mumbai 2011

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!