Laboratory Integration John Trigg

Overcoming the Challenges Facing Laboratory Integration
John Trigg
phaseFour Informatics Limited
www.phasefour-informatics.com
www.theintegratedlab.com

The e-Laboratory vs the i-Laboratory
The electronic or paperless laboratory
Application-centric
A jigsaw puzzle – a case of trying to make the pieces fit
Hampered by lack of standards
Dependent on custom solutions
The integrated laboratory
Modular
Content separated from the application
Based on data interchange standards
Based on communication standards
Products able to work together

Laboratory Integration Objectives
Smoother, easier workflows
Less manual effort
Avoiding duplication of data entry
Easier compliance
Easier to validate and maintain
Error reduction
Reduced cost of development and support
Eliminate custom interfaces
Improved efficiencies
Better data management
Easier access to data/information
More flexibility
Easier to upgrade/change
Ref: The Integration of Laboratory Systems, Institute for Laboratory Information, 2010

Changing business models, driven by technology
Analogue  Digital
Music
Film
Television
Physical media  Electronic
Photography
Newspapers/Magazines
Books
Pareto  Long Tail (markets of millions -> millions of markets)
Amazon
eBay
iTunes

Analogue vs. digital photography
Upload
Email
MMS

Why is digital photography different/better?
Easier to take, evaluate and edit photos
Point & shoot
Instant results - no need to send films away to be processed
Doesn ’ t need to involve 3 rd parties to reprint photos
Metadata automatically assigned
Easier to store and search images
No need for shoeboxes, wallets and photo-albums
Long term storage and archiving needs to be addressed
Easier to share
Photo-sharing sites
Social network sites
MMS messaging
Email
Applies to personal, social and business use.
And we don’t really need to worry about image formats and connectivity.

A generic laboratory data ‘ architecture ’
The triangle represents the different layers of abstraction that exist in R&D information flows. These are almost always handled by different systems.
Above the experimental layer is often management context, and is handled by traditional IT tools used elsewhere in the enterprise.
Cross discipline collaboration tends to happen around experiment (or reports summarising experiments). Anything more detailed than the experiment requires specific expertise and tools to interpret.
Below the experiment level there is an increasing specialisation of data types and tools, and only a few systems are comfortably deployed across workgroups.
INFORMATION DATA KNOWLEDGE

Laboratory ‘ architecture ’ Activity Format Application Programme/ Study Document Enterprise tools (Doc. Mgt.) Project Document/ Files Desktop tools (MS Office) Experiment Notebook Q/A Chemistry Biology Sample Structured data/files LIMS SDMS Chemistry tools Structures Reactions Registration Biology tools (Excel?) Databases Test Raw/ Processed data Lab Automation

Current business drivers in the laboratory
Productivity and business efficiency
Compliance; regulatory, legal, internal, H&S
IP protection, security
Knowledge management
Changing scientific goals
Increasingly biology-centric
Increasing complexity
Multi-disciplinary
More and more data
Increasing accountability (health/environment)

What are the barriers to an integrated lab ?
Lack of:
Data interchange standards
Laboratory communication standards
Common language/terminology
Short termism
The current economic climate and short term tactical requirements do not encourage long term investment
We don’t have a guardian angel
No industry association, that represents user communities, to drive the development and adoption of integration standards
Lack of community action
No self-forming communities to tackle common problems
No (not enough?) pressure on vendors
But, there are signs of community interest in discussion and sharing opinion in the LinkedIn groups, but no call to action.

What might save us?
Vendor response (single vendor vs. best of breed)
Industry (vendors + user community) collaboration
An organised body (The Pistoia Alliance?)
Community action
See :
Tribes, Seth Godin,Piatkus Books, 2008
Here Comes Everybody, Clay Shirky, AllenLane/Penguin Books, 2008
Technology
Electronic Records Management (documents)
Need for reliability, authenticity, integrity, usability
Document standards (PDF, PDF/A, ODF, OOXML)
Data Standards
JCAMP-DX, ANDI, AnIML
Need for agreed terminology, common laboratory language
Web services/XML?

What is necessary for data standards to evolve?
“… inefficient practices have become deeply ingrained by a highly risk averse and legalistic corporate culture, often at the expense of opportunities to co-develop early-stage technology tools, establish data standards, share disease target information, or pursue other forms of collaboration that could lift the productivity of the entire industry.”
Macrowikinomics, Don Tapscott & Anthony D.Williams, Atlantic Books, 2010
Collaborative Innovation?
Do we have the energy and inertia to collaboratively evolve a common language and common terminology to facilitate the development of laboratory data standards?
Do we have the energy and inertia to collaboratively encourage vendors to adopt agreed data standards?

Technology Milestones 1980 1990 2000 Microcomputers Minicomputers Proprietary OS MS-DOS Standalone Apps MS-Windows (GUI) ‘ Industry ’ standards DBMS Client-Server Integrated Apps Central Control Central Control User Control 2010 Open Source Distributed Apps Smart phones Tablets Distributed Control ‘ Social’ network Internet Networks

The Five Eras of the Social Web:
Era of Social Relationships: People connect to others and share
Era of Social Functionality: Social networks become like operating systems
Era of Social Colonisation: Every experience can now be social
Era of Social Context: Personalised and accurate content
Era of Social Commerce: Communities define future products and services
Ref: Post by Jeremiah Owyang on Web Strategy
http://www.web-strategist.com/blog/2009/04/27/future-of-the-social-web/

Skills and Culture
The laboratory is a knowledge ecosystem
Technology plays an increasing tactical and strategic role in scientific discovery and other laboratory processes
Innovation is becoming an ‘industrial’ and global process
How many lab workers receive formal training in laboratory automation and laboratory integration?
How capable and well equipped are users to understand and use technology?
Technology Processes People

Lab Managers Survey: Lab Staff Qualifications for Modern Laboratories
Q: Applicants for positions have well qualified backgrounds in lab automation tools and technologies.
Joe Liscouski, Institute for Laboratory Automation, April 2011 http://www.institutelabauto.org/research/LMSurvey.html

Conclusions
In order to meet laboratory integration goals,
We need a non-competitive process in which we, as a community can collaborate with solution providers to achieve common goals, free of politics and commercial interests, and which places the advancement of science at the forefront.
We need to work together to evolve a common basis (language and terminology) for data interchange standards to be developed, and to encourage their adoption.
We need to collaborate with higher education establishments to encourage programmes designed to address the technology and process understanding needs of modern industrial science.

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Laboratory Integration John Trigg

by John Trigg on Nov 18, 2011

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