Revolutionizing Laboratory Information Management Systems With IoT and Smart Technology
IoT-enabled LIMS boosts lab efficiency with real-time data, automation and compliance, transforming workflows and sample tracking.
Complete the form below to unlock access to ALL audio articles.
Laboratories face growing demands for efficiency, accuracy and compliance in managing complex data and workflows. To meet these challenges, many are adopting Internet of Things (IoT)-integrated laboratory information management systems (LIMS). This combination enables real-time data exchange, task automation and enhanced process visibility, supporting precise sample tracking and regulatory compliance. This article explores the benefits, key applications, challenges and future directions of IoT-enabled LIMS.
Enabling a fully connected lab
By incorporating an IoT-enabled LIMS, laboratories can foster an interconnected environment where instruments and analytics tools communicate more efficiently. This enhances operational efficiency, streamlines workflows, reduces costs and ensures precise data collection, even in high-throughput settings. One example of the benefits of such interconnectedness is in smarter sample management. Sample management is critical, especially in labs that handle thousands of samples daily.
With integrated IoT sensors able to monitor vital conditions such as temperature and humidity, IoT-enabled LIMS helps labs maintain sample integrity. These sensors provide continuous feedback and trigger alerts for quick responses to storage changes, preventing degradation. This proactive approach preserves sample quality, enhances traceability, helps ensure compliance with relevant regulations and reduces the risk of costly sample losses.1
Automated documentation and predictive maintenance transform laboratories
Professor Karnik Tarverdi, Director of Extrusion Technology at the Wolfson Centre for Materials Processing, Brunel University of London, states, “Compliance is vital for clinical and pharmaceutical labs, which require accountability and traceability for regulations such as ISO 9001 and 17025. Relying on manual documentation risks compliance issues developing through the introduction of errors and inefficiencies. IoT-enabled LIMS with cloud integration avoids these risks, ensuring accuracy, efficiency and compliance.”
IoT sensors, for example, are crucial for continuously monitoring environmental parameters such as humidity and temperature in stability chambers. They may send out real-time notifications in the event of abnormalities. Automated documentation is distinguished by this degree of accuracy and dependability, which guarantees full traceability and helps labs meet compliance requirements.
Cloud integration is also beneficial because it improves productivity by offering safe data storage, quick reporting and simple access to past documents. Labs can retrieve years of data in minutes, significantly reducing the burden of preparation during audits.
As Tarverdi notes, “Automated documentation systems are essential for maintaining compliance, boosting productivity, and staying competitive in the ever-evolving laboratory environment as regulatory requirements continue to shift.”
The integration of IoT systems in the lab can also enable predictive maintenance by monitoring equipment health to flag failures before they happen. Sensors track performance metrics, identifying early signs of wear and allowing proactive maintenance to be scheduled. This reduces downtime, extends equipment lifespan and ensures efficiency. For instance, IoT-enabled LIMS can alert technicians when a centrifuge requires servicing based on its past usage, minimizing costs and avoiding disruptions to critical workflows.
AI and edge computing: Transforming the data landscape
As IoT becomes integral to lab operations, advanced technologies such as artificial intelligence (AI) and edge computing can offer additional layers of capability. AI algorithms can assist with the processing of the extensive datasets generated by IoT sensors, revealing insights that drive data-driven decisions and operational improvements. For instance, predictive modelling powered by AI can help labs anticipate trends, optimize workflows and enhance resource utilization by uncovering patterns that might not be immediately obvious.
Edge computing is a networking philosophy that moves the processing of data closer to where it is generated, thereby reducing latency and also bandwidth use. In labs, edge computing enables faster data analysis, which is critical for high-stakes research, such as personalized medicine or diagnostics experiments. By minimizing dependence on centralized cloud systems, edge computing enhances data privacy - a valuable feature in clinical environments where data security is crucial.
Integrating robotics for automated sample preparation
Integrating robotics with IoT-enabled LIMS has revolutionized sample preparation, a traditionally labour-intensive task. By connecting LIMS with robotic systems, labs can automate processes such as sample aliquoting and labelling and sorting, reducing human error and enhancing reproducibility.
In a high-throughput environment, IoT-enabled robots efficiently handle routine sample management tasks, allowing lab personnel to concentrate on more complex analytical work. Additionally, robotic automation ensures consistent sample handling, which reduces the variability often introduced by manual processing. This level of precision not only increases throughput but also aligns with the rigorous standards required in regulated industries such as pharmaceuticals and biotechnology.
Data analytics, security, and real-time decision-making
IoT-enabled LIMS transforms labs by enabling real-time data collection and analytics for immediate, data-driven decisions. IoT devices monitor lab parameters such as environmental conditions and equipment performance, allowing managers to analyse trends, optimize workflows and respond proactively. For example, IoT systems can alert staff if temperature or humidity measurements exceed safe ranges, protecting samples and experiments while ensuring reliable results.
Data security and privacy are critical for IoT-enabled LIMS. Labs must implement encryption and multi-factor authentication and comply with regulations like GDPR and HIPAA.2 Cloud-based LIMS enhances security with audit trails, backups, and restricted access, ensuring sensitive data is protected. IoT devices also monitor for breaches, maintaining high standards of data integrity and privacy.
Towards a global network of labs
The future of IoT in laboratories promises greater connectivity and efficiency. With 5G technology, IoT devices will enable faster, more reliable communication for real-time applications, including remote equipment monitoring and virtual labs.3 AI advancements will enhance IoT-enabled LIMS with predictive analytics and automated decision-making for research and diagnostics.
IoT shows potential in multi-omics research and personalized medicine by facilitating data collection and analysis. Labs can collaborate with healthcare providers using IoT-enabled diagnostic tools like smart blood analysers, networked imaging devices, and wearable health monitors to transmit patient data in real-time.
This connectivity allows labs to receive immediate updates on patient health metrics, such as glucose levels, heart rate or oxygen saturation, directly from wearable devices.
“Subsequent benefits of this technology include earlier detection of health problems, which would decrease the potential resource burden on healthcare,” said Sheri Scott, a senior lecturer and biomedical scientist at Nottingham Trent University.
“Faster intervention would decrease the likelihood of hospital admissions or trigger earlier interventions, thus reducing overall costs of treatment and decreasing the overall carbon costs of healthcare,” Scott continued. “A further benefit could see a reduction in waiting times for other patients and result in potential workload decreases for healthcare professionals.”
IoT can integrate with lab equipment such as automated handlers and sequencing machines to centralize data seamlessly. This hub analyses trends and shares insights with healthcare providers securely. For example, a detected change in biomarker levels can trigger instant alerts, enabling faster healthcare decisions and personalized treatments.
“Although IoT-enabled LIMS promises many benefits - including faster diagnosis and quicker subsequent interventions - professionals’ exhibit concerns over the standardization, costs, security and potential biases resulting from the training data used for the tech,” Scott cautioned. “These are valid concerns and they would need to be addressed before wide-spread adoption can occur.”
Despite these concerns, with healthcare seeking new environmentally sustainable ways of working, IoT is a clear potential tool to support healthcare’s sustainability agenda.
Challenges and the future outlook for IoT-LIMS Integration
Despite its benefits, IoT-enabled LIMS presents challenges. Labs must be aware of potential issues with network compatibility, ensuring interoperability and integration with existing systems. Security is a key concern, requiring robust data protection and continuous monitoring. Additionally, evolving regulations necessitate systems that can adapt to new compliance standards. High upfront costs may also deter smaller labs, making cost-benefit analysis and scalable solutions critical for IoT adoption.
The integration of IoT with LIMS has the potential to completely revolutionize laboratory management, delivering connectivity, automation and data-driven insights beyond what has been seen before. It can enhance workflows, from sample tracking to predictive maintenance and real-time analytics, creating more efficient and reliable labs. As IoT evolves with AI, 5G and edge computing, labs will gain even greater precision and agility.
For cutting-edge research, IoT-enabled LIMS is essential to streamlining processes, boosting capabilities and accelerating discovery, with future innovations promising to redefine lab operations.
References
1. Srivastava AK, Das P. Chapter: Smart laboratories and IoT transformation. In: Biotech and IoT. Apress; 2024:37-73. doi: 10.1007/979-8-8688-0527-1_3
2. Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation) [2016] OJ L 119, 04.05.2016; cor. OJ L 127, 23.5.2018. http://data.europa.eu/eli/reg/2016/679/2016-05-04. Accessed February 2025.
3. Ahmed SF, Alam MdSB, Afrin S, et al. Toward a secure 5G-enabled Internet of Things: A survey on requirements, privacy, security, challenges, and opportunities. IEEE Access. 2024;12:13125-13145. doi: 10.1109/ACCESS.2024.3352508
