In June 2013, a Canadian medical lab, Lifelabs, lost patient files and personal information of more than 16,000 patients. A computer sent for servicing was returned without its hard drive, containing valuable ECG results gathered at three local facilities between 2007 and 2013. Its lab data management failed due to its enormous cost.
More recently, in April 2023, a ransomware attack at a medical testing lab, Enzo Clinical Labs, based in New York, caused a serious data breach, exposing more than 2.5 million customers. Personal data, medical files and lab results were compromised.
Theft and destruction: Today, holding critical data on hard drives is risk-prone and not considered best practice. They’re a single point of failure, and this centralised storage is vulnerable to destruction, theft and corrupt data. While no system is impervious to being attacked, measures around the privacy of your customers, lab research and confidential information must be taken seriously.
The Investigator pointed out that “healthcare providers are prime targets for ransomware attackers. They sometimes have less robust IT systems and have a high incentive to pay the ransom to regain control of systems and protect patient data.”
Old data: Another serious issue is data loss due to the unsuccessful transfer of physical medical files and data to electronic versions. Today, data is lost at a rate of 17% annually, and 80% of datasets older than 20 years are no longer available.
- How robust are the privacy measures around your lab’s research data?
- Are you confident that your files are secure?
- Are your old and historical data archived properly?
Find out how eLabNext can provide a solution for your lab requirements.
In this blog, you will find:
- What is Lab Data Management (LDM)?
- What digital platforms does your lab need?
- What happens when your LDM fails?
- What are the priorities of lab data management?
- A checklist of a proper lab data management system
- How did you rate?
- An elegant, all-in-one lab data management solution
Let's begin!
What is Lab Data Management?
Lab Data Management (LDM) is the systematic organisation, storage, retrieval and analysis of data generated in a laboratory environment. This encompasses samples, inventory, experiments, findings, instruments, photos and more. It is crucial and central to many industries and disciplines, including biology, chemistry, physics and environmental sciences.
The primary goal of lab data management is to ensure that data is:
- Accurately recorded
- Securely stored
- Easily accessible for analysis and reporting
It’s imperative to assess the scalability and flexibility of the system to accommodate future growth and changes in research teams. Beyond that, its users are human beings with a mix of IT savviness, so user-friendly interfaces and ease of integration with existing laboratory instruments and systems are pivotal in decreasing human input error and accidental data removal.
A good LDM system will factor in the following:
- The size of the laboratory
- The complexity of experiments
- Data security requirements
- Regulatory compliance needs
- Budget constraints
A successfully implemented LDM mitigates theft, loss of data and human error.
What digital platform does your lab need?
It’s important to understand the differences in labels and offerings out there so that your lab has the best digital platform for its needs, objectives and flow. Broadly speaking, there are LIS platforms and ELN platforms.
LIS has increasingly (and confusingly) come to mean a few different things: Lab Information Systems and Lab Inventory Systems.
ELN is an electronic lab notebook platform. It is meant to replace physical notebooks found in labs.
Very few LIS or ELN platforms today offer a complete lab solutions platform for inventory, protocol and journaling that all labs need. Most are complicated, require third-party software that forces disparate software to work as one and are not as versatile with cross platforms.
Do you know which platform is best suited to your needs? Why?
Make sure you check out our next blog, where we deep dive into these different platforms and compare elements to aid you in ensuring the platform you use for your lab is best suited to your needs.
Information integrity today: when a LDM fails
Today, information is money. Medical facilities and research labs come under attack because of the rich content of personal information, including addresses, passwords, contact details, health vulnerabilities, patent information, corporate secrets and research findings. They are targeted in various ways, including:
- Ransomware Attacks Cybercriminals may deploy ransomware to maliciously encrypt critical medical and research data, demanding a ransom for its release.
- Data Breaches Attackers may aim to steal sensitive patient information, research data, or intellectual property. Stolen healthcare records can be valuable on the dark web for identity theft, insurance fraud or other malicious activities.
- Phishing Attacks Phishing emails, which attempt to trick individuals into divulging sensitive information, are a prevalent threat. In healthcare and research settings, attackers may use fake emails to access login credentials, financial information or sensitive research data.
- Supply Chain Attacks Cybercriminals may target the supply chain of medical facilities or research labs. Compromising the security of vendors, suppliers, or partners can provide attackers with a pathway to infiltrate the primary target.
- Advanced Persistent Threats (APTs): APTs involve highly sophisticated, targeted attacks often carried out by well-funded and organised groups. These attacks aim to gain persistent access to networks, often for espionage purposes and can be particularly challenging to detect.
- Disruption of Healthcare Services Cyberattacks may be aimed at disrupting critical healthcare services, such as patient care systems, medical devices or communication infrastructure. This has severe consequences for patient safety and overall healthcare operations.
- Intellectual Property Theft Research labs are often targeted for intellectual property theft, including valuable scientific discoveries, experimental data or proprietary information.
- Internet of Things (IoT) Vulnerabilities Many medical devices and laboratory equipment leverage the Internet of Things If IoT devices are not properly secured and managed. Security vulnerabilities in these devices can be exploited to gain unauthorised access, disrupt operations, or steal sensitive information if IoT devices are not properly secured and managed.
In May 2019, an American Medical Collection Agency (AMCA) data breach impacted the privacy of more than 22 million patients. It costs €361,000 to involve IT professionals and consultants from three different firms to identify the source of the breach, diagnose its cause and implement appropriate solutions. Furthermore,
more than €3.5 million was spent meeting legal requirements and regulatory obligations. AMCA was forced to reduce its workforce from 113 to 25 employees to cope with its sudden financial repercussions.
- How savvy is your lab data management system?
The priorities of Lab Data Management
Where do issues arise when choosing an LDM? What do you need to consider before making the choice? Does your LDM provider cover the following?
Data Quality Assurance
Data Quality Assurance in Lab Data Management refers to the systematic process of ensuring the accuracy, completeness and reliability of laboratory data. It involves validating data at various stages, implementing quality control measures and adhering to standardised protocols. This ensures that research findings and clinical results derived from the data are trustworthy and meet regulatory requirements.
If this is compromised or fails, it can lead to inaccurate research outcomes, compromised patient care decisions, and regulatory non-compliance. Inaccurate data may result in flawed analyses, misinterpretations, and erroneous conclusions, impacting the integrity of scientific research or diagnostic procedures.
What is lost if your lab’s data quality assurance is weak? It’s the trust your customers place in laboratory results that can hinder further collaboration. It poses serious ethical and legal consequences in the fields of healthcare and scientific research.
Have you heard of Samplecheck5000? It may sound particularly attractive to labs, but it is actually malware developed to specifically target labs for its sensitive data!
Data security and confidentiality
The data your lab collects is confidential for your customers and your proprietary research and findings. Protecting your data’s confidentiality and security involves implementing measures to safeguard sensitive information generated or stored in laboratories. This includes protecting patient records, research findings and proprietary data from unauthorised access, disclosure or alteration. Security measures may include encryption (in transit and at rest), access controls and secure storage protocols.
Inadequate measures to protect your data can destroy the integrity of your business and cause massive financial debts to fix and compensate for damages. In today's IoT era, it is easy to gain unauthorised access to sensitive patient information, intellectual property theft or regulatory violations. Patient privacy may be jeopardised, leading to legal consequences and damaging an institution's reputation. Research findings may be at risk of theft or manipulation, impacting the validity and trustworthiness of scientific outcomes.
ISO 27001 The ISO 27001 is an international standard published jointly by the International Organization for Standardization and the International Electrotechnical Commission in 2005. It provides benchmarks for managing information security, and the latest standards were updated in 2022. When an organisation is aligned and certified by ISO 27001, it becomes a tool for risk management, cyber-resilience and operational excellence.
- Is your LDM ISO 27001 certified?
Data storage and retrieval
Data storage and retrieval in Lab Data Management refer to the systematic organisation, storage and efficient retrieval of laboratory data. Today, scalable solutions are vital to cope with the evolving growth of samples or customers needed. Hard drives or even servers have limited capacity for storage—Cloud-based solutions offer flexibility and are engineered to remove single points of failure.
It is imperative that your lab data management involves establishing secure and accessible repositories for diverse types of data, such as experimental results, patient records and research findings. Effective storage systems ensure data integrity, accessibility and long-term preservation.
If compromised, data storage and retrieval issues can lead to data loss, corruption or delays in accessing critical information. Lab researchers can run into issues hindering scientific progress and decision-making. In a healthcare setting, patient care is impacted when there are delays in accessing vital medical records—or even worse, when data is lost.
Old and historical data, particularly within a medical environment, is still relevant when treating a patient—if those files and folders succumb to fire, flooding, accidental destruction or chemical damage, the valuable information is irretrievably lost. Not to mention printing inks that might fade over time or suffer insect attacks, such as silverfish. Proper archiving is essential to prevent further loss.
Data integration
Data comes from all sources, particularly if we include historical and archived data—which can be important to derive valuable patterns and trends for lab and research use.
Data integration in Lab Data Management involves consolidating diverse data sets from different sources within a laboratory or across multiple laboratories. It aims to provide a unified and coherent view of data, facilitating comprehensive analyses and informed decision-making. Effective data integration enhances collaboration, accelerates research and enables a holistic understanding of complex scientific phenomena.
If compromised, incomplete or inaccurate datasets can hinder researchers' ability to derive meaningful insights. Inconsistencies in integrated data may lead to erroneous conclusions and impact the reliability of research outcomes. Additionally, failed data integration can impede interdisciplinary collaborations, slow down research progress and introduce inefficiencies in laboratory workflows.
Data governance
Data governance in Lab Data Management refers to the establishment and enforcement of policies, procedures and standards to ensure the quality, integrity and security of laboratory data throughout its lifecycle. It involves defining roles, responsibilities, and guidelines for data management, access, and usage.
Effective data governance promotes accountability of data streams, data consistency, transparency and compliance with regulatory requirements.
Data governance issues can lead to data inconsistencies, unauthorised access and regulatory non-compliance. Lack of clear policies and oversight may result in data mismanagement, compromising the reliability and trustworthiness of research outcomes.
Data backups
Backups are essential in the lab environment. It involves creating duplicate copies of critical data to safeguard against loss or corruption. This process ensures the availability of data in the event of accidental deletion, hardware failure or other unforeseen issues—and can help protect against ransomware. Regular backups contribute to data resilience and are crucial for maintaining the integrity of research findings and patient records.
Cloud-based Lab Data Management (LDM) solutions offer benefits such as automated backups, scalability, and accessibility. With cloud-based LDM, data is stored off-site, reducing the risk of data loss due to on-site disasters. A good SAAS-delivered LDM platform will ensure your data should be encrypted in transit and at rest.
The consequences of not backing up data or not being rigorous in choices, levels of security and frequency can be severe. Loss of critical data may impede ongoing research, disrupt laboratory workflows and compromise the continuity of patient care. Without reliable backups, recovery from data loss becomes challenging, potentially resulting in permanent loss of valuable information, setbacks in research projects and compromised scientific integrity.
Data traceability
Increasingly, data provenance is highly sought—as it allows the data to be traced to its source, its human owner and inputter and creates accountability and integrity.
The ability to track and document the origin, processing steps and modifications of laboratory data throughout its lifecycle is essential to publishing research, accessing research grants and moving the needle forward to creating a successful solution/product. It involves maintaining a comprehensive audit trail that ensures transparency, accountability and compliance with regulatory standards.
With data traceability, researchers can validate and reproduce results, verify the quality of data, and adhere to stringent documentation requirements. Cloud-based LDM solutions enhance data traceability by providing de-centralised storage, automated version control and access logs. This facilitates collaboration, reduces the risk of errors and ensures that data can be reliably traced back to its source.
Compliance
Maintaining compliance in a lab environment, particularly in environments governed by Good Laboratory Practice (GLP) guidelines, is critical. The GLP is a set of principles and standards established
by various national and international regulatory agencies. One of the key organisations involved in developing and promoting GLP principles at the global level is the Organisation for Economic Co-operation and Development (OECD). In the European Union, GLP regulations are outlined in Directive 2004/10/EC, which was later incorporated into the Good Laboratory Practice Regulation (EU) No 2017/160.
The primary objective of GLP is to facilitate the generation of high-quality and credible data, particularly in industries such as pharmaceuticals, chemicals and biotechnology. Regulatory bodies rely on the data generated in non-clinical studies to make decisions about the safety and efficacy of products before they reach the market. Adherence to GLP helps ensure that the data produced is of the highest quality, minimising the risk of errors, fraud and misinterpretation.
Compliance encompasses data collection, storage, retrieval, and documentation processes to meet regulatory requirements and maintain the quality of research outcomes.
A cloud-based LDM system provides several benefits, such as de-centralised and secure storage, automated audit trails, and version control mechanisms that facilitate traceability, allowing organisations to demonstrate compliance during regulatory inspections within their supply chain. Cloud-based solutions also enable scalability, accommodating the growing volume of data generated in research labs and ensuring efficient and cost-effective management.
The consequences of non-compliance can be severe, especially when failing to meet GLP guidelines. Regulatory penalties, data rejection by authorities and damage to the institution's reputation are potential outcomes.
🡪 What can happen at a legal level if your lab is not digitised? Read our whitepaper.
Version control
Systematic management and tracking of changes made to datasets, software and analysis tools over time ensures version control for a successful Lab Data Management (LDM). With effective version control, researchers can identify, compare and revert to previous versions of data or software, maintaining data integrity and reproducibility.
Failure to have effective version control results in challenging management of multiple versions of datasets. The reliability and efficacy of data sets weaken, leading to confusion, errors and difficulties in reproducing or validating research results.
Data ownership and intellectual property
Data ownership and intellectual property (IP) involve defining and protecting the rights and responsibilities associated with generated data and intellectual contributions. In the context of a research lab, IP encompasses the creations, innovations and discoveries conducted within the laboratory. It often includes:
- Patents
- Copyrights (software code, scientific publications)
- Trademarks (lab names, logos or brand names)
- Trade secrets like methods, techniques or procedures, recipes (e.g., in perfumery, food & drink production)
- Databases/sets
- Innovations (e.g., if a lab or organisation designs their own novel equipment or devices.)
Researchers, institutions and collaborators need clear agreements on data ownership, authorship and intellectual property rights to avoid disputes and ensure ethical use. De-centralised LDM systems can facilitate these aspects by providing transparent access controls, audit trails and collaborative platforms. Permissions can be fine-tuned, ensuring that only authorised individuals can access, modify or share specific datasets, safeguarding sensitive information and adhering to legal and ethical standards.
This is an extremely important facet of your Lab Data Management. If this is compromised, costly disputes may arise over authorship, data usage or intellectual property rights. Inadequate protection may discourage innovation, collaboration and the secure exchange of data, hindering scientific progress.
Training and documentation
At the end of the day, any Lab Data Management system is only as good as the ability of the user to comply. It is no good if the user insists on sticking with notebooks, pens and pencils! Training and education on proper data management practices and maintaining comprehensive records outlining data handling procedures are vital for lab users. While the software may be intuitive, it still needs humans to be properly initiated into its usage.
Training ensures that individuals understand the importance of data integrity, security and compliance with relevant regulations. Clear documentation provides guidelines and standard operating procedures (SOPs) for data collection, storage, analysis and sharing.
Documentation is also crucial: Cloud platforms facilitate real-time updates, ensuring all users can access the latest information. Training modules can be delivered remotely, fostering efficient onboarding and continuous education for lab personnel.
Data reporting
Efficient data reporting is crucial for communication, decision-making and meeting regulatory requirements.
Data reporting is the systematic and accurate presentation of research findings, experimental results and analytical outcomes. This process includes creating comprehensive reports, summarising key insights and ensuring that the data presented is clear, transparent and adheres to relevant standards. Cloud-based solutions enhance data traceability, ensuring that the reported information can be linked back to its source and supporting reproducibility.
Without high-level data reporting, the dissemination of inaccurate or incomplete information results in flawed interpretations hinders collaboration and impacts the credibility of research outcomes. Inadequate reporting practices can also lead to regulatory non-compliance, especially in industries where adherence to standards is essential.
Electronic Lab Notebooks (ELN) integration
Electronic Lab Notebooks (ELN) are digital versions of traditional paper lab notebooks. They enable researchers to record, organise and share experimental data electronically, improving collaboration, data accessibility and traceability in laboratory settings. There are many ELN software in the market but few integrate seamlessly with inventory systems, LIMS and LIS software too—particularly one within its own ecosystems.
Does your Electronic Lab Notebooks (ELN) integrate seamlessly with the other systems in your Lab Data Management (LDM) or is it disparate and glitchy? The benefits of ELN integration include being able to access their electronic notebooks securely from anywhere, facilitating remote collaboration; while real-time synchronisation ensures that the latest data entries are instantly available to the entire team.
Data silos are a very real problem when integration fails, causing data to be scattered across various platforms, hindering collaboration and traceability. Incomplete integration may result in data duplication or loss, affecting the accuracy and completeness of experimental records. Security vulnerabilities in the ELN integration can expose sensitive information to unauthorised access, risking data integrity and confidentiality.
Resource constraints
Every lab has to work within set budgets, personnel and IT support. Integrating considerations regarding implementing and maintaining advanced data management systems into decision-making within a laboratory setting is vital. Laboratories often face challenges in allocating funds and dedicated personnel for robust data management infrastructure.
Select Cloud-based LDM solutions that eliminate the need for extensive in-house IT infrastructure, reducing upfront costs and providing scalable and secure solutions. Cloud-based LDM also allows labs to benefit from regular updates and improvements without the need for costly in-house IT support.
Without adequate financial investment, labs might resort to suboptimal data management practices, potentially leading to data loss, inconsistency and reduced data quality.
Collaboration
By definition, research within the lab environment often sits in collaboration with teams, not only within the physical confines of the lab but with partners and other teams around the world. The science world is a highly social world, with the need to collaborate with other teams in moving the process forward for their innovation, be it chemical, medical or aeronautical.
Is your Lab Data Management system able to work with other platforms seamlessly? Does it recognise other platforms?
Collaboration in Lab Data Management (LDM) involves the seamless sharing, integration and coordination of research data among team members—in- and out-of-house—and across different projects. Effective collaboration is essential for enhancing research outcomes, accelerating discoveries and fostering interdisciplinary cooperation within laboratories.
Cloud-based LDM systems allow researchers to work on the same datasets in real-time, irrespective of geographical location. These platforms also support standardised collaboration tools, ensuring uniformity in data management practices and enhancing interoperability.
Inconsistencies lead to errors, misinterpretations and delays in research projects. Inventory can be mixed up, ELN entries can be confusing, leading to data silos, hindering efficient information exchange and collaborative decision-making. Progress of research is impeded, which undermines the quality of scientific outcomes.
A checklist of a proper Lab Data Management system
Is your Lab Data Management system up to scratch? Will it pass muster today? Does it include the following?
- ISO27001 level security for my data so that confidentiality is maintained.
- Data is stored following modern best practices so that theft, destruction, misplaced hard drives, and computers can easily be avoided.
- My data storage flexes and scales with the needs of my team and research.
- I can easily and reliably access and retrieve my data, no matter how old it is.
- My LDM facilitates easy data integration with multiple platforms and diverse data sets.
- My data is governed by the proper establishment and enforcement of policies, procedures and standards to abide by regulatory requirements.
- My LDM ensures proper backups to secure ISO 27001-certified solutions.
- I have the ability to track and document the origin, processing steps and modifications of my laboratory data throughout its lifecycle.
- My LDM provides a high level of GLP-compliant checks to ensure my data is credible so that I can rest easy, knowing that my innovation/product is both safe and efficacious.
- My LDM systematically manages and tracks changes made to datasets, allowing me to identify, compare and revert to previous versions of data if I need to.
- My LDM provides transparent access controls, audit trails and collaborative platforms, negating issues of data ownership and compromised intellectual property.
- My LDM provider ensures that my team and I are adequately trained to use the software and have proper documentation to refer to for help.
- My LDM generates reporting for systematic and accurate presentation of research findings, experimental results and analytical outcomes.
- My LDM seamlessly integrates my ELN with our inventory systems, LIMS and LIS software.
- My LDM comfortably fits within our lab’s allotted budgets, personnel and IT support.
- My LDM allows me to collaborate with my team effortlessly—and even others within the ecosystem of my study.
How did you rate?
Data is increasingly valuable—which also means it is increasingly vulnerable. Labs spend tens of thousands to ensure the integrity, security, integration and strength of their lab data management. And yet, many don’t work seamlessly and are stapled together piecemeal, often using a workaround.
🡪 What other lab data management considerations are there? Read our other whitepapers.
A simple solution
eLabNext’s Lab Data Management is simple. We don’t like complicated. Our ecosystem of software comes in three separate modules, but all designed to work as one. What’s more, our entire ecosystem is certified ISO27001, not just the separate modules.
eLabJournal is our all-in-one electronic lab notebook (ELN). It has been designed to work seamlessly with our eLabInventory and eLabProtocol modules, providing the complete software solution for labs all over the world. We offer secure hosting plans as well as our expertise across Cloud-based hosting solutions, such as AWS, which is often considered the gold standard.
🡪Have a read about our take on what to consider when choosing the right ELN for your lab.
To securely manage your data, a decentralised, Cloud-based solution is ideal. It offers the following four main benefits:
Scalability
Because Cloud-based data solutions do not rely on you having a physical disk under your desk or in a cabinet in your building, it can expand and contract with your user pool and needs. It is also able to maintain acceptable performance as demand increases. The Cloud has "infinite" scalability as long as the applications and systems are architected optimally.
eLabNext is a Software as a Service (SaaS) solution—this means scalability is built into its strength and flexibility.
🡪 Read how easy it is to digitise your sample collection, organisation, labelling and more.
Security
Under the hood, Cloud-based data storage is designed to be decentralised, with encrypted parts of the data separated across physical disks and physical cabinets in a data centre, ideally across geographical locations. This allows the data to remain whole even if one physical cabinet fails—the Cloud can intelligently fill in the gaps.
eLabNext allows you to control and govern your applications and data through user authentication and authorisation. We have systems in place to prevent and detect security events; our Cloud-based solution is more secure because you have a greater ability to manage security settings, which include greater logging and monitoring and the ability to take automatic actions.
Reliability
Labs need their data and databases to be reliably delivered at any moment. Unreliable systems can mean the loss of important research results and data. Cloud-based lab data management reduces anxiety because it is a system that can serve traffic with minimal/no downtime. Additionally, the Cloud can be more secure because everything is engineered for high availability—after all, it has no single point of failure.
Equally important is eLabNext’s software ecosystem, which allows reliable integration between eLabJournal, eLabInventory, and eLabProtocol. This means no integration issues can disrupt the reliable storage, saving and cataloguing of lab data.
Resiliency
Decentralised storage systems better withstand failures and disruption by design. It can continue to serve traffic while maintaining integrity of security because redundancies are built in. Recovery can also be automated to self-heal.
eLabNext’s ISO 27001 certification includes our expertise in creating environments for your data that protect your valuable findings, patient/sample info, publications and ability to move your product to market.
ISO 27001 The ISO 27001 is an international standard published jointly by the International Organisation for Standardization and the International Electrotechnical Commission in 2005. It provides benchmarks for managing information security; the latest standards were updated in 2022. When an organisation is aligned and certified by ISO 27001, it becomes a tool for risk management, cyber-resilience and operational excellence.
Find out more
Do you want to know more about a lab data management system that ticks all the boxes in our checklist? Our team members are experts in tech and software and have backgrounds in science and lab environments. Speak to an insider about selecting the best lab data management system that is designed from the core for your needs.
We also welcome you to sign up for a trial.
Who is eLabNext?
Please peruse our easy-to-navigate website to find out more about eLabNext. It is our mission to elevate life science research with tools that are elegantly designed from the code-up. Our eLabNext platform is powerful enough to fit the needs of 10 or 5,000 lab research teams—but remains pared down in bulk and unnecessary elements that make software bloat and become clunky over time.
We’re a Dutch-born-and-based software endeavour founded by research scientists in 2010. Erwin Seinen and Wouter de Jong developed eLabNext because they were frustrated with their paper notebooks and how software systems out there were not seamless and did not integrate with each other, including equipment, security, inventory, and sample tools.
Today, we have offices in the Netherlands, UK, USA and Australia, servicing labs all over the world. We help future-proof their digital platforms so that they can keep doing what they do to help better the human experience and our planet.
.png){kind=icon}
