Pre-Analytical Automation Systems Robin A. Felder, Ph.D. Director, Medical Automation Research Center Professor of Pathology The University of Virginia © College of American Pathologists 2004. Materials are used with the permission of Robin Felder, PhD.
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Pre-Analytical Automation Systems
Robin A. Felder, Ph.D.Director, Medical Automation Research Center
Professor of PathologyThe University of Virginia
© College of American Pathologists 2004. Materials are used with the permission of Robin Felder, PhD.
Improving healthcare quality and efficiency through the development of advanced
technologies
Medical Automation Research Center
http://marc.med.virginia.edu
The Hospital/Laboratory Partnership
• Improving physician efficiency and efficacy by providing rapid definitive diagnostic data– Electronic medical records, minimally invasive
Point-of-Care diagnostics, efficient sample collection, labeling, and transportation
• Improving overall hospital efficiency– Resource tracking, schedule optimization,
inventory control, skill level assessment and training, process control
• Allowing patients to self diagnose– Internet health portals, home diagnostics
• Creating a partnership between the lab and the physician
Course Objectives
• Describe pre-analytical and analytical molecular diagnostic automation
• Show actual performance data on some of these systems
Small Laboratory Issues
• Smaller laboratories have had few options to improve their competitiveness against larger reference laboratories
• Improve competitiveness– Better service (faster turnaround time,
improved consults, better patient education, fewer errors)
– Reduced costs (eliminate send out costs, reduce labor, reduce tube diversity, reduce inefficient arrival patterns)
Tube Diversity
Specimen Arrival RatesArrival Pattern
0
50
100
150
200
250
300
350
400
450
1 4 7 10 13 16 19 22
Time of Day
Prim
ary
Tube
s / H
our
Arrival Pattern
0
50
100
150
200
250
300
350
400
1 4 7 10 13 16 19 22
Time of DayPr
imar
y Tu
bes
/ Hou
r
Arrival Pattern
0
50
100
150
200
250
300
350
1 4 7 10 13 16 19 22
Time of Day
Prim
ary
Tube
s / H
our
Arrival Pattern
0
100
200
300
400
500
600
700
800
1 4 7 10 13 16 19 22
Time of Day
Prim
ary
Tube
s / H
our
60% Centrifugation30 % 1 Aliquot
70 % Centrifugation20 % 1 Aliquot
60% Centrifugation50% 1 Aliquot
60 % Centrifugation40 % 1 Aliquot
Arrival Pattern
0
10
20
30
40
50
60
70
80
90
100
1 4 7 10 13 16 19 22
Time of Day
Prim
ary
Tube
s / H
our
Arrival Pattern
0
50
100
150
200
250
300
3501 4 7 10 13 16 19 22
Time of Day
Prim
ary
Tube
s / H
our
Arrival Pattern
0
20
40
60
80
100
120
140
160
1 4 7 10 13 16 19 22
Time of Day
Prim
ary
Tube
s / H
our
60% Centrifugation5 % 1 Aliquot
72 % Centrifugation31 % 1 Aliquot
40 % Centrifugation23 % 1 Aliquot
Source: Donna Crook, Tecan, Research Triangle Park, NC, USA
Selection of Automation Based on Test Volume and Versatility
0
1
2
3
Sam
ples
per
Yea
r (M
illio
ns)
Relative Cost
Total LaboratoryAutomation
Workstation
Workcell
Clinical Laboratory Automation
Total LaboratoryAutomation (TLA)
Workcell
Modular LaboratoryAutomation (MLA)
Workstation
Benefits of Pre-Analytical Automation
• Pre-analytical workstations installed worldwide are exceeding customer expectations
• Optimized preparation of high quality samples
• Exceptional use of laboratory space• Significant increases in laboratory
productivity• Predictable return on investment
Standardized AutomationPreanalytical Module
Picture: Courtesy of A&T Corp.
Open LA21 Project
Picture: Courtesy of A&T Corp.
A&T Open LA21 Modular
• Maximizing Analyzer Throughput– Single tube but “high speed” transportation– Buffering Module avoids traffic jam– Efficient distribution of sample – the number of samples
loaded in sampling point will be monitored and controlled
Sample Load/Sample Load/Unload M.Unload M. Buffering M.Buffering M. ImmunoImmuno--a. M.a. M. Chemistry M.Chemistry M.
Conveyor with FeederConveyor with Feeder Universal Connection M.Universal Connection M.
Picture: Courtesy of A&T Corp.
Load/Unload M.Load/Unload M.Buffering M.Buffering M. ImmunoImmuno--a. M.a. M. Chemistry M.Chemistry M.
Conveyor Module with FeederConveyor Module with Feeder Universal Connect. M.Universal Connect. M.
Open LA21
• Random Access for Routine, Emergency and Repeat Testing– All the samples will be dispatched from Buffering Module to the
Analyzer with “random access”– STAT Sample will be fed to Sampling Point with priority– The sample will be kept in Buffering Module for Retesting
Picture: Courtesy of A&T Corp.
Pre-analytical Workstations
Front End ProcessorPyxis
Power ProcessorBeckman Coulter
Brea, CA
MODULAR Preanalytics,Roche Diagnostics, Indianapolis, IN
GENESIS FE500Abbott/Tecan, North Chicago, IL/Durham, NC
PathfinderAi-Scientific,ScarboroughAustralia
Bayer
• Single point connections for power, modem, network,water, and waste
• LabCell information system–ADVIA CentraLink®
–Process Control–Auto verification
ADVIA® LabCell®Bayer Healthcare (Tarrytown, NY)
noIn developmentyes600/module11.5x75-
16.2x100BayerADVIA, Lab Cell
yes
yes
no
yes
no
Recapping
ULyes200 – 425(300 if
aliquotting)
13x75-16x100
Lab-InterlinkFront-end Processor
5yes60013x75-16x100
RocheMODULAR
ULno30013x75-16x100
Ai-ScientificPathfinder
6yes30013x75-16x100
Beckman CoulterPower Processor
ULyes288 – 332,(8 -10 min spins)
13x75-16x100
Abbott/TecanFE 500
AliquotsCentrifugationThroughputPrimary/max
output/hr
Tube requirementsPre-analytical
Processors
UL = unlimited
Time to 1st Tube
20 secondsno centrifugation
15 seconds, no centrifugation
NA6 secondsPathfinder
11 min,1 sec
10 min, 55 sec
10 min,30 secCent (10 min,24 sec)
6 secFront End Processor
17 min, 40 sec
17 min, 32 sec
15 min,Cent (8 min)
52 secondsFE 500
Time to 1st
Tube, Cent + 2 Aliquots
Time to 1st
Tube, Cent + 1 Aliquot
Time to 1st
Tube w CentTime to 1st
Tube woCentrifugation
Tecan GENESIS FE500
Case Study 1: Clinical Trial FE500
• 4000 specimens over a period of 3 months
• Input rate from 40 to 300 tubes per hour
• Aliquots from 1 to 5• We measured
– throughput– error rate reduction– centrifuge efficiency– Labor savings
AliquotingStation
GENESIS FE 500 Layout
Specimen Input
Specimen OutputCentrifugation
Positive Specimen ID
Tube Loading
Installation
Site Preparation
System Fine TuningAnd Training
Delivering, Installation,Testing, Intelligent RoutingProgramming
Day 1
Day 2
Day 12
FE 500 Throughput40
100
200
72
180
360
104
260
520
68
170
340
96
240
480
0
100
200
300
400
500
600
24 Minutes 36 Minutes 1 Hour
Average Time to Complete Primary and Secondary Tubes
Tube
s Lo
aded
and
Unl
oade
d
80% 1 aliquot, 20%
direct sort
Tubes loaded
80% 2 aliquots, 20%
direct sort
70% 1 aliquot, 30%
direct sort
70% 2 aliquots, 30%
direct sort
Error Reduction
99.3243,126Biohazard exposure events
80.01,8009,011Labeling errors
80.06143,072Pour-off errors
80.02,03810,192Sorting and routine errors
% ReductionPost FE500***Pre FE500Error / event classification
Number of Errors / Events per Month**
* Study performed at Milton S. Hershey Medical Center, Pennsylvania State University.** Estimated for one month’s period of data collection.*** Errors recorded in this category were from manually-handled samples for STAT testing plus those samples processed for microbiology and virology testing.
Centrifuge Efficiency
3.43 ± 3.21.9
7.51 ± 2.04.2
10.9 ± 2.46.1
180 ± 0100
Subject 2 (n=3)% of Ref.
1.6 ± 1.31.0
6.4 ± 2.84.0
6.4 ± 2.44.0
159 ± 6.6100
Subject 1 (n=3)% of Ref.
GENESIS FE500**(10 min cent)
GENESIS FE 500**(8 min cent)
Control run (manually centrifuged)*
Reference sample* (whole blood)
Data is expressed as mean ± SD of total platelets (x 103) / uL of whole blood. * NOTE: We performed a control run on each specimen according to NCCLS guidelines (e.g., 1500 x g for 10 minutes).
Fiscal Impact of the FE500
• Manual Processing Steps per month –75K
• 12 FTEs• Manual Processing
steps per month 25K• 8FTEs (- 33%)
Manual Processing
Automated Processing
SUMMARY
• Pre-analytical automation provides a cost effective improvement in specimen processing
• Throughput of pre-analytical automation workstations matches the needs of most medium sized laboratories
• Errors are significantly reduced by pre-analytical automation
Case Study 2: CoagAutolink
Automation Reduces Steps
INSPECT BALANCE LOAD ALIGN LOAD
TRANSPORT
Pre-analytical Processing Time
0 50 100 150
Minutes
Workcell Pre-labeled
Workcell
STAT Manual
Routine Manual
Source: Graves S, Felder RA. Robotic automation of coagulation analysis. Clinica Chemica Acta 278(2):269-279, 1998.
(simulated)
Times from Central Receiving to Aspiration
Manual
Auto
Case Study 3: Beckman Coulter
• Step I– Power
Processor– 16X100 mm– Manual barcode
scan• Step II
– Power Processor II
– Many size tubes– Automated bar
code scanning
Dadoun R., Case Study: Automation’s Impact on productivity and turnaround timeMLO, May 2002, 36-38.
0
5
10
15
20
25
STEPS STAT TOT Routine TOT
BeforeStep IStep II
Mobile Robots for Medical Deliveries
• Hospital wide delivery using the Helpmate (Pyxis, Inc., Danbury, CT)
• Intra-laboratory delivery using the RoboCart (CCRI, Lake Arrowhead, CA)
PIC & PLACE
• Automated pick up and delivery for medical specimens
• Does not interrupt busy technologists
• Provides high capacity transportation
• Provides greater efficiency than human based delivery methods
• Point of origin to point of need connectivity
Mobile Robots and Delivery Efficiency
Delivery Time Costs
050,000
100,000150,000200,000250,000300,000350,000400,000450,000
Cost
s, $
USA
2 Robots 3 Robots 6 Robots Courier
Alternatives
COSTS, Robot vs Courier
0
10
20
30
40
50
Deliv
ery
Tim
e (m
in)
2 Robots 3 Robots 6 Robots Courier
Alternatives
Delivery Time, Robot vs Courier
30% more efficient$250,000annual savings
Tecan Freedom EVO
• Modular design to serve genomics, proteomics, and diagnostics
• Modular hardware for detection, separation and storage
• Meets European EU In-Vitro Diagnostics Directive 98/79/EC and FDA’s 21 CFR Part 11 regulations
Gen-Probe Tigris DTS
• Automates all steps related to molecular diagnostic testing (nucleic acid amplification)– Sample processing– Amplification– Detection– Data analysis
Molecular Diagnostics
• Fastest growing diagnostic test sector• Presents new pre-analytical challenges
– Sample Identification and privacy– Cross contamination– Sample size
• Analytical techniques
Pre-analytical DNA Processors
• Automated DNA extraction at a rate of 40-96 specimens/day
• Whole blood, buffycoat, packed cells, lysates for compromised samples, buccals, cultured cells
• Cost per test is about $4/specimen
• DNA is suitable for most reactions
Gentra Autopure LS
Gentra Versapure 1000
Single Function MDx Automation• Completely automated
DNA/RNA extraction / purification
Magtration Extractor Precision System Science Tokyo, Japan.
Magnetic bead based extraction
Multiple Function MDx Automation
• Performs multiple parts of MDx reaction scheme
• Can be programmed for user flexibility
• Thermal cyclers, pipetting automation, and signal detection instruments placed on board
• Ideal for clinical molecular biology method development
TECAN Genesis RSP 150
Making DNA testing a routine part of medicine and industryD N A D E T E C T I O N T E C H N O L O G Y
Relies on bioelectronics—using organic molecules to form electronic circuits.
Allows the simple, rapid, and cost-effective detection of up to 36 DNA or RNA targets simultaneously: SNP, Mutation, Bacterial, Viral, Transgene, and Gene Expression
Simplified DNA Detection
• Electronic biochip reader• Custom and catalog biochip cartridges • Software and protocols • Designed for use in a commercial lab
setting
Molecular Diagnostics Summary
Ideal Small Laboratory Initial Molecular Diagnostic Devices
• Nucleic acid extractor• Polymorphism detection system
Post Analytical Automation
• Usually a function available on a pre-analytical processor
• Sorting, labeling, capping, organizing
• Automated reflex, repeat, add-on
AutomatedLowTemperatureStorage andRetrieval System
Compact Secure Storage
Summary and Conclusion
Goals• Provide examples of
modular automation systems that make sense in smaller laboratories
• Show actual performance data on some of these modular systems
Conclusions• Modular automation is
possibly the best first step in clinical laboratory automation
• Substantial process improvement, error reduction, and cost savings are being realized
• Modular automation is evolving to keep pace with the changing clinical diagnostics market
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