Laboratory information management system

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Laboratories around the world depend on a LIMS to manage data, assign rights, manage inventory, and more.

Sometimes referred to as a laboratory information system (LIS) or laboratory management system (LMS), a laboratory information management system (LIMS) is a software-based laboratory and information management system that offers a set of key features that support a modern laboratory's operations. Those key features include—but are not limited to—workflow and data tracking support, flexible architecture, and smart data exchange interfaces, which fully "support its use in regulated environments."[1] The features and uses of a LIMS have evolved over the years from simple sample tracking to an integrated application that handles laboratory management, quality management, and enterprise resource planning processes, from testing and quality control to reporting and invoicing.

Due to the rapid pace at which laboratories and their data management needs shift, the definition of LIMS has become somewhat controversial. As the needs of the modern laboratory vary widely from lab to lab, what is needed from a LIMS also shifts. The end result: the definition of a LIMS will shift based on who you ask and what their vision of the modern lab is.[1] Dr. Alan McLelland of the Institute of Biochemistry, Royal Infirmary, Glasgow highlighted this problem in the late 1990s by explaining how a LIMS is perceived by an analyst, a laboratory manager, an information systems manager, and an accountant, "all of them correct, but each of them limited by the users' own perceptions."[2]

Historically the term "LIMS" has tended to be used to reference laboratory informatics systems targeted for environmental, research, or industrial analysis such as water quality, pharmaceutical, or petrochemical work. "LIS" has tended to be used to reference informatics systems in the forensics and clinical markets, which often requires special case and patient management tools. In modern times, LIMS functionality has spread even farther beyond its original purpose of sample management. Assay data management, data mining, statistical analysis, electronic laboratory notebook (ELN) integration, and industry-specific functionality that supports regulatory requirements in that industry (e.g., hazard analysis and critical control points [HACCP] workflow tools in food and beverage manufacturing) are all types of functionality added to LIMS, enabling the realization of greater laboratory and enterprise management through one software solution. Additionally, the distinction between a LIMS and a LIS has blurred, as many LIMS now also fully support comprehensive case-centric clinical specimen and patient data management.


Up until the late 1970s, management of laboratory samples and their associated analysis and reporting was a time-consuming manual processes often riddled with transcription errors. This gave some organizations impetus to streamline the collection of data and how it was reported. Custom in-house solutions were developed by a few individual laboratories, while some enterprising entities at the same time sought to develop a more commercial reporting solution in the form of special instrument-based systems.[3]

In 1982, the first generation of LIMS was introduced in the form of a single centralized minicomputer, which offered laboratories the first opportunity to utilize automated reporting tools. As the interest in these early LIMS grew, industry leaders like Gerst Gibbon of the Federal Energy Technology Centre in Pittsburgh began planting the seeds through LIMS-related conferences. By 1988, the second-generation commercial offerings were tapping into relational databases to expand LIMS into more application-specific territory, and international LIMS conferences were in full swing. As personal computers became more powerful and prominent, a third generation of LIMS emerged in the early 1990s. These new LIMS took advantage of the developing client/server architecture, allowing laboratories to implement better data processing and exchanges.[3]

By 1995, the client/server tools had developed to the point of allowing processing of data anywhere on the network. Web-enabled LIMS were introduced the following year, enabling researchers to extend operations outside the confines of the laboratory. From 1996 to 2002, additional functionality was included in LIMS, from wireless networking capabilities and georeferencing of samples, to the adoption of XML standards and the development of internet-based purchasing.[3]

By the early 2010s, some LIMS had added additional characteristics that continued to shape how a LIMS was defined. Examples include the addition of clinical functionality and electronic laboratory notebook (ELN) functionality, as well a rise in the cloud-based software as a service (SaaS) distribution model.[4][5] By the late 2010s, cloud-based LIMS were more numerous in quantity and adoption but not the de facto standard, as the costs and daunting nature associated with vendors transitioning legacy products to the cloud and with companies trying to integrate a cloud-based LIMS into a complicated IT and regulatory environment had partially stymied growth.[6][7] Today, despite these challenges, cloud-based approaches to the management of laboratory data continue to see adoption or intent to adopt[8][9], including in the more heavily regulated GxP (good practice) laboratories, which have their own unique challenges with data integrity and security requirements.[10]

Purpose and technology

A LIMS is a software solution designed to allow end users to better manage a wide variety of operational and quality management aspects of academic, government, and industrial laboratories serving a broad range of industries and stakeholders. The software can be monolithic or microservices-based, with each architecture type having its own pros and cons, especially dependent upon the number of concurrent users, desired functional scale, and deployment method (e.g., on-premises vs. in the cloud).[11] The reasons for adopting a LIMS and other laboratory informatics solutions varies by laboratory, but common purposes for adopting such systems include wanting to automate and better manage laboratory processes; more accurately capture laboratory and experiment data; more efficiently calculate, prepare, and disseminate analytical results; better aggregate and analyze laboratory data and information; increase throughput and productivity; and enhance regulatory compliance.[8] Through regulatory, market, customer, and technological pressures, many laboratories have decided that increasingly digitizing the laboratory makes sense in its efforts towards compliance, competitiveness, relevancy, and efficiency.[8][12] A LIMS deployment primarily focuses on sample management, data acquisition, and reporting activities; however, its scope can expand much further depending on the scientific discipline or industry served. The following subsections examine these concepts further.

Laboratory information management operations

The LIMS is an evolving concept, with new features and functionality being added often. As laboratory demands change and technological progress continues, the functions of a LIMS will likely also change. Despite these changes, a LIMS tends to have a base set of functionality that defines it. That functionality can roughly be divided into five laboratory processing phases, with numerous software functions falling under each[13]:

  • the reception and log in of a sample and its associated customer data;
  • the assignment, scheduling, and tracking of the sample and the associated analytical workload;
  • the processing and quality control associated with the sample and the utilized equipment and inventory;
  • the storage of data associated with the sample analysis; and
  • the inspection, approval, and compilation of the sample data for reporting and/or further analysis.

There are several pieces of core functionality associated with these laboratory processing phases that tend to appear in most LIMS.

Sample management

A lab worker matches blood samples to documents. With a LIMS, this sort of sample management is made more efficient.

The core function of LIMS has traditionally been and largely continues to be the management of samples.[3][14] This typically is initiated when a sample is received in the laboratory, at which point the sample will be registered in the LIMS. This registration process may involve accessioning the sample and producing barcodes to affix to the sample container. Various other parameters, such as clinical or phenotypic information corresponding with the sample, are also often recorded.[14] The LIMS can then track a sample's progress throughout the lab and its workflow. In many cases, location tracking can be quite granular, down to a particular freezer location, even down to the level of shelf, rack, box, row, and column. Beyond location, other aspects of and actions upon the sample can be tracked and time-stamped, including freeze and thaw cycles that a sample undergoes, aliquoting of the sample, and more.

Modern LIMS have implemented extensive configurability, as each laboratory's needs for tracking additional data points can vary widely. LIMS vendors cannot typically make assumptions about what these data tracking needs are, and therefore vendors often create LIMS that are adaptable to individual environments. This typically involves the inclusion of workflow management tools in the LIMS. Users may also have regulatory concerns to comply with such as CLIA, HIPAA, 21 CFR Part 11, good laboratory practice (GLP), and FDA specifications, affecting certain aspects of sample management in a LIMS solution.[14][15][16][17] In the end, an analytical lab's deliverables are the results of its analyses of samples and specimens; it's imperative they are timely, accurate, and of good provenance. At the core of any modern sample management activities is the concept of "data integrity", and a LIMS' ability to track sample-related data and metadata at every step of the laboratory workflow from the point of origin (thanks to instrument integration functionality[14]; see next subsection), all while using audit trail and electronic signature functionality, positively lends to a lab's overall approach to data integrity and producing accurate, defensible results.[17][18]

Instrument and application integration

Modern LIMS offer integration with laboratory instruments, a desirable feature for data integrity purposes.[14] This used to be a costly and time-consuming process[9][19][20][21], setting up a control file on an instrument-by-instrument basis, which would "feed" into the instrument and direct its operation on some physical item such as a sample tube or sample plate. The LIMS would then import instrument results files back into the system and extract data for quality control assessment of the operation on the sample. The rise of modular, pre-configured middleware solutions that can from the start interface a series of device and device types to a LIMS more efficiently has in small part lessened this burden for LIMS users, however.[9][20] In all cases, the LIMS may also limit access to that instrument data fed into the system based on chain of custody assignments or other security features if need be.

In addition, a LIMS typically allows for the import and management of raw assay data results.[22] Modern targeted assays such as qPCR and deep sequencing can produce tens of thousands of data points per sample, all while the qPCR instrument is difficult itself to directly interface with the LIMS.[14] Furthermore, in the case of drug and diagnostic development, a dozen or more assays may be run for any given sample. As such, the LIMS ideally will still provide a means to import raw data files extracted from instruments like qPCR even if the instrument itself can't be directly interfaced. However, in order to track and make usable this imported data, a LIMS solution needs to be adaptable to many different assay formats at both the data layer and import creation layer, while maintaining a high level of overall performance.

Increasingly, a LIMS also provides the ability to integrate with other third-party applications such as ELNs, enterprise resource planning (ERP) systems, or regulatory compliance systems (such as seed-to-sale reporting systems for cannabis testing).[14][23][24] This integration is typically achieved through the use of an application programming interface (API)[23][24][25], code which serves as an interface between different software programs and databases, and facilitates their interactions.

Electronic data exchange

The exponentially growing volume of data created in laboratories, coupled with increased business demands and focuses on profitability, have pushed LIMS vendors to increase attention to how their LIMS handles the electronic exchange of data with other systems and instruments. The effectiveness of this data exchange is highly important to regulated industries that regularly report to an authority, as found with cannabis testing and some U.S. states' reporting requirements[24], as well as clinical labs reporting to state- and federal-based public health agencies.[26] (Many labs' electronic systems' ability to exchange data with public health agencies was put to the test during the height of the COVID-19 pandemic.[27] In some cases, academic clinical research labs with the means to test patients using their qPCR devices simply couldn't exchange data with health systems' electronic health records [EHRs], which ultimately excluded those labs from assisting with COVID-19 testing.[28])

In particular, attention must be paid to how an instrument's input and output data is managed, how remote sample collection data is imported and exported, and how mobile and other third-party applications integrate with the LIMS. The successful transfer of data files in a wide variety of formats (including interoperable nonproprietary file types for better meeting the FAIR principles of making data and information more findable, accessible, interoperable, and reusable[25]), while maintaining the associated metadata and keeping it secure, is paramount. Historically speaking, the transition "from proprietary databases to standardized database management systems such as Oracle ... and SQL" has had significant impact on how data is managed and exchanged in laboratories[29], culminating today in cloud-based relational and NOSQL databases that can be set up, operated, and scaled with relative ease.[30][31]

Additional functions

In addition to the key functions of sample management, instrument and application integration, and electronic data exchange, there are numerous additional laboratory-based operations that can be managed in a LIMS. This includes but is not limited to[32][33][34][35]:

Test, sample, and result management

  • End-to-end sample and inventory management and tracking
  • Complete capture of a registered sample's data and metadata
  • Unique sample identifiers
  • Sample batching
  • Free-form reception-based sample data
  • Barcode and RFID support
  • Pre-defined and configurable common and industry-specific sample types, tests, methods, and protocols
  • Pre-defined and configurable industry-specific workflows
  • Robust sampling and test method development
  • Configurable screens and data fields
  • Specification management
  • Test, sampling, instrument, etc. scheduling and assignment
  • Test requesting
  • Data import and export
  • Robust query tools
  • Analytical tools, including data visualization, statistical analysis, and data mining tools
  • Project management
  • Investigation management
  • Facility and sampling site management
  • Storage management and monitoring

Quality, security, and compliance

  • Quality assurance / quality control mechanisms
  • Multi-level review of test results
  • Validation of sampling and test methods
  • Audit trails and chain of custody support
  • Support for mapping professional requirements to existing system tasks, sample types, and methods
  • Instrument lock-out
  • Consistent, retrievable calibration and maintenance records
  • Calibration activity linkages
  • Calibration and maintenance audit trail
  • Incident, nonconformance, and deviation notification, tracking, and management
  • Statistical trending and control charts
  • Internal and external audit management
  • Secure backup and retrieval
  • Facility monitoring
  • Environmental monitoring
  • Data retention and encryption
  • Robust system security
  • LIMS validation
  • Secure granular access
  • Logical and physical access control
  • Electronic signature support
  • Status updates and alerts

Operations management and reporting

  • Document and image management, with versioning and release controls
  • Controlled document access
  • Provision of the most current document version
  • User manuals and training documentation
  • Support for unique document identifiers
  • Support for training and certification records
  • Complaint and problem management
  • Unique identification of instruments
  • Support for scheduled, frequency-based calibration and maintenance
  • Support for data importing and exporting of a variety of formats, including interoperable nonproprietary file types
  • Support for data and metadata archiving
  • Support for rapid and accurate retrieval of archived data and metadata
  • Support for certificates of analysis or similar verification documents
  • Support for changed, amended, or re-issued reports
  • Configurable dashboards for monitoring, by product, process, facility, etc.
  • Industry-compliant reporting and labeling
  • Email integration
  • Instrument interfacing and data management
  • Third-party software and database interfacing
  • Supplier/vendor/customer management
  • Integrated (or online) system help

LIMS architecture and delivery methods

A LIMS has historically over many decades depended on a variety of architectures and distribution models for its implementation and use. As technology has changed, how a LIMS is installed, managed, and used has also changed with it. The following represents architectures which have been utilized at one point or another.


A thick-client LIMS is a more traditional client/server architecture, with some of the system residing on the computer or workstation of the user (the client) and the rest on the server. The LIMS software is installed on the client computer, which does all of the data processing. Later it passes information to the server, which has the primary purpose of data storage. Most changes, upgrades, and other modifications will happen on the client side.

This was one of the first architectures implemented into a LIMS, having the advantage of providing higher processing speeds (because processing is done on the client and not the server) and slightly more security (as access to the server data is limited only to those with client software). Additionally, thick-client systems have also provided more interactivity and customization, though often at a greater learning curve. The disadvantages of client-side LIMS include the need for more robust client computers and more time-consuming upgrades, as well as a lack of base functionality through a web browser. The thick-client LIMS can become web-enabled through an add-on component.[36][37]


A web-enabled LIMS architecture is essentially a thick-client architecture with an added web browser component. In this setup, the client-side software has additional functionality that allows users to interface with the software through their device's browser. This functionality is typically limited only to certain functions of the web client. The primary advantage of a web-enabled LIMS is the end-user can access data both on the client side and the server side of the configuration. As in a thick-client architecture, updates in the software must be propagated to every client machine. However, the added disadvantages of requiring always-on access to the host server and the need for cross-platform functionality mean that additional overhead costs may arise.[36][37]


The concept of cloud computing is one of the most recent architecture and delivery models to affect LIMS.

A thin-client LIMS is a more modern architecture which offers full application functionality accessed through a device's web browser. The actual LIMS software resides on a server (host) which feeds and processes information without saving it to the user's hard disk. Any necessary changes, upgrades, and other modifications are handled by the entity hosting the server-side LIMS software, meaning all end-users see all changes made. To this end, a true thin-client LIMS will leave no "footprint" on the client's computer, and only the integrity of the web browser need be maintained by the user. The advantages of this system include significantly lower cost of ownership and fewer network and client-side maintenance expenses. However, this architecture has the disadvantage of requiring real-time server access, a need for increased network throughput, and slightly less functionality. A sort of hybrid architecture that incorporates the features of thin-client browser usage with a thick client installation exists in the form of a web-based LIMS.[36][37]

Additionally, maintenance support and warranty (MSW) agreements are usually offered with thin-client installations. Pricing levels are typically based on a percentage of the license fee, with a standard level of service for 10 concurrent users being approximately 10 hours of support and additional customer service at a set per-hour rate. Though some may choose to opt out of an MSW after the first year, it's often more economical to continue the plan in order to receive updates to the LIMS, giving it a longer life span in the laboratory.

Cloud and SaaS

In the early 2010s, LIMS vendors began to rent hosted, thin-client solutions as "software as a service" (SaaS). These cloud-based solutions tended to be less configurable than on-premise solutions and were therefore considered for less demanding implementations such as laboratories with few users and limited sample processing volumes. However, cloud-based software has seen greater adoption as the technology has improved, and configurable LIMS for laboratory operations big and small have become a more realistic option.[6][7][8][9] For example, a June 2022 report published by Astrix Technology found that of life science organizations surveyed, 78 percent of them indicated they have adopted and used or plan to adopt and use cloud-based applications; of all respondents, 43 percent said they are taking a cloud-first or cloud-only approach to its laboratory applications.[8]


Arguably one of the most confusing architectures, web-based LIMS architecture is a hybrid of the thick- and thin-client architectures. While much of the client-side work is done through a web browser, the LIMS also requires the additional support of Microsoft's .NET Framework technology installed on the client device. The end result is a process that is apparent to the end-user through the Microsoft-compatible web browser, but perhaps not so apparent as it runs thick-client-like processing in the background. In this case, web-based architecture has the advantage of providing more functionality through a more friendly web interface. The disadvantages of this setup are more sunk costs in system administration and support for Internet Explorer and .NET technologies, and reduced functionality on mobile platforms.[36][37]

The distinction between a LIMS and a LIS

Historically, the LIMS and LIS have exhibited a few key differences, making them noticeably separate entities[38]:

1. A LIMS traditionally has been designed to process and report data related to batches of samples from biology labs, water treatment facilities, drug trials, and other entities that handle complex batches of data. A LIS has been designed primarily for processing and reporting data related to individual patients in a clinical setting.[39][40]

2. A LIMS needs to satisfy good manufacturing practice (GMP) and meet the reporting and audit needs of the U.S. Food and Drug Administration and research scientists in many different industries. A LIS, however, must satisfy the reporting and auditing needs of hospital accreditation agencies, HIPAA, and other clinical medical practitioners.[39]

3. A LIMS is most competitive in group-centric settings (dealing with "batches" and "samples") that often deal with mostly anonymous research-specific laboratory data, whereas a LIS is usually most competitive in patient-centric settings (dealing with "subjects" and "specimens") and clinical labs.[40][41][42]

However, these distinctions began to fade somewhat in the early 2010s as some LIMS vendors began to adopt the case-centric information management normally reserved for a LIS, blurring the lines between the two components further.[42] Thermo Scientific's Clinical LIMS was an example of this merger of LIMS with LIS, with Dave Champagne, informatics vice president and general manager, stating: "Routine molecular diagnostics requires a convergence of the up-to-now separate systems that have managed work in the lab (the LIMS) and the clinic (the LIS). The industry is asking for, and the science is requiring, a single lab-centric solution that delivers patient-centric results."[43] Abbott Informatics Corporation's STARLIMS product was another example of this LIMS/LIS merger.[38] With the distinction between the two entities becoming less clear, discussions within the laboratory informatics community began to includes the question of whether or not the two entities should be considered the same.[44][45] As of 2024, vendors continue to recognize the historical differences between the two products while also continuing to acknowledge that some developed LIMS are taking on more of the clinical aspects usually reserved for a LIS.[46][47][48]

Regulations, standards, and best practices affecting LIMS development and use

A LIMS' development and use is affected by regulations, standards, and best practices such as:

  • 21 CFR Part 11 Electronic records; Electronic signature: Regulated clinical-focused industries, such as medical devices or pharmaceuticals, are expected to comply with U.S. Food and Drug Administration (FDA) regulations like 21 CFR Part 11, which address matters of software validation, data integrity, data retention, audit trails, signed records, and secured access to data. These matters pertain to software systems like LIMS and ELN, as well as other systems employed in modern laboratories.[49][50][51]
  • ASTM E1578 Standard Guide for Laboratory Informatics: This standard is geared towards a variety of stakeholders having some sort of professional interest in laboratory informatics. It intends to educate on and recommend approaches to laboratory software development, acquisition, implementation, and maintenance, including as how they relate to LIMS.[52]
  • Good laboratory practice (GLP): GLP is a quality- and data-driven approach to ensuring the safety, consistency, high quality, and reliability of developed and produced goods. These best practices address a variety of aspects of non-clinical research and manufacturing laboratory workflows, from personnel and equipment to tests and reporting. Some LIMS are developed to help labs better enforce a GLP approach to its operations.[53]
  • ISO 15189 Medical laboratories — Requirements for quality and competence: This standard specifies quality management approaches to clinical laboratory settings. It pulls inspiration from ISO/IEC 17025 while acknowledging the unique characteristics and needs of the clinical lab. The standard's requirements on laboratory need for addressing cybersecurity, system validation, and more apply directly to LIMS development and implementation.[54]
  • ISO/IEC 17025 General requirements for the competence of testing and calibration laboratories: This standard has evolved significantly over the years, today expressing how analytical and calibration labs should best handle quality management through its operations.[55] Like ISO 15189, this standard addresses many activities of these labs and how they should best performed to conform to a high level of quality. A LIMS has many ways to address the needs of a lab attempting to comply with the standard.[35]

See also

Further reading


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  2. McLelland, A. (1998). "What is a LIMS - a laboratory toy, or a critical IT component?" (PDF). Royal Society of Chemistry. p. 1. Archived from the original on 04 October 2013. Retrieved 12 March 2024. 
  3. 3.0 3.1 3.2 3.3 Gibbon, G.A. (1996). "A brief history of LIMS". Laboratory Automation and Information Management 32 (1): 1–5. doi:10.1016/1381-141X(95)00024-K. 
  4. Nagisetty, P. (2 November 2012). "Is any one aware of a SaaS LIMS success story?". LinkedIn. Retrieved 12 March 2024. 
  5. Mullin, R. (24 May 2010). "LIMS in the Cloud". Chemical & Engineering News 88 (21): 12–16. Retrieved 12 March 2024. 
  6. 6.0 6.1 Knippenberg, R. (9 May 2017). "Moving your Lab IT Infrastructure to the Cloud? Consider Nearshoring". Astrix Blog. Astrix Technology Group. Archived from the original on 31 January 2023. Retrieved 12 March 2024. 
  7. 7.0 7.1 Joyce, J. (1 May 2017). "What You and Your IT Team Should Know About the Cloud". Lab Manager. LabX Media Group. Retrieved 12 March 2024. 
  8. 8.0 8.1 8.2 8.3 8.4 "2022 Laboratory Informatics: Progress Snapshot on Enabling the Digital Lab of the Future" (PDF). Astrix Technology, LLC. June 2022. pp. 18–23. Retrieved 12 March 2024. 
  9. 9.0 9.1 9.2 9.3 Lanewala, M.; Yauger, T.; Jones, L.L. (4 March 2024). "2024 LIMS Trends". Clarkston Consulting Insights. Clarkston Consulting. Retrieved 12 March 2024. 
  10. Davis, Scott; Usansky, Joel; Mitra-Kaushik, Shibani; Kellie, John; Honrine, Kimberly; Woolf, Eric; Adams, Jeb; Kelly, Ryan et al. (1 September 2021). "Cloud solutions for GxP laboratories: considerations for data storage" (in en). Bioanalysis 13 (17): 1313–1321. doi:10.4155/bio-2021-0137. ISSN 1757-6180. 
  11. Blinowski, Grzegorz; Ojdowska, Anna; Przybylek, Adam (2022). "Monolithic vs. Microservice Architecture: A Performance and Scalability Evaluation". IEEE Access 10: 20357–20374. doi:10.1109/ACCESS.2022.3152803. ISSN 2169-3536. 
  12. Liscouski, J. (July 2023). "1. Introduction to LIMS and its acquisition and deployment". In Douglas, S.E.. Justifying LIMS Acquisition and Deployment within Your Organization. LIMSwiki. Retrieved 13 March 2024. 
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  15. Zipp, K. (21 February 2007). "Regulatory compliance drives LIMS". Design World. WTWH Media, LLC. Retrieved 12 March 2024. 
  16. Boyar, Kyle; Pham, Andrew; Swantek, Shannon; Ward, Gary; Herman, Gary (2021), Opie, Shaun R., ed., "Laboratory Information Management Systems (LIMS)" (in en), Cannabis Laboratory Fundamentals (Cham: Springer International Publishing): 131–151, doi:10.1007/978-3-030-62716-4_7, ISBN 978-3-030-62715-7, Retrieved 2024-03-12 
  17. 17.0 17.1 Famili, Parsa; Cleary, Susan (9 March 2022), Huynh‐Ba, Kim, ed., "Laboratory Information Management System (LIMS) and Electronic Data" (in en), Analytical Testing for the Pharmaceutical GMP Laboratory (Wiley): 345–373, doi:10.1002/9781119680475.ch10, ISBN 978-1-119-12091-9, Retrieved 2024-03-12 
  18. McDowall, R.D. (2016). "How Can LIMS Help Ensure Data Integrity?". LCGC Europe 29 (6): 310–16. Retrieved 12 March 2024. 
  19. John3504 (7 December 2011). "HL7 Interface cost and maintenance". Spiceworks. Retrieved 12 March 2024. 
  20. 20.0 20.1 MLO Staff (1 August 2012). "Interfacing the LIS". Medical Laboratory Observer. Retrieved 12 March 2024. 
  21. Duckworth, J.. "IT in the Lab: The Instrument Interface... Revisited". Laboratory Network. Retrieved 28 February 2024. 
  22. Khan, Masood N.; Findlay, John W. (2009). "11.6 Integration: Tying It All Together". Ligand-Binding Assays: Development, Validation, and Implementation in the Drug Development Arena. John Wiley & Sons. pp. 324. ISBN 0470041382. Retrieved 21 March 2020. 
  23. 23.0 23.1 "10 Ways LIMS Can Automate Your Lab". CSols, Inc. 9 February 2017. Retrieved 12 March 2024. 
  24. 24.0 24.1 24.2 Audino, S. (7 February 2018). "Managing Cannabis Testing Lab Workflows using LIMS". Cannabis Industry Journal. Retrieved 12 March 2024. 
  25. 25.0 25.1 Berezin, Casey-Tyler; Aguilera, Luis U.; Billerbeck, Sonja; Bourne, Philip E.; Densmore, Douglas; Freemont, Paul; Gorochowski, Thomas E.; Hernandez, Sarah I. et al. (7 December 2023). Markel, Scott. ed. "Ten simple rules for managing laboratory information" (in en). PLOS Computational Biology 19 (12): e1011652. doi:10.1371/journal.pcbi.1011652. ISSN 1553-7358. PMC PMC10703290. PMID 38060459. 
  26. Rajamani, Sripriya; Kayser, Ann; Emerson, Emily; Solarz, Sarah (21 September 2018). "Evaluation of Data Exchange Process for Interoperability and Impact on Electronic Laboratory Reporting Quality to a State Public Health Agency". Online Journal of Public Health Informatics 10 (2). doi:10.5210/ojphi.v10i2.9317. ISSN 1947-2579. PMC PMC6194099. PMID 30349622. 
  27. Douglas, S.E. (September 2021). "4. Workflow and information management for COVID-19 (and other respiratory diseases)". COVID-19 Testing, Reporting, and Information Management in the Laboratory (Fall 2021 ed.). LIMSwiki.,_Reporting,_and_Information_Management_in_the_Laboratory/Workflow_and_information_management_for_COVID-19_(and_other_respiratory_diseases). Retrieved 12 March 2024. 
  28. Maxmen, A. (2020). "Thousands of coronavirus tests are going unused in US labs". Nature 580 (7803): 312–13. doi:10.1038/d41586-020-01068-3. PMID 32273619. 
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  32. "ASTM E1578-18 Standard Guide for Laboratory Informatics". ASTM International. 23 August 2019. Retrieved 12 March 2024. 
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  34. Douglas, S.E. (December 2022). "LII:LIMSpec 2022 R2". LIMSwiki. Retrieved 12 March 2024. 
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