Technologies, is endowed with prime features. Apart from having features like high speed and resolution, the technology also offers whole slide imaging, view with robotic remote control, manual microscopy and AI-assisted diagnosis.
SigTuple, a medtech start-up, offers digital microscopy solutions enabled by AI and robotics.
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The integration of AI has revolutionised pathology while ensuring precision and accuracy. AI-powered microscopy is indeed magnifying and augmenting microscopy using real-time data analysis.
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This innovative technology can capture high-resolution images, which are then analysed using AI. igTuple claims that the analysis can take almost a minute, helping technicians to analyse as many as 300 to 400 samples in a day.
“The use of AI, data analytics, machine learning, and robotics is rapidly transforming disciplines like microbiology and molecular diagnostics. In microbiology, advanced algorithms analyse vast genomic datasets to identify microbial genomes rapidly, streamlining the path from diagnosis to targeted treatment,” says Dr Bendre.
Challenges and impediments
While laboratories have shifted their approach towards traditional testing methods, bringing an overhaul to the system, adopting digital technologies has often been met with challenges and roadblocks.
Laboratory automation presents immense potential through increased laboratory footprint, the ability to manage high sample volumes and quality testing. However, this transformative sector has its own set of challenges. “Integrating modern digital systems with existing workflows can lead to disruptions and necessitate expensive employee training,” reiterates Dr Eswarachari.
He adds that digitising labs involves handling sensitive patient data, which heightens the risk of cyber-attacks, making robust cybersecurity measures essential. Dr Eswarachari states that compliance with stringent data protection laws, such as HIPAA in the US and GDPR in Europe, adds another layer of complexity.
Interoperability, i.e. compatibility of newer automation systems with existing systems, poses a significant challenge. Often, these adjustments lead to a disruption in the workflow of the existing systems. Other obstacles include data accuracy and integrity; given that automated labs generate large volumes of data, minor errors and anomalies must be noticed as these can have an overbearing effect on the final result.
Dr Bendre states a few other challenges in the uptake of digitisation by laboratories, i.e. evolving regulation on data security and accreditation bodies, and user training needs and adoption. While AI empowers all healthcare stakeholders, it handles automated systems integrated with technologies like AI and ML, which will require a certain amount of upskilling to operate new systems. Upskilling laboratory workforce with skills to handle such new systems often comes across with a lot of hesitancy.
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Since automated labs generate large volumes of data, minor errors and anomalies must be noticed, as these can have an overbearing effect on the final result.
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One of the downsides of automating labs is the high cost of installation. Labs often have to deal with space constraints to accommodate hardware and machines. Installing TLA systems entails high costs in modifying the ambient environmental conditions by setting up robust air conditioning systems and soundproofing.
Phasing out redundancies
Medical technology is a dynamic field, with advanced iterations of hardware and software flooding the market every few years. This makes machines acquired by labs previously redundant and obsolete. Acquiring such variants for laboratories to stay up to date can require a substantial amount of investment.
The diagnostic sector fueled by automation is expected to see robust growth and steadily expand. The rising incidence of NCDs, increased awareness of health, popularity of personalised and preventive medicine and other factors are expected to urge labs to bring about an overhaul in their system to improve operational efficiency. The landscape of the laboratory will be shaped by sophisticated laboratory techniques and the integration of data analytics, robotics, informatics, and AI, all of which will ensure precision, accuracy, efficiency, and improved patient outcomes.
With clinical decision-making heavily reliant on diagnostics, automation has become a burgeoning need to keep up with the emerging demand. Despite several constraints and challenges, laboratories are increasingly adopting automation as a strategic move to fuel their growth story.
