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An Introduction to SLAS and Laboratory Technology Trends
Steven Hamilton, Ph.D.SLAS Director of Education
Society for Laboratory Automation and Screening
An international community of more than 10,000 individual scientists, engineers, researchers & technologists• Provides forums for education and information exchange to
encourage study and advance laboratory science and technology
• Academic, government and commercial laboratories. • Drug discovery, agrochemical, biotechnology, chemical, clinical
diagnostic, consumer product, energy, food, forensic, security and other industries.
SLAS Conferences & Symposia
Distance Learning
• Virtual Courses• LabAutopedia Wiki• LabMan Blog/Podcast• Standards• Journals on Demand• Reference Material
SLAS Scientific Journals
SLAS member surveys
1 2 3 4 5
4.7Increase productivity
3.8Improve data quality
3.5Reduce operating cost
2.4Improve safety
in the laboratory
Why do you use laboratory automation?
2.8Improve working conditions
in the laboratory
(Low) (High)Rating
2006 slas survey – full data in LabAutopedia
Technology Driven Industries
Organization AgePro
duct
ivity
, C
ompe
titiv
enes
s
Organizational Lifecycle
Technology Driven Industries
Organization AgePro
duct
ivity
, C
ompe
titiv
enes
s
Organizational Lifecycle
Lab Automation in PharmaWhat have we learned?
• The goal is Enterprise Optimization.• Automation can enable good science, not create it.• No single technology or discipline holds the key. • The impact of technology on the balance and flow
of the entire R&D process must be understood, planned and managed.
Horsepower alone does not create good science
The winning companies effectively integrate technology with science using both in-house resources and external partnerships. - Boston Consulting Group Report
PharmacologyPharmacology
Biology
ProteomicsChemistry
GenomicsPharmaEnterprise
Bio-chemistry
MolecularBiology
How Do We Automate Science?
2006
1998
2003
Lab Automation Sources
Customized
26%53% 47%
46%54%
49%51%
Off The Shelf
We find that science automation is highly customized
How Do We Automate Science?
Less customization now done in-house
3rd Party Integrator
Off The Shelf
2006
47%
1998
2003
11%
Lab Automation Sources
Vendor Modified
26%
Developed In-House
15%
Customized Solutions
49%4%
25%22%
46%24%20%
9%
How Do We Automate Science?
Yet companies still dedicate resources to lab automation
No:36%
No:25%Yes: 75%
Yes:64%
2006 1998
Companies with internal lab automation resources
How Do We Automate Science?
Yet companies still dedicate resources to lab automation.If more work is being outsourced, why?
No:36%
No:25%Yes: 75%
Yes:64%
2006 1998
• Outsourced projects still require internal expertise, but different focus• Lab Automation has spread more widely across companies
• Requires more on-going support
Success of lab automation?
My organizations senior management feels it’s investment in laboratory automation has:
56% Succeeded in delivering the expected result
56% Succeeded in delivering the expected result
43% Produced
mixed results
43% Produced
mixed results
Not delivered the expected result
1%
Success of lab automation?
My organizations senior management feels it’s investment in laboratory automation has:
56% Succeeded in delivering the expected result
56% Succeeded in delivering the expected result
43% Produced
mixed results
43% Produced
mixed results
Not delivered the expected result
1%
62% had internalautomation resources
62% had internalautomation resources
39% had internalautomation resources
39% had internalautomation resources
The Laboratory Automation Expert?
Key to success
• Few formal degree programs provide this interdisciplinary background
• Most have formal degrees in Chemistry, Biology, Engineering or Computer Science
• Important skills– Understanding of relevant areas of
science– Programming– Engineering– Project management– Leadership, business
Scientist
MechanicalEngineer
Software Engineer
FluidicsExpert
ElectricalEngineer
ProjectManager
Risk-Taking with Technology?
Internal resources matter
Technology Entry PointWith
internal resources
Without internal
resources
Bleeding edge: technology showing high potential, but yet to demonstrate value or practicality.
7% 5%
Leading edge: technology proven in marketplace but few knowledgeable personnel to implement or support it.
67% 44%
State of the Art: when everyone agrees that a particular technology is the right solution.
26% 51%
Technology Entry PointWith
internal resources
Without internal
resources
Bleeding edge: technology showing high potential, but yet to demonstrate value or practicality.
7% 5%
Leading edge: technology proven in marketplace but few knowledgeable personnel to implement or support it.
67% 44%
State of the Art: when everyone agrees that a particular technology is the right solution.
26% 51%
Technology Entry PointWith
internal resources
Without internal
resources
Bleeding edge: technology showing high potential, but yet to demonstrate value or practicality.
7% 5%
Leading edge: technology proven in marketplace but few knowledgeable personnel to implement or support it.
67% 44%
State of the Art: when everyone agrees that a particular technology is the right solution.
26% 51%
What Limits our use of Lab Automation Today?
2.3
2.5
2.5
2.6
2.7
2.7
2.8
3
3.3
3.3
0 0.5 1 1.5 2 2.5 3 3.5
Automation System Throughput
Forced downtime (broken)
Ease of operating automation
Vendor support
Data management
Data evaluation/computation
Up and downstream infrastructure
Time to reconfigure for new process
Time to develop assays/procedures
Time to validate process on automation
Limiting Factors: 1=Low; 5=High
2.3
2.5
2.5
2.6
2.7
2.7
2.8
3
3.3
3.3
0 0.5 1 1.5 2 2.5 3 3.5
Automation System Throughput
Forced downtime (broken)
Ease of operating automation
Vendor support
Data management
Data evaluation/computation
Up and downstream infrastructure
Time to reconfigure for new process
Time to develop assays/procedures
Time to validate process on automation
Limiting Factors: 1=Low; 5=High
2.3
2.5
2.5
2.6
2.7
2.7
2.8
3
3.3
3.3
0 0.5 1 1.5 2 2.5 3 3.5
Automation System Throughput
Forced downtime (broken)
Ease of operating automation
Vendor support
Data management
Data evaluation/computation
Up and downstream infrastructure
Time to reconfigure for new process
Time to develop assays/procedures
Time to validate process on automation
Limiting Factors: 1=Low; 5=High
Requires internal
automation /science
resources
No longer the
limiting factors
How to Succeed with Laboratory Automation?
Navigate the delicate waters of change by joining SLAS and by employing SLAS members!