ASTM E1578-18

Standard Guide for Laboratory Informatics

SIGNIFICANCE AND USE
4.1 Relevance—This guide is intended to educate the intended audience on many aspects of laboratory informatics. Specifically, the guide may:  
4.1.1 Help educate new users of laboratory informatics;  
4.1.2 Help educate general audiences in laboratories and other organizations that use laboratory informatics;  
4.1.3 Help educate instrument manufactures and producers of other commonly interfaced systems;  
4.1.4 Provide standard terminology that can be used by laboratory informatics vendors and end users;  
4.1.5 Establish a minimum set of requirements for primary laboratory informatics functions;  
4.1.6 Provide guidance on the tasks performed and documentation created in the specification, evaluation, cost justification, implementation, project management, training, and documentation of laboratory informatics; and  
4.1.7 Provide high-level guidance for the integration of laboratory informatics and other software tools.  
4.2 How to be Used—This guide is intended to be used by all stakeholders involved in any aspect of laboratory informatics implementation, use, or maintenance.  
4.2.1 It is intended to be used throughout the laboratory informatics life cycle by individuals or groups responsible for laboratory informatics implementation and use, including specification, build/configuration, validation, use, upgrades, and retirement/decommissioning.  
4.2.2 This guide also provides an example of a laboratory informatics functional requirements checklist that can be used to guide the purchase, upgrade, or development of a laboratory informatics system.
SCOPE
1.1 This guide helps describe the laboratory informatics landscape and covers issues commonly encountered at all stages in the life cycle of laboratory informatics from inception to retirement. It explains the evolution of laboratory informatics tools used in today’s laboratories such as laboratory information management systems (LIMS), laboratory execution systems (LES), laboratory information systems (LIS), electronic laboratory notebooks (ELN), scientific data management systems (SDMS), and chromatography data systems (CDS). It also covers the relationship (interactions) between these tools and the external systems in a given organization. The guide discusses supporting laboratory informatics tools and a wide variety of the issues commonly encountered at different stages in the life cycle. The subsections that follow describe the scope of this document in specific areas.  
1.2 High-Level Purpose—The purpose of this guide includes: (1) educating new users on laboratory informatics tools; (2) providing a standard terminology that can be used by different vendors and end users; (3) establishing minimum requirements for laboratory informatics; (4) providing guidance for the specification, evaluation, cost justification, implementation, project management, training, and documentation of the systems; and (5) providing a functional requirements checklist for laboratory informatics systems that can be adopted within the laboratory and integrated with existing systems.  
1.3 Laboratory Informatics Definition—Laboratory informatics is the specialized application of information technology aimed at optimizing laboratory operations. It is a collection of informatics tools utilized within laboratory environments to collect, store, process, analyze, report, and archive data and information from the laboratory and its supporting processes. Laboratory informatics includes the effective use of critical data management systems, the electronic delivery of results to customers, and the use and integration of supporting systems (for example, training and policy management). Examples of primary laboratory informatics tools include laboratory information management systems (LIMS), laboratory execution systems (LES), laboratory information systems (LIS), electronic laboratory notebooks (ELN), scientific data management systems (SDMS), and chromat...

General Information

• Status: Published
• Publication Date: 31-Jul-2018
• ICS: 35.240.80 - IT applications in health care technology
• Technical Committee: E13 - Molecular Spectroscopy and Separation Science
• Drafting Committee: E13.15 - Analytical Data

Relations

• Replaces: ASTM E1578-13 - Standard Guide for Laboratory Informatics
• Effective Date: 01-Aug-2018
• Refers: ASTM E2077-00(2016) - Standard Specification for Analytical Data Interchange Protocol for Mass Spectrometric Data
• Effective Date: 01-Apr-2016
• Refers: ASTM E2078-00(2016) - Standard Guide for Analytical Data Interchange Protocol for Mass Spectrometric Data
• Effective Date: 01-Apr-2016
• Refers: ASTM E2078-00(2010) - Standard Guide for Analytical Data Interchange Protocol for Mass Spectrometric Data
• Effective Date: 01-Nov-2010
• Refers: ASTM E2077-00(2010) - Standard Specification for Analytical Data Interchange Protocol for Mass Spectrometric Data
• Effective Date: 01-Nov-2010
• Refers: ASTM E1947-98(2009) - Standard Specification for Analytical Data Interchange Protocol for Chromatographic Data
• Effective Date: 01-Oct-2009
• Refers: ASTM E1948-98(2009) - Standard Guide for Analytical Data Interchange Protocol for Chromatographic Data
• Effective Date: 01-Oct-2009
• Refers: ASTM E2369-05e2 - Standard Specification for Continuity of Care Record (CCR)
• Effective Date: 01-Oct-2005
• Refers: ASTM E2369-05e1 - Standard Specification for Continuity of Care Record (CCR)
• Effective Date: 01-Oct-2005
• Refers: ASTM E2369-05 - Standard Specification for Continuity of Care Record (CCR)
• Effective Date: 01-Oct-2005
• Refers: ASTM E2077-00(2005) - Standard Specification for Analytical Data Interchange Protocol for Mass Spectrometric Data
• Effective Date: 01-Sep-2005
• Refers: ASTM E2078-00(2005) - Standard Guide for Analytical Data Interchange Protocol for Mass Spectrometric Data
• Effective Date: 01-Sep-2005
• Refers: ASTM E1947-98(2004) - Standard Specification for Analytical Data Interchange Protocol for Chromatographic Data
• Effective Date: 01-Apr-2004
• Refers: ASTM E1948-98(2004) - Standard Guide for Analytical Data Interchange Protocol for Chromatographic Data
• Effective Date: 01-Apr-2004
• Refers: ASTM E2077-00 - Standard Specification for Analytical Data Interchange Protocol for Mass Spectrometric Data
• Effective Date: 10-Mar-2000

Overview

ASTM E1578-18, Standard Guide for Laboratory Informatics, is a comprehensive guideline developed by ASTM International to support laboratories in the selection, implementation, and lifecycle management of laboratory informatics tools. Laboratory informatics encompasses the application of information technology to optimize laboratory operations, including the collection, storage, processing, analysis, reporting, and archival of laboratory data. This standard serves to educate a broad range of stakeholders, including new users, managers, IT professionals, vendors, and regulatory personnel, on the best practices and requirements for modern laboratory information systems.

ASTM E1578-18 outlines terminology, functionality, and integration considerations for core informatics tools such as Laboratory Information Management Systems (LIMS), Electronic Laboratory Notebooks (ELN), Laboratory Execution Systems (LES), Scientific Data Management Systems (SDMS), and Chromatography Data Systems (CDS). The standard also addresses the full informatics life cycle, from initial specification to system retirement.

Key Topics

• Introduction to Laboratory Informatics: Defines informatics as the merging of IT and laboratory workflow to enable efficient data management.
• Core Informatics Systems:
  • LIMS (Laboratory Information Management Systems): For sample tracking, test management, and compliance.
  • LIS (Laboratory Information Systems): Clinical laboratory operations and results management.
  • LES (Laboratory Execution Systems): Method execution at the bench level.
  • ELN (Electronic Laboratory Notebooks): Electronic documentation of experiments and research.
  • SDMS (Scientific Data Management Systems): Secure data storage and archiving across platforms.
  • CDS (Chromatography Data Systems): Data integration and analysis from analytical instruments.
• Standard Terminology: Provides a unified vocabulary to reduce confusion among users and vendors.
• Life Cycle Management: Covers system specification, acquisition, validation, implementation, ongoing use, upgrades, and decommissioning.
• Integration: High-level discussion of interoperability and data exchange between multiple systems and instruments.
• Functional Requirements Checklist: Example checklist to guide purchasing, upgrading, or customizing laboratory informatics solutions.

Applications

ASTM E1578-18 is applicable to a diverse array of laboratory environments and industries, including:

• General Laboratories: Standard organizations, government, and regulatory.
• Environmental Monitoring: Data-intensive workflows in compliance-driven environments.
• Life Sciences and Healthcare: Biotechnology, diagnostics, pharmaceuticals, public health, and hospital settings.
• Industry Sectors: Heavy industry, food and beverage labs, transportation, resources, and manufacturing.
• Public Sector: Forensics, education, utilities, and non-profits.

The standard is used by project managers, IT and quality professionals, laboratory directors, informatics vendors, and support staff to:

• Select the right informatics solution based on laboratory needs and processes.
• Configure, validate, and document laboratory systems for compliance and operational efficiency.
• Justify investment in new or upgraded informatics tools.
• Standardize processes for data integrity, electronic signature, and regulatory reporting.
• Integrate laboratory data with enterprise systems such as ERP, MES, and document management systems.

Related Standards

ASTM E1578-18 references and aligns with several key industry standards for laboratory informatics, data integrity, and system validation:

• ASTM Standards: E1947 (Analytical Data Interchange Protocol for Chromatographic Data), E2066, and E2077.
• ISO/IEC/IEEE Standards: ISO/IEC 27000 (Information Security Management), ISO/IEEE 11073, ISO/HL7 27932 (HL7 Clinical Document Architecture), ISO/IEC/IEEE 12207 (Software Life Cycle Processes).
• HL7, LOINC, and SNOMED-CT: For health data exchange and medical terminology.
• GAMP 5: Guidance for validation of automated systems.
• NIST Cybersecurity Framework: For protecting laboratory data.
• FDA 21 CFR Part 11: Electronic records and signatures requirements.

For a complete list of referenced standards and further reading, consult the official ASTM E1578-18 document and its bibliography.

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Keywords: ASTM E1578-18, laboratory informatics, LIMS, ELN, SDMS, LIS, laboratory information management systems, data integrity, regulatory compliance, laboratory information systems, standard guide, laboratory automation, data management systems, laboratory software.

Standards Content (Sample)

This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the
Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.
Designation: E1578 − 18
Standard Guide for
Laboratory Informatics
This standard is issued under the fixed designation E1578; the number immediately following the designation indicates the year of
original adoption or, in the case of revision, the year of last revision. A number in parentheses indicates the year of last reapproval. A
superscript epsilon (´) indicates an editorial change since the last revision or reapproval.
1. Scope primary laboratory informatics tools include laboratory infor-
mation management systems (LIMS), laboratory execution
1.1 This guide helps describe the laboratory informatics
systems (LES), laboratory information systems (LIS), elec-
landscape and covers issues commonly encountered at all
troniclaboratorynotebooks(ELN),scientificdatamanagement
stagesinthelifecycleoflaboratoryinformaticsfrominception
systems (SDMS), and chromatography data systems (CDS).
to retirement. It explains the evolution of laboratory informat-
ics tools used in today’s laboratories such as laboratory
1.4 Scope Considerations when Selecting and Implementing
information management systems (LIMS), laboratory execu- Laboratory Informatics Solutions—Many laboratories have
tion systems (LES), laboratory information systems (LIS),
determined that they need to deploy multiple laboratory
electronic laboratory notebooks (ELN), scientific data manage- informatics systems to automate their laboratory processes and
ment systems (SDMS), and chromatography data systems
managetheirdata.Selectionofaninformaticssolutionrequires
(CDS). It also covers the relationship (interactions) between a detailed analysis of the laboratory’s requirements and should
these tools and the external systems in a given organization.
not be a simple product category decision. Information tech-
The guide discusses supporting laboratory informatics tools nology (IT) representatives and subject matter experts (SMEs)
and a wide variety of the issues commonly encountered at
whounderstandtheneedsofthelaboratoryneedtobeinvolved
different stages in the life cycle. The subsections that follow in the selection and implementation of a laboratory informatics
describe the scope of this document in specific areas. systemtoensurethattheneedsofthelaboratoryaremetandIT
can support it. Customers (internal and external) of laboratory
1.2 High-Level Purpose—The purpose of this guide in-
information should also be included in the laboratory informat-
cludes: (1) educating new users on laboratory informatics
icssolutiondesigntoensurefullelectronicintegrationbetween
tools; (2) providing a standard terminology that can be used by
systems.
different vendors and end users; (3) establishing minimum
requirements for laboratory informatics; (4) providing guid- 1.5 The scope of this guide covers a wide range of labora-
ance for the specification, evaluation, cost justification,
tory types, industries, and sizes. Examples of laboratory types
implementation, project management, training, and documen-
and industries include:
tation of the systems; and (5) providing a functional require-
1.5.1 General Laboratories:
ments checklist for laboratory informatics systems that can be
1.5.1.1 Standards (ASTM, IEEE, ISO) and
adopted within the laboratory and integrated with existing
1.5.1.2 Government(EPA,FDA,JPL,NASA,NRC,USDA,
systems.
USGS, FERC).
1.5.2 Environmental:
1.3 Laboratory Informatics Definition—Laboratory infor-
1.5.2.1 Environmental monitoring.
matics is the specialized application of information technology
1.5.3 Life Science Laboratories:
aimed at optimizing laboratory operations. It is a collection of
1.5.3.1 Biotechnology and
informatics tools utilized within laboratory environments to
1.5.3.2 Diagnostic.
collect, store, process, analyze, report, and archive data and
1.5.4 Healthcare and Medical:
information from the laboratory and its supporting processes.
1.5.4.1 Bionomics/genomics,
Laboratory informatics includes the effective use of critical
data management systems, the electronic delivery of results to 1.5.4.2 Medical devices,
customers, and the use and integration of supporting systems 1.5.4.3 Pharmaceutical,
(for example, training and policy management). Examples of
1.5.4.4 Veterinary,
1.5.4.5 Public health, and
1 1.5.4.6 Hospital.
This guide is under the jurisdiction of ASTM Committee E13 on Molecular
Spectroscopy and Separation Science and is the direct responsibility of Subcom- 1.5.5 Heavy Industry Laboratories:
mittee E13.15 on Analytical Data.
1.5.5.1 Energy and resources,
Current edition approved Aug. 1, 2018. Published September 2018. Originally
1.5.5.2 Manufacturing and construction,
approved in 1993. Last previous edition approved in 2013 as E1578-13. DOI:
10.1520/E1578-18. 1.5.5.3 Materials and chemicals, and
Copyright © ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959. United States
E1578 − 18
1.5.5.4 Transportation and shipping. Individuals who are purchasing specific tools may also use this
1.5.6 Food and Beverage Laboratories: guide to identify functions that are recommended for specific
laboratory environments. Research and development staff of
1.5.6.1 Agriculture,
different commercial laboratory informatics systems vendors
1.5.6.2 Beverages,
mayusetheguideasatooltoevaluate,identify,andpotentially
1.5.6.3 Food, and
improve the capabilities of their products. The vendors’ sales
1.5.6.4 Food service and hospitality.
staff may use the guide to represent functions of their labora-
1.5.7 Public Sector Laboratories:
tory informatics products to prospective customers in more
1.5.7.1 Law enforcement/forensic,
generic and product-neutral terms.
1.5.7.2 State and local government,
1.9 Out of Scope—This guide does not attempt to define the
1.5.7.3 Education and nonprofits, and
boundaries of laboratory informatics, as they continue to
1.5.7.4 Public utilities (water, electric, waste treatment).
evolve and blur between the different types of tools; rather, it
1.6 Integration—The scope of integration covered in this
focuses on the functionality that is provided by laboratory
guide includes communication and meaningful data exchange
informatics as a whole.
between different laboratory informatics tools and other exter-
1.10 This international standard was developed in accor-
nal systems (document management, chromatography data
dance with internationally recognized principles on standard-
systems, laboratory instruments, spectroscopy data systems,
ization established in the Decision on Principles for the
enterprise resource planning (ERP), manufacturing execution
Development of International Standards, Guides and Recom-
systems (MES), investigations/deviations and CAPA manage-
mendations issued by the World Trade Organization Technical
ment systems), and other integrated business systems (for
Barriers to Trade (TBT) Committee.
example, clinical or hospital environments) provide significant
business benefits to any laboratory and is discussed at a high
2. Referenced Documents
level in this guide.
2.1 ASTM Standards:
1.7 Life-Cycle Phases—The scope of this guide is intended
E1394 Specification for Transferring Information Between
to provide an understanding of laboratory informatics tools’
Clinical Instruments and Computer Systems (Withdrawn
life cycle from project initiation point to retirement and 3
2002)
decommissioning. This guide was designed to help newer
E1947 Specification for Analytical Data Interchange Proto-
audiences in understanding the complexity in the relationships
col for Chromatographic Data
between different laboratory informatics tools and how to plan
E1948 Guide for Analytical Data Interchange Protocol for
and manage the implementation project, while seasoned users
Chromatographic Data
may use the differentlifecyclestomaintainexistinglaboratory
E2077 Specification for Analytical Data Interchange Proto-
informatics tools. Integrating additional informatics tools to
col for Mass Spectrometric Data
existing ones in today’s evolving laboratory environment adds
E2078 Guide for Analytical Data Interchange Protocol for
constraints that need to be considered. The life-cycle discus-
Mass Spectrometric Data
sionincludesboththelaboratoryinformaticssolutionlifecycle
E2369 Specification for Continuity of Care Record (CCR)
as well as the project life cycle.
2.2 CDISC Standard:
1.7.1 The product life cycle encompasses a specific labora-
SEND Standard for Exchange of Nonclinical Data;
tory informatics system and the expected useful life of that
2.3 CIDX Standard:
system before it needs to be replaced or upgraded.
CIDX Chemistry Industry Data eXchange
1.7.2 The project life cycle encompasses the activities to
2.4 EPA Standard:
acquire, implement, operate, and eventually retire a specific
ESAR Environmental Sampling, Analysis and Results Data
laboratory informatics system.
Standard
1.8 Audience—This guide has been created with the needs
2.5 FDA Regulation:
of the following stakeholders in mind: (1) end users of
21 CFR Part 11 Electronic Records; Electronic Signatures,
laboratory informatics tools, (2) implementers of laboratory
62 FR 13464
informatics tools, (3) quality personnel, (4) information tech-
nology personnel, (5) laboratory informatics tools vendors, (6)
For referenced ASTM standards, visit the ASTM website, www.astm.org, or
instrument vendors, (7) individuals who approve laboratory
contact ASTM Customer Service at [e-mail]. For Annual Book of ASTM
informatics tools funding, (8) laboratory informatics applica-
Standards volume information, refer to the standard’s Document Summary page on
tions support specialists, and (9) software test/validation spe-
the ASTM website.
The last approved version of this historical standard is referenced on
cialists.Informationcontainedinthisguidewillbenefitabroad
www.astm.org.
audience of people who work in or interact with a laboratory.
Available from Clinical Data Interchange Standards Consortium (CDISC), 401
New users can use this guide to understand the purpose and
West 15th Street, Suite 800, Austin, TX 78701, https://www.cdisc.org/.
functions of the wide variety of laboratory informatics tools as
The CIDX Chem eStandards are available at OAGi, P.O. Box 4897, Marietta,
GA 30061-4897, http://www.oagi.org/.
well as the interactions between these tools with external
Available from United States Environmental Protection Agency (EPA), 1200
systems. The guide can also help prospective users in under-
Pennsylvania Ave., NW, Washington, DC 20460, http://www.epa.gov/.
standingterminology,configurations,features,design,benefits,
Available from U.S. Food and Drug Administration (FDA), 10903 New
and costs of these different laboratory informatics tools. Hampshire Ave., Silver Spring, MD 20993, http://www.fda.gov.
E1578 − 18
FDAData Integrity and Compliance with CGMP: Guidance 2.13 NCPDP Standard:
for Industry Batch Transaction Format
2.6 HL7 Standards:
2.14 NIST Standard:
Health Level Seven Standards
NIST Cybersecurity Framework
2.7 ICH Standard:
2.15 NRC Standards:
ICH Quality Guideline Q9 Quality Risk Management
10 10 CFR Appendix B to Part 50 Quality Assurance Criteria
2.8 IEEE Standards:
for Nuclear Power Plants and Fuel Reprocessing Plants,
IEEE 1012 Standard for System, Software, and Hardware
72 FR 49505
Verification and Validation
10 CFR Appendix E to Part 50 Emergency Planning and
IEEE 1028 Standard for Software Reviews and Audits
Preparedness for Production and Utilization Facilities, 80
2.9 ISA Standard:
FR 74980
ANSI/ISA-95.00.06 Enterprise-ControlSystemIntegration--
10CFRAppendixKtoPart50 ECCSEvaluationModels,65
Part 6: Messaging Service Model
12 FR 34921
2.10 ISO Standards:
2.16 PIC/S Standard:
ISO/IEC/IEEE 12207 Systems and software engineering --
PIC/S Good Practices for Data Management and Integrity in
Software life cycle processes
Regulated GMP/GDP Environments
ISO/IEC 27000 Information technology -- Security tech-
niques -- Information security management systems --
2.17 Regenstrief Institute Standard:
Overview and vocabulary
LOINC Logical Observation Identifiers Names and Codes
ISO/HL7 27932 Data Exchange Standards -- HL7 Clinical
2.18 SNOMED International Standard:
Document Architecture, Release 2
SNOMED-CT Systematized Nomenclature of Medicine-
ISO/IEEE 11073-10101 Health informatics -- Point-of-care
Clinical Terms
medical device communication -- Part 10101: Nomencla-
2.19 WHO Standard:
ture
WHO Technical Report Series, No. 996, Annex 5 Guidance
ISO/IEC/IEEE 26511 Systems and software engineering --
on good data and record management practices
Requirements for managers of user documentation
ISO/IEC/IEEE 26512 Systems and software engineering --
3. Terminology
Requirements for acquirers and suppliers of information
ISO/IEC/IEEE29119-4 Systemsandsoftwareengineering--
3.1 Definitions—This guide defines the majority of termi-
Software testing -- Part 4: Test techniques
nology used in the field of laboratory informatics. Users of this
ISO/IEC/IEEE29119-5 Systemsandsoftwareengineering--
guide should request a terminology list from each vendor with
Software testing -- Part 5: Keyword-Driven Testing
a cross reference to the terms used in this guide.
ISO/IEC/IEEE 29148 Systems and software engineering --
3.2 Definitions of Terms Specific to This Standard:
Life cycle processes -- Requirements engineering
3.2.1 artificial intelligence, AI, n—behavior by machines or
2.11 ISPE GAMP Guides:
computers versus the natural intelligence of humans and
ISPE GAMP 5: A Risk-based Approach to Compliant GxP
animals.
Computerized Systems
3.2.1.1 Discussion—In the computer science arena, any
ISPE GAMP Guide: Records & Data Integrity
device that perceives its environment and takes action to
2.12 MHRA Standard:
maximize success in achieving a goal is exhibiting AI. Ma-
MHRA GxP Data Integrity Definitions and Guidance for
chine learning is an application of artificial intelligence that
Industry
providessystemstheabilitytoautomaticallylearnandimprove
from experience without being explicitly programmed.
Registered trademark of and available from Health Level Seven (HL7)
3.2.2 chromatography data system, CDS, n—computer sys-
International, 3300 Washtenaw Avenue, Suite 227, Ann Arbor, MI 48104, http://
tem used to acquire, analyze, store, and report information
www.hl7.org/.
from chromatographic instruments.
Available from International Conference on Harmonisation of Technical
Requirements for Registration of Pharmaceuticals for Human Use (ICH), ICH
Secretariat, 9, chemin des Mines, P.O. Box 195, 1211 Geneva 20, Switzerland,
http://www.ich.org.
10 15
Available from Institute of Electrical and Electronics Engineers, Inc. (IEEE), Available from National Council for Prescription Drug Programs (NCPDP),
445 Hoes Ln., Piscataway, NJ 08854-4141, http://www.ieee.org. 9240 East Raintree Drive, Scottsdale, AZ 85260-7518, https://www.ncpdp.org/.
11 16
Available from The International Society of Automation (ISA), 67 T. W. Available from National Institute of Standards and Technology (NIST), 100
Alexander Drive, P. O. Box 12277, Research Triangle Park, NC 27709, http:// Bureau Dr., Stop 1070, Gaithersburg, MD 20899-1070, http://www.nist.gov.
www.isa.org. Available from U. S. Nuclear Regulatory Commission (NRC), 11555 Rock-
Available from International Organization for Standardization (ISO), ISO ville Pk., Rockville, MD 20852, http://www.nrc.gov.
Central Secretariat, BIBC II, Chemin de Blandonnet 8, CP 401, 1214 Vernier, Available from PIC/S Secretariat, 14 rue du Roveray CH, 1207 Geneva,
Geneva, Switzerland, http://www.iso.org. Switzerland, https://picscheme.org/.
Registered trademark of and available from International Society for Pharma- Registered trademark of and available fromThe Regenstrief Institute, Inc, 410
ceutical Engineering (ISPE), 600 N. Westshore Blvd., Suite 900, Tampa, FL33609, West 10th Street, Suite 2000, Indianapolis, IN 46202-3012, http://loinc.org.
http://www.ispe.org. Available from SNOMED International, One Kingdom St., Paddington
Available from Medicines and Healthcare products Regulatory Agency, Her Central, London W2 6BD, United Kingdom, https://www.snomed.org/.
Majesty’s Government, 10 South Colonnade, London E14 4PU, United Kingdom, Available from World Health Organization (WHO), Avenue Appia 20, 1202
https://www.gov.uk/. Geneva, Switzerland, http://www.who.int.
E1578 − 18
3.2.3 cloud computing, v—term generally used to refer to cycle, including document initiation, multiple review levels,
software applications that are delivered as a software service versioncontrol,security,andarchivingofhistoricalversionsof
through remote hosting using the public internet (public cloud) documents.
or within the users’ network environment (private cloud).
3.2.9 electronic laboratory notebook, ELN, n—software
3.2.3.1 Discussion—Essentially, the difference between
program designed to replace paper laboratory notebooks; an
cloud computing and traditional application deployment is that
electronic system on which to create, store, retrieve, and share
the application’s users may not be responsible for the installa-
fully electronic records in ways that meet all legal, regulatory,
tion and maintenance of the computing infrastructure and
technical, and scientific requirements.
application software.
3.2.9.1 Discussion—Laboratory notebooks, in general, are
3.2.4 corrective and preventative action, CAPA, n—CAPA
used by scientists, engineers, and technicians to document
applications are used to collect information, analyze
research, experiments, and procedures performed in a labora-
information, identify and investigate product and quality
tory. A laboratory notebook is often maintained to be a legal
problems, and take appropriate and effective corrective or
document and may be used in a court of law as evidence.
preventive (or both) action to prevent their recurrence.
Similar to an inventor’s notebook, the laboratory notebook is
3.2.4.1 Discussion—Verifying or validating corrective and
also often referred to in patent prosecution and intellectual
preventive actions, communicating corrective and preventive
property litigation.
action activities to responsible people, providing relevant
3.2.10 electronic signature, n—electronic representation of
information for management review, and documenting these
a handwritten signature.
activities are essential in dealing effectively with product and
quality problems, preventing their recurrence, and preventing
3.2.11 enterprise resource planning, ERP, n—computer sys-
or minimizing device failures.
temtointegratedifferenttypesofdatasuchasinventorylevels,
3.2.5 cybersecurity, n—set of technologies, practices, and
product orders, manufacturing capacity, inspection results,
processes used to protect computers, networks, programs, and
accounting data, and customer relationship management infor-
data from attack, damage, exploitation, and unauthorized
mation from organizations within an enterprise (company),
access. facilitating the flow of information between various business
functions across a company as well as with outside business
3.2.6 data exchange standardization, n—as defined by the
partners.
International Organization for Standardization (ISO) in ISO/
HL7 27932, the process of agreeing on standards, which
3.2.12 good automated manufacturing practice forum,
represent the common language that allows the exchange of
GAMP Forum, n—volunteer group under the auspices of the
data between disparate data systems.
InternationalSocietyofPharmaceuticalEngineering(ISPE)for
3.2.6.1 Discussion—The goals of standardization are to
writing guidance for the validation of computerized systems
achieve comparability, compatibility, and interoperability be-
used in the regulated portions of the pharmaceutical and allied
tween independent systems, to ensure compatibility of data for
industries and it is specifically designed to aid suppliers and
comparative statistical purposes, and to reduce duplication of
users in the pharmaceutical industry.
effort and redundancies. A data standard often includes data
3.2.13 integration broker, n—messaging application that
elements, data element definitions, and such agreements as
can receive or extract data from a source system at the
formats, message structures, and vocabulary. In the context of
appropriate time, transform the data, and route the reformatted
this paper, a standard is a specification or requirement and is
data to the target node.
not synonymous with a policy, procedure, guideline,
3.2.13.1 Discussion—An integration broker application can
framework, technique, or best practice.Adopting standards has
also provide a repository for archiving, searching, and retriev-
the potential to improve interoperability and reduce costs by
ing these messages.
facilitating the ability of networked laboratories to coordinate
activities during public health incidents where surge capacity
3.2.14 internet of things, IoT, n—system of objects—
may be required (for example, national response and readi-
computing devices, machines, objects, people, animals, and so
ness). Adopting standards may reduce the costs of laboratory
forth—that can connect to a network and communicate among
informatics system implementation and vendor/developer sup-
themselves, often without human intervention.
port.
3.2.14.1 Discussion—An IoT device is an object operating
3.2.7 data integrity, n—extenttowhichdataareattributable,
within that system.
complete, consistent, accurate, and reliable throughout the data
3.2.15 laboratory execution system, LES, n—computer sys-
life cycle.
tem used in the laboratory at the analyst work level to aid in
3.2.8 electronic document management system, EDMS,
step enforcement for laboratory test method execution.
n—computer system used to store, catalog, review/approve,
3.2.15.1 Discussion—LES focus on step execution of de-
retrieve, view, and print digital documents.
fined laboratory test methods. The LES is typically used in
3.2.8.1 Discussion—Modern EDMS applications typically
quality control laboratories that have defined test methods.The
provide the ability to manage a document throughout its life
functionality of a LES and a laboratory information manage-
ment system (LIMS) overlaps in the areas of result entry,
Foradditionalinformation,visittheFDA’sCAPApageathttp://www.fda.gov/. instrument integration, and specification flagging. Deployment
E1578 − 18
options include LES and LIMS systems deployed as an management, scheduled sample collection and testing, result
integrated solution, LIMS-only, or LES-only (for limited entry, capture of results from instruments, result review,
functions). reporting, trending, and business rule enforcement. These
systems interface with laboratory instruments (for example,
3.2.16 laboratory informatics, n—term used to describe the
CDS and other information systems such as ERP, LIS, or
specialized application of information technology aimed at
manufacturing execution systems [MES]).ALIMS is a highly
optimizing laboratory operations.
flexible application, which can be configured or customized to
3.2.16.1 Discussion—That technology includes informatics
facilitate a wide variety of laboratory workflow models.
tools used within laboratory environments to collect, store,
3.2.20 laboratory information system, LIS, n—class of ap-
process,analyze,report,andarchivedataandinformationfrom
plication software that supports clinical laboratories by helping
the laboratory and supporting processes. Laboratory informat-
laboratory personnel manage the quality and integrity of test
ics includes the effective use of critical data management
samples, departmental workflow functions, result review
systems,theelectronicdeliveryofresultstocustomers,andthe
processes, reports of finalized results, interpretations, and
use and integration of supporting systems (for example, train-
diagnoses.
ing and policy management). Examples of primary laboratory
3.2.20.1 Discussion—These systems often interface with
informatics tools include, LIMS, LES, CDS, ELN, laboratory
instruments and other information systems such as hospital
information systems (LIS), and scientific data management
information systems (HIS). A LIS is a highly configurable
systems (SDMS).
application and often includes laboratory-specific electronic
3.2.17 laboratory informatics tools configuration, n—refers
medical records, direct clinician access via secure web
to the process of changing the functions of any laboratory
connections, billing modules for laboratories performing com-
informatics tool to match the business processes used in a
mercial testing, sophisticated interface engines for routing
particular laboratory, and it does not involve the use of writing
orders and results to external systems, and on-board image
software code either via a recognized software language or a
archival systems for pathology images. Patient confidentiality
language provided by the informatics application supplier.
and HIPAA requirements define unique security functionality
3.2.17.1 Discussion—This is a GAMP Category 4 software
for a LIS. The College of American Pathologists (CAP)
and is defined as “Configured software including, LIMS, 23
publishes LIS product guides that list current LIS in the
SCADA, DCS, CDS, etc.” Such configuration typically in-
market.
volves using an interface provided by the vendor to enter
3.2.21 lean laboratory, n—set of management and organi-
information that describes the types of samples, analytical
zational processes that enables efficient testing flow, leveled
methods, specifications, and so forth, used in the laboratory. It
workloads, visual work assignment and tracking, and the
may also involve the configuration of options and businesses
elimination of waste.
rules within the tool.
3.2.21.1 Discussion—Lean laboratory designs yield
3.2.18 laboratory informatics tools customization, n—refers
productive, high-quality laboratory environments that are
to the process of changing the functions of any laboratory
sometimes supported by laboratory informatics tools.
informatics tool to match the business processes used in a
3.2.22 mapping tools, n—graphical data mapping,
particular laboratory.
conversion, and integration applications that map data between
3.2.18.1 Discussion—This is different from the previously
any combination of XML, database, flat file, EDI, Excel
mentioned tools configuration in that customization involves
(OOXML), XBRL, or web service, or both, then transforms
writing software code either via a recognized software lan-
data or autogenerates data integration code for the execution of
guage or a language provided by the informatics application
recurrent conversions.
supplier. This is a GAMP 5 software category. Such customi-
3.2.23 master data, n—represents the business objects
zation typically involves adding tables, modifying table
which are agreed on and shared across the enterprise.
structures, and writing code or programs to alter the behavior
3.2.23.1 Discussion—It can include relatively static
of any laboratory informatics tool.
reference,transactional,unstructured,analytical,andhierarchi-
3.2.19 laboratory information management system, LIMS,
cal data, as well as associated metadata. Examples of master
n—(1) computer software and hardware that can acquire,
data include product specifications, test method steps (to
analyze, report, and manage data and information in the
capture intermediate and final results), laboratory calculations,
laboratory; (2) computer software that is used in the laboratory
instrument information, and standard and reagent information.
for the management of samples, test results, laboratory users,
3.2.24 metadata, n—(1) data about data and (2) information
instruments, standards, and other laboratory functions such as
that describes another set of data.
invoicing, plate management, product/material stability
3.2.24.1 Discussion—Additional information about the data
programs, and work flow automation; and (3) a class of
that provides context and meaning, including how, when, and
application software which handles storing and managing of
by whom it was collected, and its relationship to the subject or
information generated by laboratory processes.
test. Metadata in any laboratory informatics tool’s context
3.2.19.1 Discussion—These systems are used to manage
laboratory processes, including master data definition, sample
management and chain of custody, work assignment, instru-
For additional information, visit CAP’s product guide page at http://
ment and equipment management, standard and reagent www.captodayonline.com.
E1578 − 18
typically includes all data that supports a test result that is better collect, process, analyze, report, store, and share the data
recorded in this tool. For example, a pH test includes a pH and information derived from the laboratory and its supporting
result that can be supported by metadata, including what
processes. These processes are often an integral part of a
instrument was used, what the calibration date of the instru-
laboratory’s workflow and include activities such as registra-
ment was, what standard buffer solutions (reagents) were used
tion of samples or experiments, or both, assignment of tests,
to calibrate the pH probe sensor, the expiration dates for the
entry of results, review and approval of results, and reporting.
standard solutions, and the temperature of the solution at time
Laboratory informatics’scope encompasses multiple technical
of measurement.
solutions or systems that are responsible for streamlining these
3.2.25 sample registration, n—process of recording incom- and other laboratory processes. Laboratory informatics is not
ing sample information in a given laboratory informatics tool. solely about software managing laboratory data; it has many
elements, some of which integrate or cross over with business
3.2.26 scientific data management system, SDMS,
management and other third-party tools. Those elements are
n—computer system used to capture, centrally store, catalog,
also becoming increasingly complex, both in functionality and
and manage data generated in a laboratory environment.
3.2.26.1 Discussion—These data are then available for re- interoperability. Outside of standard laboratory information
use and integration with other laboratory informatics systems. management systems (LIMS) and laboratory information sys-
An example of an SDMS is an electronic repository for reports tems (LIS), elements such as field data capture systems,
from laboratory informatics systems. The SDMS may include advanced analytics tools, and artificial intelligence continue to
raw data file storage and archiving of data. It may also provide
shape the field of laboratory informatics. The division between
e-signature functionality for review/approval.
these and other system categories continues to soften as
functionality continues to be added to each of them. LIMS
3.2.27 spectroscopic data systems, n—computer systems
were originally created to address laboratories’need to manage
used to collect, process, visualize, interpret, store, and report
information from spectroscopic instruments. laboratory operations and data, provide traceability for all
laboratory samples and equipment, and ensure that laboratory
4. Significance and Use
procedures are followed. Electronic laboratory notebooks
4.1 Relevance—This guide is intended to educate the in-
(ELNs), on the other hand, were originally created to meet
tended audience on many aspects of laboratory informatics.
scientists’ need to document their experimental design,
Specifically, the guide may:
execution, and conclusion in an electronic format instead of in
4.1.1 Help educate new users of laboratory informatics;
a paper notebook. The scientific data management system
4.1.2 Help educate general audiences in laboratories and
(SDMS) was created to provide a repository of all scientific
other organizations that use laboratory informatics;
data files and results regardless of instrument type.The current
4.1.3 Help educate instrument manufactures and producers
definitions of each of these system categories are far more
of other commonly interfaced systems;
encompassing and continue to evolve as the boundaries be-
4.1.4 Provide standard terminology that can be used by
tween categories continue to blur. That blurring of laboratory
laboratory informatics vendors and end users;
informatics elements, as well as their potential integration with
4.1.5 Establish a minimum set of requirements for primary
enterprise elements—both within organizations and with cus-
laboratory informatics functions;
tomers of laboratory information—are illustrated in Fig. 1.
4.1.6 Provide guidance on the tasks performed and docu-
Laboratory informatics and all it encompasses is shown with
mentation created in the specification, evaluation, cost
the large yellow circle on the left, while the internal business
justification, implementation, project management, training,
systems that support laboratories are found associated with the
and documentation of laboratory informatics; and
blue circle on the right. Surrounding both is a bubble repre-
4.1.7 Provide high-level guidance for the integration of
senting third-party interactions with both laboratory generated
laboratory informatics and other software tools.
data and business data. The figure highlights the wide variety
4.2 How to be Used—This guide is intended to be used by
of crossover and interactions that can occur both within and
all stakeholders involved in any aspect of laboratory informat-
external to laboratory informatics. Laboratory informatics
ics implementation, use, or maintenance.
applications are also taking on some of the functionality of
4.2.1 It is intended to be used throughout the laboratory
internal business systems. (See 7.6–7.11 for more information
informatics life cycle by individuals or groups responsible for
on integration cases.)
laboratory informatics implementation and use, including
5.1.1 Core Systems—These laboratory systems most often
specification, build/configuration, validation, use, upgrades,
provide the outward face of laboratory informatics and include
and retirement/decommissioning.
LIMS, LIS, laboratory execution systems (LES), ELN, SDMS,
4.2.2 This guide also provides an example of a laboratory
and chromatography data systems (CDS). Not all systems will
informatics functional requirements checklist that can be used
necessarily appear in a laboratory together; some are more
to guide the purchase, upgrade, or development of a laboratory
typical to certain laboratory types than others. However, they
informatics system.
usually play a key role in a laboratory’s research or analysis
5. Elements of Laboratory Informatics
activities, or both, and represent the key software systems with
which laboratory personnel and customers of the laboratory
5.1 Laboratory Informatics Elements Overview—
Laboratory informatics is used to help laboratory personnel may interact. From research samples and clinical specimens to
E1578 − 18
FIG. 1 Laboratory Informatics System Integration Concept Model
outlined experiments and raw instrument data, these core ELN include data import, content linking, preformatted and
systems fill a vital role in the laboratory informatics sphere. customizable templates, and messaging.
5.1.1.1 LIMS, LIS, and LES are alike in many regards in 5.1.1.3 An SDMS is designed primarily to consolidate data
that they all act as core systems in a laboratory and handle data and manage knowledge-based assets. The SDMS has typically
capture,analysis,review,storage,andreporting.Thesesystems excelled at handling unstructured files such as images,
integrate in variable degrees with analytical instruments, auto- spreadsheets, raw instrument files, and PDFs. A set of agreed-
mated tools, and other software systems, and they provide upon rules in the system dictate how incoming data is
certain levels of regulated, industry-standard security for the processed and structured in the SDMS, acting as a gatekeeper
data generated and transferred from its integrations. However, for what is captured and how (including the application of
these systems also have fundamental differences that place metadata).AnSDMScanbeintegratedwithaLIMS,ELN,and
them in specific use cases.ALIMS has been traditionally used so forth, to create a common repository for a laboratory’s data,
to process and report on batches of samples from research, which can then be further associated with specific projects,
quality control, and manufacturing laboratories, all of which experiments, or locations, or combinations thereof, or its data
handle mostly anonymous, complex laboratory data.ALIS has can simply be archived for long-term storage.
normally been used in the clinical context of specimens and 5.1.1.4 A CDS is designed for collecting, processing, and
patients, and a LES is most often adopted in automated and analyzing samples run on instruments managing chromatogra-
regulated manufacturing environments where quality control, phy techniques such as high-performance liquid chromatogra-
process control, test step execution, and instrument interface phy (HPLC), ion chromatography (IC), gas chromatography
and calculation validation support laboratory testing. (GC), size-exclusion chromatography (SEC), and affinity chro-
5.1.1.2 An ELN largely serves as an electronic replacement matography. The CDS typically consists of a combination of
for the traditional paper laboratory notebook associated with hardware and software connecting the instrument to the system
scientistsandtechniciansinresearch-drivenenvironments.The and is computationally intensive, rapidly generating large data
ELN may be tailored to the individual researcher, large sets in laboratory environments. Complex algorithms and
collaborative research efforts, or both. It may also be designed mathematical transformations of data can be performed within
tomanagetheactivitiesrelatedtoaspecificscientificdiscipline a CDS, which directly supports a wide range of chromatogra-
or application, or it may be cross-disciplinary, supporting data phy instruments with bidirectional control of instrument set-
of all types. Traditionally used to document experiments and tings (that is, temperature, pressure, and detector wavelength).
analysis, and act as intellectual property protection, the paper The CDS typically provides sample handing (auto samplers),
laboratory notebook has fallen out of favor with some labora- auto injection, mobile phase controls (temperature/pressure),
tories that prefer the ELN’s ability to improve search, support detectorcontrol(wavelength),datacollection(datapointsfrom
collaboration, and limit siloed data. Additional features of an one or more detectors), data analysis (for example, calibration
E1578 − 18
curves, peak detection, and integration), reporting, and audit typically allow native mobile apps to integrate, improving data
trail support.The CDS can be deployed as a standalone system analysis and reducing manual data input time.
or in larger configurations supporting multiple instruments, 5.1.5 Laboratory Support Systems—These systems are typi-
sites, and geographic regions. The CDS is typically interfaced cally ancillary to the core systems, filling in functionality gaps
to other laboratory informatics tools (that is, LIMS, ELN, and that the core systems do not provide. Quality management
SDMS) in which sample information is passed between the software is one such example, used to formulate quality policy
andobjectives,standardoperatingprocedures,andtherequired
LIMS and the CDS, and the CDS test results (that is, peak
records used for the quality certification process. Middleware
areas) are passed back to the LIMS for final reporting. The
that can handle auto-validation of samples represents another
CDS can also integrate with multiple analytical techniques in
example. The following may all be considered part of this
which data are passed between different instruments [such as a
category:
liquid chromatography-mass spectrometry (LC-MS) instru-
5.1.5.1 Artificial intelligence (AI) tools and algorithms are
ment].Thesoftwareistypicallytreatedasaseparatelaboratory
being used by researchers to inspect data better and make
informatics element with its own IT infrastructure, including
discoveries in the laboratory, while laboratory tools such as
data acquisition modules (to attach to chromatography instru-
freezers, incubators, and air-cleaning systems are becoming
ments) and administration, configuration, and security access
“smarter” with added sensors that can feed data to one or more
controls.
software systems for monitoring.
5.1.1.5 Bioinformatics and genomic applications are used to
5.1.5.2 Batch and lot management tools assist with the
collect and analyze biological data, including genomic data.
creation, genealogy, review, and disposition of samples en
Genomic instruments generate much larger amounts of data
masse,intheprocessassigningthesamepropertiesandprocess
compared to traditional laboratory instruments. Genomic data
tracking for increased efficiency.
is often analyzed using specialized, proprietary bioinformatics
5.1.5.3 Capacity planning and laboratory scheduling im-
algorithms.
proves the efficiency of laboratory workflow, allowing labora-
5.1.2 Instrument Data Systems—Some laboratory systems
tory personnel to use better the time and resources of available
are purpose-made for specific instruments, with the CDS being
personnel and equipment. Such tools take into account sched-
a common case. Other examples include data acquisition
uled instrument maintenance and planned time off of research-
systems (DAQ) for calibration equipment and digital oscillo-
ers.
scope software. These systems excel at “talking” with a
5.1.5.4 Compliance management, whether embedded in a
specific instrument, capturing the data, and providing custom
core system or installed as a support system, helps keep
analysis tools related to the captured data. In the case of
laboratories of all types on track with complying with govern-
chromatography, a CDS will often both control a chromatog-
ment regulations. Aside from the typical audit trails and
raphyorspectroscopyinstrumentandprovideavisualreportof
electronic signatures, compliance management tools also may
the chromatogram with contextual meaning. DAQ for calibra-
assist with risk assessments, business governance, and contrac-
tion instruments may include additional functionality such as
tual obligation management.
real-time data visualization and certificate generation.
5.1.5.5 Data integrity is a core competency and expectation
5.1.3 Advanced Analytics Tools—This element represents a
of laboratory informatics solutions. Data integrity includes the
broad category of advanced analytical tools used in laborato-
maintenance and assurance of the accuracy and consistency of
ries.Examplesincludethescientificfieldofgenomicsinwhich
data over its entire life cycle. Data integrity is a critical design
advanced tools are used to study complete genomes (genetic
requirement that touches every element of laboratory informat-
material within an organism). High-throughput genome ana-
ics that stores, processes, or retrieves laboratory data. (See
lyzer instruments automate process steps to provide high-
Section 10 for more on data integrity.)
volume parallel operations that combine DNA molecules,
5.1.5.6 Human resource management encompasses the ac-
primers, polymerase amplification, imaging, and computa-
tivities associated with managing the data surrounding labora-
tional functions to yield low-cost DNA sequencing outputs.
tory personnel. This includes the management of analyst
Advanced tools are also used to automate DNA sequence
training records, qualifications, certifications, and perfor-
assembly (reconstruction of an original DNA sequence). Ad-
mance.
vanced annotation tools/instruments are used to annotate DNA
5.1.5.7 Instrument and equipment management tools help to
sequencesbyidentifyingportionsofthegenomethatdoanddo
determine on- or offline status, assist with calibration
not code for proteins, including supporting biological informa-
management, update service and preventative maintenance
tion.
schedules, and present the qualification s
...

This document is not an ASTM standard and is intended only to provide the user of an ASTM standard an indication of what changes have been made to the previous version. Because
it may not be technically possible to adequately depict all changes accurately, ASTM recommends that users consult prior editions as appropriate. In all cases only the current version
of the standard as published by ASTM is to be considered the official document.
Designation: E1578 − 13 E1578 − 18
Standard Guide for
Laboratory Informatics
This standard is issued under the fixed designation E1578; the number immediately following the designation indicates the year of
original adoption or, in the case of revision, the year of last revision. A number in parentheses indicates the year of last reapproval. A
superscript epsilon (´) indicates an editorial change since the last revision or reapproval.
1. Scope
1.1 This guide helps describe the laboratory informatics landscape and covers issues commonly encountered at all stages in the
life cycle of laboratory informatics from inception to retirement. It explains the evolution of laboratory informatics tools used in
today’s laboratories such as Laboratory Information Management Systems (LIMS), Electronic Laboratory Notebooks (ELN),
Scientific Data Management Systems (SDMS), and Chromatography Data Systemslaboratory information management systems
(LIMS), laboratory execution systems (LES), laboratory information systems (LIS), electronic laboratory notebooks (ELN),
scientific data management systems (SDMS), and chromatography data systems (CDS). It also covers the relationship
(interactions) between these tools and the external systems in a given organization. The guide discusses supporting laboratory
informatics tools and a wide variety of the issues commonly encountered at different stages in the life cycle. The
sub-sectionssubsections that follow describe details of the scope of this document in specific areas.
1.2 High-Level Purpose—The purpose of this guide includes: (1) helping educate educating new users ofon laboratory
informatics tools,tools; (2) provideproviding a standard terminology that can be used by different vendors and end users,users; (3)
establishestablishing minimum requirements for laboratory informatics,informatics; (4) provideproviding guidance for the
specification, evaluation, cost justification, implementation, project management, training, and documentation of the systems,
systems; and (5) provide function checklist examples providing a functional requirements checklist for laboratory informatics
systems that can be adopted within the laboratory and integrated with the existing systems.
1.3 Laboratory Informatics Definition—Laboratory informatics is the specialized application of information technology aimed
at optimizing laboratory operations. It is a collection of informatics tools utilized within laboratory environments to collect, store,
process, analyze, report, and archive data and information from the laboratory and its supporting processes. Laboratory informatics
includes the integration of effective use of critical data management systems, the electronic delivery of results to customers, and
the use and integration of supporting systems including (for example, training and policies. policy management). Examples of
primary laboratory informatics include: Laboratory Information Management Systems (LIMS), Electronic Laboratory Notebooks
(ELNs), Chromatography Data Systems (CDS), and Scientific Data Management Systems (SDMS).tools include laboratory
information management systems (LIMS), laboratory execution systems (LES), laboratory information systems (LIS), electronic
laboratory notebooks (ELN), scientific data management systems (SDMS), and chromatography data systems (CDS).
NOTE 1—Laboratory informatics scope encompasses multiple technical solutions or systems. The division between these system categories continues
to soften as functionality continues to be added to each of them. LIMS were originally created to address the laboratories’ need to manage laboratory
operations and data, provide traceability for all laboratory samples and equipment, and ensure that laboratory procedures are followed. ELNs, on the other
hand, were originally created to meet the scientists’ need to document their experimental design, execution, and conclusions in an electronic format instead
of in a paper notebook. SDMS was created to provide a repository of all scientific data files and results regardless of instrument type. The current
definitions of each of these system categories are far more encompassing.
1.4 Scope Considerations Whenwhen Selecting and Implementing Laboratory Informatics Solutions—Many laboratories have
determined that they need to deploy multiple laboratory informatics systems to automate their laboratory processprocesses and
manage their data. Selection of an informatics solution requires a detailed analysis of the laboratory’s requirements rather than by
choosing a product category. It is important to include representatives from Information Technology (IT) and Subject Matter
Experts (SMEs),and should not be a simple product category decision. Information technology (IT) representatives and subject
matter experts (SMEs) who understand the needs of the laboratory, laboratory need to be involved in the selection and
implementation of a laboratory informatics system to ensure that the needs of the laboratory are met and that IT can support it.
Customers (internal and external) of laboratory information should also be included in the laboratory informatics solution
design,design to ensure there is full electronic integration between systems.
This guide is under the jurisdiction of ASTM Committee E13 on Molecular Spectroscopy and Separation Science and is the direct responsibility of Subcommittee E13.15
on Analytical Data.
Current edition approved Aug. 1, 2013Aug. 1, 2018. Published November 2013September 2018. Originally approved in 1993. Last previous edition approved in 20062013
as E1578-06.-13. DOI: 10.1520/E1578-13.10.1520/E1578-18.
Copyright © ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959. United States
E1578 − 18
1.5 The scope of this guide covers a wide range of laboratory types, industries, and sizes. Examples of laboratory types and
industries are listed in the following:include:
1.5.1 General Laboratories:
1.5.1.1 Standards (ASTM, IEEE, ISO),ISO) and
1.5.1.2 Government (EPA, FDA, JPL, NASA, NRC, USDA, USGS, FERC).
1.5.2 Environmental:
1.5.2.1 Environmental Monitoring.monitoring.
1.5.3 Life Science Laboratories:
1.5.3.1 Biotechnology,Biotechnology and
1.5.3.2 Diagnostic.
1.5.4 Healthcare and Medical:
1.5.4.1 Devices,Bionomics/genomics,
1.5.4.2 Pharmaceuticals vet/animal,Medical devices,
1.5.4.3 Pharmaceutical,
1.5.4.4 Veterinary,
1.5.4.5 Public health, and
1.5.4.6 Hospital LIS.Hospital.
1.5.5 Heavy Industry Laboratories:
1.5.5.1 Energy and resources,
1.5.5.2 Manufacturing and construction,
1.5.5.3 Materials and chemicals, and
1.5.5.4 Transportation and shipping.
1.5.6 Food and Beverage Laboratories:
1.5.6.1 Agriculture,
1.5.6.2 Beverages,
1.5.6.3 Food, and
1.5.6.4 Food service and hospitality.
1.5.7 Public Sector Laboratories:
1.5.7.1 Law enforcement,enforcement/forensic,
1.5.7.2 State and local government,
1.5.7.3 Education,Education and nonprofits, and
1.5.7.4 Public utilities (water, electric, waste treatment).
1.6 Integration—The scope of integration covered in this guide includes communication and meaningful data exchange between
different laboratory informatics tools and other external systems (document management, chromatography data systems, laboratory
instruments, spectroscopy data systems, Enterprise Resource Planning (ERP), Manufacturing Execution Systems (MES),
Investigations/Deviationsenterprise resource planning (ERP), manufacturing execution systems (MES), investigations/deviations
and CAPA management systems), and other integrated business systems (for example, clinical or hospital environments) provide
significant business benefits to any laboratory and is discussed at a high level in this guide.
1.7 Life Cycle Life-Cycle Phases—The scope of this guide is intended to provide an understanding of laboratory informatics
tools’ life cycle from project initiation point to retirement and absolution.decommissioning. This guide was designed to help newer
audiences in understanding the complexity in the relationships between different laboratory informatics tools and how to plan and
manage the implementation project, while seasoned users may use the different life cycles to maintain existing laboratory
informatics tools. Integrating additional tool(s) informatics tools to the existing one(s)ones in today’s evolving laboratory
informatics world environment adds constraints that need to be considered. The lifecyclelife-cycle discussion includes both the
laboratory informatics solution lifecycle life cycle as well as the project lifecycle, which describes steps to a laboratory informatics
solution.life cycle.
1.7.1 The product lifecycle life cycle encompasses a specific laboratory informatics system and the expected useful life of that
system before it needs to be replaced or upgraded.
1.7.2 The project lifecycle life cycle encompasses the activities to acquire, implement, operate, and eventually retire a specific
laboratory informatics system.
1.8 Audience—This guide has been created with the needs of the following stakeholders in mind: (1) end users of laboratory
informatics tools, (2) implementers of laboratory informatics tools, (3) quality personnel, (4) information technology personnel,
(5) laboratory informatics tools vendors, (6) instrument vendors, (7) individuals who shall approve laboratory informatics tools
funding, (8) laboratory informatics applications support specialists, and (9) software test/validation specialists. Information
contained in this guide will benefit a broad audience of people who work in or interact with a laboratory. New users can use this
guide to understand the purpose and functions of the wide varietiesvariety of laboratory informatics tools as well as the interactions
between these tools with external systems. The guide can also help prospective users in understanding terminology, configurations,
E1578 − 18
features, design, benefits, and costs of these different laboratory informatics tools. Individuals who are purchasing (a) specific
tool(s)tools may also use this guide to identify functions that are recommended for specific laboratory environments. Research and
development staff of different commercial laboratory informatics systems vendors may use the guide as a tool to evaluate, identify,
and potentially improve the capabilities of their products. The vendors’ sales staff may use the guide to represent functions of their
laboratory informatics products to prospective customers in more generic and product neutral product-neutral terms.
1.9 Out of Scope—This guide does not attempt to define the boundaries, boundaries of laboratory informatics, as they continue
to evolve, evolve and blur between the different types of laboratory informatics but rather tools; rather, it focuses on the
functionality that is provided by laboratory informatics as a whole.
1.10 This international standard was developed in accordance with internationally recognized principles on standardization
established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued
by the World Trade Organization Technical Barriers to Trade (TBT) Committee.
2. Referenced Documents
2.1 ASTM Standards:
E1340E1394 Guide for Rapid Prototyping of Information Specification for Transferring Information Between Clinical
Instruments and Computer Systems (Withdrawn 2017)2002)
E1947 Specification for Analytical Data Interchange Protocol for Chromatographic Data
E2066E1948 Guide for Validation of Laboratory Information Management SystemsAnalytical Data Interchange Protocol for
Chromatographic Data (Withdrawn 2015)
E2077 Specification for Analytical Data Interchange Protocol for Mass Spectrometric Data
E2078 Guide for Analytical Data Interchange Protocol for Mass Spectrometric Data
E2369 Specification for Continuity of Care Record (CCR)
2.2 EPA Data CDISC Standard:
40 CFR 160SEND Code of Regulations, 54 FR 34067, August 17, 1989Standard for Exchange of Nonclinical Data;
2.3 CIDX Standard:
CIDX Chemistry Industry Data eXchange
2.4 EPA Standard:
ESAR Environmental Sampling, Analysis and Results Data Standard
2.5 FDA Regulation:
FDA 21 CFR Part 11 Electronic Records, Electronic Signatures Final Rule, 62 Federal Register 13464, March 20, 1997Records;
Electronic Signatures, 62 FR 13464
FDA Data Integrity and Compliance with CGMP: Guidance for Industry
2.6 GAMP:HL7 Standards:
GAMP 5Health Level Seven Standards Good Automated Manufacturing Practice (GAMP) Guide for Validation of Automated
Systems in Pharmaceutical Manufacture, ISPE, 2008
2.7 ICH Standard:
ICH Quality Guideline Q9 Quality Risk Management
2.8 IEEE Standards:
IEEE 829 1998 IEEE Standard for Software Test Documentation
IEEE 830 1998 IEEE Recommended Practice for Software Requirements Specifications
IEEE 1008 1987 IEEE Standard for Software Unit Testing
IEEE 1012 2004 IEEE Standard for Software System, Software, and Hardware Verification and Validation
IEEE 1028 1997 IEEE Standard for Software Reviews and Audits
IEEE 1063 2001 IEEE Standard for Software User Documentation
2.9 ISA Standard:
ANSI/ISA-95.00.06 Enterprise-Control System Integration--Part 6: Messaging Service Model
For referenced ASTM standards, visit the ASTM website, www.astm.org, or contact ASTM Customer Service at [e-mail]. For Annual Book of ASTM Standards
volume information, refer to the standard’sstandard’s Document Summary page on the ASTM website.
The last approved version of this historical standard is referenced on www.astm.org.
Available from Clinical Data Interchange Standards Consortium (CDISC), 401 West 15th Street, Suite 800, Austin, TX 78701, https://www.cdisc.org/.
The CIDX Chem eStandards are available at OAGi, P.O. Box 4897, Marietta, GA 30061-4897, http://www.oagi.org/.
Available from United States Environmental Protection Agency (EPA), 1200 Pennsylvania Ave., NW, Washington, DC 20460, http://www.epa.gov.http://www.epa.gov/.
Available from U.S. Food and Drug Administration (FDA), 10903 New Hampshire Ave., Silver Spring, MD 20993-0002,20993, http://www.fda.gov.
Registered trademark of and available from Health Level Seven (HL7) International, 3300 Washtenaw Avenue, Suite 227, Ann Arbor, MI 48104, http://www.hl7.org/.
Available from International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH), ICH Secretariat, 9,
chemin des Mines, P.O. Box 195, 1211 Geneva 20, Switzerland, http://www.ich.org.
Available from Institute of Electrical and Electronics Engineers, Inc. (IEEE), 445 Hoes Ln., Piscataway, NJ 08854-4141, http://www.ieee.org.
Available from The International Society of Automation (ISA), 67 T. W. Alexander Drive, P. O. Box 12277, Research Triangle Park, NC 27709, http://www.isa.org.
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2.10 ISO Standards:
ISO/IECISO/IEC/IEEE 12207 Information technology—Software Systems and software engineering -- Software life cycle
processes
ISO/IEC 27000 Information technology -- Security techniques -- Information security management systems -- Overview and
vocabulary
ISO/HL7 27932:200927932 Data Exchange Standards—HL7 Standards -- HL7 Clinical Document Architecture, Release 2
ISO/IEEE 11073-10101 Health informatics -- Point-of-care medical device communication -- Part 10101: Nomenclature
ISO/IEC/IEEE 26511 Systems and software engineering -- Requirements for managers of user documentation
ISO/IEC/IEEE 26512 Systems and software engineering -- Requirements for acquirers and suppliers of information
ISO/IEC/IEEE 29119-4 Systems and software engineering -- Software testing -- Part 4: Test techniques
ISO/IEC/IEEE 29119-5 Systems and software engineering -- Software testing -- Part 5: Keyword-Driven Testing
ISO/IEC/IEEE 29148 Systems and software engineering -- Life cycle processes -- Requirements engineering
2.11 ISPE GAMP Guides:
ISPE GAMP 5: A Risk-based Approach to Compliant GxP Computerized Systems
ISPE GAMP Guide: Records & Data Integrity
2.12 MHRA Standard:
MHRA GxP Data Integrity Definitions and Guidance for Industry
2.13 NCPDP Standard:
Batch Transaction Format
2.14 NIST Standard:
NIST Cybersecurity Framework
2.15 NRC Standards:
FDA CFR Part 21 10 Code of Federal Regulations (CFR) Part 21.42 FR 28893, June 6, 1977
FDA10 CFR Part 50, Appendix B 10to Part 50 Code of Federal Regulations (CFR) Part 50 Appendix B. 35 FR 10499, June 27,
1970, as amended at 36 FR 18301, Sept. 11, 1971; 40 FR 3210D, Quality Assurance Criteria for Nuclear Power Plants and
Fuel Reprocessing Plants, 72 FR 49505Jan. 20, 1975
FDA10 CFR Part 50, Appendix E 10to Part 50 Code of Federal Regulations (CFR) Part 50 Appendix E. 45 FR 55410,
Emergency Planning and Preparedness for Production and Utilization Facilities, 80 FR 74980Aug. 19, 1980, et sequentia as
amended
FDA10 CFR Part 50, Appendix K 10to Part 50 Code of Federal Regulations (CFR) Part 50 Appendix K. 21 FR 355, ECCS
Evaluation Models, 65 FR 34921Jan. 19, 1956, unless otherwise noted
2.16 PIC/S Standard:
PIC/S Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
2.17 Regenstrief Institute Standard:
LOINC Logical Observation Identifiers Names and Codes
2.18 SNOMED International Standard:
SNOMED-CT Systematized Nomenclature of Medicine-Clinical Terms
2.19 WHO Standard:
WHO Technical Report Series, No. 996, Annex 5 Guidance on good data and record management practices
Available from International Organization for Standardization (ISO), ISO Central Secretariat, BIBC II, Chemin de Blandonnet 8, CP 401, 1214 Vernier, Geneva,
Switzerland, http://www.iso.org.
Registered trademark of and available from International Society for Pharmaceutical Engineering (ISPE), 600 N. Westshore Blvd., Suite 900, Tampa, FL 33609,
http://www.ispe.org.
Available from International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH), ICH Secretariat, c/o
IFPMA, 15 ch. Louis-Dunant, P.O. Box 195, 1211 Geneva 20, Switzerland, http://www.ich.org.Medicines and Healthcare products Regulatory Agency, Her Majesty’s
Government, 10 South Colonnade, London E14 4PU, United Kingdom, https://www.gov.uk/.
Available from Institute of Electrical and Electronics Engineers, Inc. (IEEE), 445 Hoes Ln., Piscataway, NJ 08854, http://www.ieee.org.National Council for Prescription
Drug Programs (NCPDP), 9240 East Raintree Drive, Scottsdale, AZ 85260-7518, https://www.ncpdp.org/.
Available from International Organization for Standardization (ISO), 1, ch. de la Voie-Creuse, CP 56, CH-1211 Geneva 20, Switzerland, http://www.iso.org.National
Institute of Standards and Technology (NIST), 100 Bureau Dr., Stop 1070, Gaithersburg, MD 20899-1070, http://www.nist.gov.
Available from U. S. Nuclear Regulatory Commission (NRC), One White Flint North, 11555 Rockville Pk., Rockville, MD 20852-2738,20852, http://www.nrc.gov.
For additional information, visit http://www.fda.gov/ICECI/Inspections/InspectionGuides/ucm170612.htm#page1.
For additional information, visit http://www.captodayonline.com/productguides/software-systems.html
Available from International Society of Automation (ISA), 67 Alexander Drive, Research Triangle Park, NC 27709, http://www.isa.orgPIC/S Secretariat, 14 rue du
Roveray CH, 1207 Geneva, Switzerland, https://picscheme.org/.
Health Level Seven International is an ANSI-accredited standards developing organization dedicated to providing a comprehensive framework and related standards for
the exchange, integration, sharing, and retrieval of electronic health information that supports clinical practice and the management, delivery and evaluation of health services.
Additional information available from Health Level Seven International (HL7), 3300 Washtenaw Avenue, Suite 227 Ann Arbor, MI 48104, http://www.hl7.org/.
Registered trademark of and available from The Regenstrief Institute, Inc, 410 West 10th Street, Suite 2000, Indianapolis, IN 46202-3012, http://loinc.orghttp://loinc.org.
Available from SNOMED International, One Kingdom St., Paddington Central, London W2 6BD, United Kingdom, https://www.snomed.org/.
Available from World Health Organization (WHO), Avenue Appia 20, 1202 Geneva, Switzerland, http://www.who.int.
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3. Terminology
3.1 This guide defines the majority of different terminology used in the laboratory informatics tools field. Users of this guide
should request a terminology list from each vendor with a cross reference to the terms used in this guide.
3.1 Definitions—This guide defines the majority of terminology used in the field of laboratory informatics. Users of this guide
should request a terminology list from each vendor with a cross reference to the terms used in this guide.
3.2 Definitions of Terms Specific to This Standard:
3.2.1 artificial intelligence, AI, n—behavior by machines or computers versus the natural intelligence of humans and animals.
3.2.1.1 Discussion—
In the computer science arena, any device that perceives its environment and takes action to maximize success in achieving a goal
is exhibiting AI. Machine learning is an application of artificial intelligence that provides systems the ability to automatically learn
and improve from experience without being explicitly programmed.
3.2.2 chromatography data system, CDS, n—computer system used to acquire, analyze, store, and report information from
chromatographs.chromatographic instruments.
3.2.3 cloud computing, v—term generally used to refer to software applications that are delivered as a software service through
remote hosting using the public internet (public cloud) or within the users’ network environment (private cloud).
3.2.3.1 Discussion—
Essentially, the difference between cloud computing and a traditional application deployment is that the applicationapplication’s
users aremay not be responsible for the installation and maintenance of the computing infrastructure and application software.
3.2.4 corrective and preventative action, CAPA, n—CAPA applications are used to collect information, analyze information,
identify and investigate product and quality problems, and take appropriate and effective corrective or preventive or both(or both)
action to prevent their recurrence.
3.2.4.1 Discussion—
Verifying or validating corrective and preventive actions, communicating corrective and preventive action activities to responsible
people, providing relevant information for management review, and documenting these activities are essential in dealing effectively
with product and quality problems, preventing their recurrence, and preventing or minimizing device failures.
3.2.5 cybersecurity, n—set of technologies, practices, and processes used to protect computers, networks, programs, and data
from attack, damage, exploitation, and unauthorized access.
3.2.6 data exchange standardization, n—as defined by the International Organization for Standardization (ISO) in ISO/HL7
27932, the process of agreeing on standards, which represent the common language that allows the exchange of data between
disparate data systems.
3.2.6.1 Discussion—
The goals of standardization are to achieve comparability, compatibility, and interoperability between independent systems, to
ensure compatibility of data for comparative statistical purposes, and to reduce duplication of effort and redundancies. A data
standard often includes data elements, data element definitions, and such agreements as formats, message structures, and
vocabulary. In the context of this paper, a standard is a specification or requirement and is not synonymous with a policy,
procedure, guideline, framework, technique, or best practice. Adopting standards has the potential to improve interoperability and
reduce costs by facilitating the ability of networked laboratories to coordinate activities during public health incidents where surge
capacity may be required (for example, national response and readiness). Adopting standards may reduce the costs of LIMS
laboratory informatics system implementation and vendor/developer support.
3.2.7 data integrity, n—extent to which data are attributable, complete, consistent, accurate, and reliable throughout the data life
cycle.
3.2.8 electronic document management system, EDMS, n—computer system used to store, catalog catalog, review/approve,
retrieve, view, and print digital documents.
For additional information, visit the FDA’s CAPA page at http://www.fda.gov/.
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3.2.8.1 Discussion—
Modern EDMS applications typically provide the ability to manage a document throughout its lifecycle with functions life cycle,
including document initiation, multiple levels of review, version controls, security and archivereview levels, version control,
security, and archiving of historical versions of documents.
3.2.9 electronic laboratory notebook, ELN, n—software program designed to replace paper laboratory notebooks. Defined by
CENSA (Collaborative Electronic Notebook Systems Association) as “a system notebooks; an electronic system on which to
create, store, retrieve, and share fully electronic records in ways that meet all legal, regulatory, technical, and scientific
requirements.”requirements.
3.2.9.1 Discussion—
Laboratory notebooks, in general, are used by scientists, engineers, and technicians to document research, experiments, and
procedures performed in a laboratory. A laboratory notebook is often maintained to be a legal document and may be used in a court
of law as evidence. Similar to an inventor’sinventor’s notebook, the laboratory notebook is also often referred to in patent
prosecution and intellectual property litigation.
3.2.10 electronic signature, n—electronic representation of a handwritten signature.
3.2.11 enterprise resource planning, ERP, n—ERPcomputer system integrates to integrate different types of data such as
inventory levels, product orders, accounting, manufacturing capacity, inspection results, accounting data, and customer relationship
management information from organizations within an enterprise (company) to facilitate (company), facilitating the flow of
information between various business functions across a company as well as with outside business partners.
3.2.12 good automated manufacturing practice forum, GAMP Forum, n—a volunteer group under the auspices of the
International Society of Pharmaceutical Engineering (ISPE) for writing guidance for the validation of computerized systems used
in the regulated portions of the pharmaceutical and allied industries. It industries and it is specifically designed to aid suppliers and
users in the pharmaceutical industry.
3.2.13 integration broker, n—messaging application that can receive or extract data from a source system at the appropriate
time, transform the data, and route the reformatted data to the target node.
3.2.13.1 Discussion—
An integration broker application can also provide a repository for archiving, searching, and retrieving these messages.
3.2.14 laboratory information system, LIS,internet of things, IoT, n—class of application software that supports clinical
laboratories by helping technologists manage the quality and integrity of test samples; departmental workflow functions, result
review processes, reporting of finalized results, interpretations, and diagnosis.system of objects—computing devices, machines,
objects, people, animals, and so forth—that can connect to a network and communicate among themselves, often without human
intervention.
3.2.14.1 Discussion—
These systems often interface with instruments and other information systems such as hospital information systems (HIS). A LIS
is a highly configurable application and often includes laboratory-specific electronic medical records; direct clinician access via
secure web connections; billing modules for laboratories performing commercial testing; sophisticated interface engines for
routing orders and results to external systems; and on-board image archival systems for pathology images. Patient confidentiality
and HIPAA requirements define unique security functionality for a LIS. The College of American Pathologists (CAP) publishes
LIS product guidesAn IoT device is an object operating within that list current LIS in the market.system.
3.2.15 laboratory execution system, LES, n—computer system used in the laboratory at the analyst work level to aid in step
enforcement for laboratory test method execution.
3.2.15.1 Discussion—
Laboratory execution systems (LES) LES focus on step execution of defined laboratory test methods. The LES areis typically used
in quality control laboratories that have defined test methods. The functionality of LES and LIMS overlap a LES and a laboratory
information management system (LIMS) overlaps in the areas of result entry, instrument integration, and specification flagging.
Deployment options include LES and LIMS systems deployed as an integrated solution, LIMS only or LES only LIMS-only, or
LES-only (for limited functions).
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3.2.16 laboratory informatics, n—term used to describe the specialized application of information technology aimed at
optimizing laboratory operations and it is a collection of informatics tools utilized within laboratory environments to collect, store,
process, analyze, report, and archive data and information from the laboratory and supporting processes.operations.
3.2.16.1 Discussion—
That technology includes informatics tools used within laboratory environments to collect, store, process, analyze, report, and
archive data and information from the laboratory and supporting processes. Laboratory informatics includes the integration of
effective use of critical data management systems, the electronic delivery of results to customers, and the use and integration of
supporting systems including (for example, training and policies. policy management). Examples of laboratory informatics
include: Laboratory Information Management Systems (LIMS), Electronic Laboratory Notebooks (ELNs), Chromatography Data
Systems (CDS) and Scientific Data Management Systemsprimary laboratory informatics tools include, LIMS, LES, CDS, ELN,
laboratory information systems (LIS), and scientific data management systems (SDMS).
3.2.17 laboratory informatics tools configuration, n—refers to the process of changing the functions of any of the laboratory
informatics toolstool to match the business processprocesses used in a particular laboratory. It laboratory, and it does not involve
the use of writing software code either via a recognized software language or a language provided by the informatics application
supplier. This is a GAMP 4 software category.
3.2.17.1 Discussion—
It This is a GAMP Category 4 software and is defined as “Configured software including, LIMS, SCADA, DCS, CDS, etc.” Such
configuration typically involves using an interface provided by the vendor to enter information that describes the types of samples,
analytical methods, specifications, and so forth, used in the laboratory. It may also involve the configuration of options and
businesses rules within the tool.
3.2.18 laboratory informatics tools customization, n—refers to the process of changing the functions of any of the laboratory
informatics toolstool to match the business processprocesses used in a particular laboratory. It involves the writing software code
either via a recognized software language or a language provided by the informatics application supplier. This is a GAMP 5
software category.
3.2.18.1 Discussion—
It This is different from the previously mentioned tools configuration in that customization involves writing software code either
via a recognized software language or a language provided by the informatics application supplier. This is a GAMP 5 software
category. Such customization typically involves adding tables, modifying table structures, and writing code or programs to alter
the behavior of any of the laboratory informatics tools.tool.
3.2.19 laboratory information management system, LIMS, n—(1) computer application(s) software and hardware that can
acquire, analyze, report, and manage data and information in the laboratory; (2) computer software that is used in the laboratory
for the management of samples, test results, laboratory users, instruments, standards, and other laboratory functions such as
invoicing, plate management, product/material stability programs, and work flow automation; and (3) a class of application
software which handles storing and managing of information generated by laboratory processes.
3.2.19.1 Discussion—
These systems are used to manage laboratory processes, including defining master data, data definition, sample management and
chain of custody, work assignment, instrument and equipment management, standard and reagent management, scheduled sample
collection and testing, result entry, capture of results from instruments, result review, reporting, trending, and business rule
enforcement. These systems interface with laboratory instruments (for example, chromatography data systems (CDS), CDS and
other information systems such enterprise resource planning (ERP),as ERP, LIS, or manufacturing execution systems (MES), or
health care based laboratory information systems (LIS)). [MES]). A LIMS is a highly flexible application, which can be configured
or customized to facilitate a wide variety of laboratory workflow models.
3.2.20 laboratory information system, LIS, n—class of application software that supports clinical laboratories by helping
laboratory personnel manage the quality and integrity of test samples, departmental workflow functions, result review processes,
reports of finalized results, interpretations, and diagnoses.
3.2.20.1 Discussion—
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These systems often interface with instruments and other information systems such as hospital information systems (HIS). A LIS
is a highly configurable application and often includes laboratory-specific electronic medical records, direct clinician access via
secure web connections, billing modules for laboratories performing commercial testing, sophisticated interface engines for routing
orders and results to external systems, and on-board image archival systems for pathology images. Patient confidentiality and
HIPAA requirements define unique security functionality for a LIS. The College of American Pathologists (CAP) publishes LIS
product guides that list current LIS in the market.
3.2.21 lean laboratory, n—set of management and organizational processes derived from lean manufacturing and the Toyota
Production System (TPS) and the goal of a lean laboratory is to use less effort, fewer resources, and less time to test incoming
samples.that enables efficient testing flow, leveled workloads, visual work assignment and tracking, and the elimination of waste.
3.2.21.1 Discussion—
Lean laboratory designs yield productive, high-quality laboratory environments that are sometimes supported by laboratory
informatics tools.
3.2.22 mapping tools, n—graphical data mapping, conversion, and integration applications that map data between any
combination of XML, database, flat file, EDI, Excel (OOXML), XBRL, and/oror web service, or both, then transforms data or
autogenerates data integration code for the execution of recurrent conversions.
3.2.23 master data, n—represents the business objects which are agreed on and shared across the enterprise.
3.2.23.1 Discussion—
It can include relatively static reference, transactional, unstructured, analytical, and hierarchical data, as well as associated
metadata. Examples of master data include product specifications, test method steps (to capture intermediate and final results),
laboratory calculations, instrument information, and standard and reagent information.
3.2.24 metadata, n—(1) data about data and (2) information that describes another set of data.
3.2.24.1 Discussion—
Additional information about the data that provides context and meaning, including how, when, and by whom it was collected, and
its relationship to the subject or test. Metadata in any laboratory informatics toolstool’s context typically includes all data that
supports a test result that is recorded in this tool. Examples include for For example, a pH test, test includes a pH result that can
be supported by metadata, including what instrument was used, what is the calibration date of the instrument, instrument was, what
standard buffer solutions (reagents) were used to calibrate the pH probe sensor, the expiration dates for the standard solutions, and
the temperature of the solution at time of measurement.
3.2.25 sample registration, n—process of recording incoming sample information in a given laboratory informatics tool.
3.2.26 scientific data management system, SDMS, n—computer system used to capture, centrally store, catalog, and manage
data generated in a laboratory environment.
3.2.26.1 Discussion—
These data are then available for re-use and integration with other laboratory informatics systems. An example of an SDMS is an
electronic repository for reports from laboratory informatics systems. The SDMS may include raw data file storage and archiving
of data. It may also provide e-signature functionality for review/approval.
3.2.27 spectroscopic data systems, n—computer systems used to collect, process, visualize, interpret, store, and report
information from spectroscopic instruments.
4. Significance and Use
4.1 Relevance—This guide is intended to educate those in the intended audience on many aspects of laboratory informatics.
Specifically, the guide may:
4.1.1 Help educate new users of laboratory informatics;
4.1.2 Help educate general audiences in laboratories and other organizations that use laboratory informatics;
4.1.3 Help educate instrument manufactures and producers of other commonly interfaced systems;
4.1.4 Provide standard terminology that can be used by laboratory informatics vendors and end users;
For additional information, visit CAP’s product guide page at http://www.captodayonline.com.
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4.1.5 Establish a minimum set of requirements for primary laboratory informatics functions;
4.1.6 Provide guidance on the tasks performed and documentation created in the specification, evaluation, cost justification,
implementation, project management, training, and documentation of laboratory informatics; and
4.1.7 Provide high-level guidance for the integration of laboratory informatics.informatics and other software tools.
4.2 How to be Used—This guide is intended to be used by all stakeholders involved in any aspect of laboratory informatics
implementation, use, or maintenance.
4.2.1 It is intended to be used throughout the laboratory informatics life cycle by individuals or groups responsible for
laboratory informatics implementation and use, including specification, build/configuration, validation, use, upgrades, and
retirement/decommissioning.
4.2.2 It is also intended to provide This guide also provides an example of a laboratory informatics functions checklist.func-
tional requirements checklist that can be used to guide the purchase, upgrade, or development of a laboratory informatics system.
5. Laboratory Informatics Concept Model—Graphic Picture of Systems and Functionality Elements of Laboratory
Informatics
5.1 Laboratory Informatics Elements Overview—Laboratory informatics is used to help laboratory personnel better collect,
process, analyze, report, store, and share the data and information derived from the laboratory and its supporting processes. These
processes are often an integral part of a laboratory’s workflow and include activities such as registration of samples or experiments,
or both, assignment of tests, entry of results, review and approval of results, and reporting. Laboratory informatics’ scope
encompasses multiple technical solutions or systems that are responsible for streamlining these and other laboratory processes.
Laboratory informatics is not solely about software managing laboratory data; it has many elements, some of which integrate or
cross over with business management and other third-party tools. Those elements are also becoming increasingly complex, both
in functionality and interoperability. Outside of standard laboratory information management systems (LIMS) and laboratory
information systems (LIS), elements such as field data capture systems, advanced analytics tools, and artificial intelligence
continue to shape the field of laboratory informatics. The division between these and other system categories continues to soften
as functionality continues to be added to each of them. LIMS were originally created to address laboratories’ need to manage
laboratory operations and data, provide traceability for all laboratory samples and equipment, and ensure that laboratory procedures
are followed. Electronic laboratory notebooks (ELNs), on the other hand, were originally created to meet scientists’ need to
document their experimental design, execution, and conclusion in an electronic format instead of in a paper notebook. The
scientific data management system (SDMS) was created to provide a repository of all scientific data files and results regardless of
instrument type. The current definitions of each of these system categories are far more encompassing and continue to evolve as
the boundaries between categories continue to blur. That blurring of laboratory informatics elements, as well as their potential
integration with enterprise elements—both within organizations and with customers of laboratory information—are illustrated in
Fig. 1. Laboratory informatics and all it encompasses is shown with the large yellow circle on the left, while the internal business
systems that support laboratories are found associated with the blue circle on the right. Surrounding both is a bubble representing
third-party interactions with both laboratory generated data and business data. The figure highlights the wide variety of crossover
and interactions that can occur both within and external to laboratory informatics. Laboratory informatics applications are also
taking on some of the functionality of internal business systems. (See 7.6–7.11 for more information on integration cases.)
5.1.1 Core Systems—These laboratory systems most often provide the outward face of laboratory informatics and include LIMS,
LIS, laboratory execution systems (LES), ELN, SDMS, and chromatography data systems (CDS). Not all systems will necessarily
appear in a laboratory together; some are more typical to certain laboratory types than others. However, they usually play a key
role in a laboratory’s research or analysis activities, or both, and represent the key software systems with which laboratory
personnel and customers of the laboratory may interact. From research samples and clinical specimens to outlined experiments and
raw instrument data, these core systems fill a vital role in the laboratory informatics sphere.
5.1.1.1 LIMS, LIS, and LES are alike in many regards in that they all act as core systems in a laboratory and handle data capture,
analysis, review, storage, and reporting. These systems integrate in variable degrees with analytical instruments, automated tools,
and other software systems, and they provide certain levels of regulated, industry-standard security for the data generated and
transferred from its integrations. However, these systems also have fundamental differences that place them in specific use cases.
A LIMS has been traditionally used to process and report on batches of samples from research, quality control, and manufacturing
laboratories, all of which handle mostly anonymous, complex laboratory data. A LIS has normally been used in the clinical context
of specimens and patients, and a LES is most often adopted in automated and regulated manufacturing environments where quality
control, process control, test step execution, and instrument interface and calculation validation support laboratory testing.
5.1.1.2 An ELN largely serves as an electronic replacement for the traditional paper laboratory notebook associated with
scientist
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