Lab Automation

LAB AUTOMATION RESOURCE GUIDE 

2018 

LAB AUTOMATION 

RESOURCE GUIDE 

INTRODUCTION 

by Laurence Painell 

THE LAB OF 

TOMORROW 


A SCRIPTING 

APPROACH TO 

AUTOMATION 

by Matheus C. Carvalho 

INSIGHTS INTO AUTOMATING YOUR 

Biobanking, Liquid Handling, Sample 

Preparation, and Immunoassays 

by Mike May, Angelo DePalma, and Joe 

Liscouski 

RETURN ON INVESTMENT 

by Joe Liscouski 

THE HUMAN SIDE 

by Erica Tennenhouse 

Lab Manager 2017 

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LabManager.com

Introduction 


Laboratories are constantly evolving. Systems, processes, 

machines, techniques, and layouts are always changing and 

adapting to the science and innovation required to design, 

test, and bring to market new products—and automation has 

a huge role to play. 

Automation and other developments like machine learning 

and robotics are already making waves in the industry by 

relieving researchers of mundane tasks and increasing 

accuracy and efficiency. Just look at high-throughput labs, 

where automation and robotics have been commonplace 

for decades. Thanks to modern technologies and the 

bidirectional nature of communication, the door is slowly 

being opened to more opportunities and innovations that 

could reduce time to market further while addressing 

other important issues such as regulatory compliance and 

transparency. 


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The Lab of Tomorrow 

What might the lab of the future look like? 

Where will automation fit in? Here are some predictions. 


The next five years 

Despite the speed of technological advancements, 

introducing new systems and processes in a laboratory 

can take time. Over the next five years, it might not look 

as though labs are changing significantly—but if you look 

beneath the surface, some major developments are likely to 

be taking place. 

• The cloud will become the norm even in regulated 

environments 

• Integration between software, services, and physical 

devices will be critical to providing a backbone for 

laboratory technologies 

• Collaboration and outsourcing will become 

commonplace 

• Data will become increasingly open and available across 

a given lab or business 

• The keyboard will be replaced with voice recognition 

technology 

• As the technology matures, 3-D printing will work its 

way further into prototyping and manufacturing 

EXPERT TIP: 

THE SECRET TO 

AUTOMATION SUCCESS 

“I think the secret to automation success is two-fold. First, 

know your extraction method really well and think about 

how you would perform it from a robot’s perspective. 

The method has to be automatable and no robot will be 

as perceptive or responsive to variations in the process as 

a human operator. Second, be the master of your robot. 

Vendor companies will provide programming support, but 

to guarantee success you need at least one staff member 

who is capable of programming the instrument. Vendors 

may be experts at programming, but they are unlikely to 

know your process as intimately as you do.” 

Rohan Steel, PhD, project leader in the Biological 

Research Unit at Racing Analytical Services, Ltd. 

(RASL), in Flemington, Australia 

• AI and machine learning will becoming more prevalent 

• Labs and businesses could decide to unlock their legacy 

data for the greater good 

• The internet of things (IoT) will create a steep 

change in efficiency by allowing for bidirectional 

communication between instruments, robots, and the 

systems and services used 

• It will be interesting to see how augmented reality 

develops over the next decade—but it’s something 

we could see slowly integrated into the laboratory 

environment 

The next 10 years 

This is where we start to break from certainty and start to 

look at changes that we expect to see based on the current 

evolution of technologies. 

• Radio-frequency identification RFID tags that allow the 

automatic reading of data will become cheap enough to 

be ubiquitous 


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A Scripting Approach to Automation 

Many laboratories still have not adopted automation, mostly due to the high cost of standard 

automated laboratory instruments. The situation is aggravated by the lack of compatibility 

between instruments made by different manufacturers. 

by Matheus C. Carvalho 

The problem of lack of compatibility between 

laboratory instruments has been recognized since the 

1990s. It has prompted some groups of laboratory 

professionals (see, for example, the Standardization in 

Lab Automation and Clinical and Laboratory Standards 

Institute initiatives) to propose the standardization of 

laboratory instruments. The reason is that standardized 

instruments would be compatible with each other. However, 

standardization involves considerable costs for instrument 

manufacturers and end-users, and thus standardization 

has achieved only limited success to improve instrument 

compatibility, a situation that will probably not change in the 

next few years. 

Fortunately, it is not necessary to wait for standardization 

in order to cope with the lack of compatibility between 

instruments. It is possible, today, to buy an instrument from 

company A and combine it with another from company B. 

And you do not need to be a technical wiz to do it—all you 

need is to learn about scripting. 

The scripting approach 

The technology that enables unrestricted compatibility 

between laboratory instruments is scripting, a 

variation of computer programming. Among scripting 

languages, AutoIt stands out as probably the most useful 

for integrating laboratory instruments because it enables 

automation of mouse clicks and keyboard entries. AutoIt has 

been developed and perfected since 1999, and it is entirely 

free. 

The main difference between the traditional approach for 

instrument integration and the one based on scripting is 

the way information is exchanged between instruments. 

In the traditional way, instruments send signals to each 

other (Figure 1). With scripting, instruments do not send 

signals to each other at all; instead, a computer (or more 

than one computer in a network) controls all instruments 

(Figure 2), and sends commands to them in an orderly 

fashion. Therefore, it is not necessary that the manufacturer 

of a certain instrument design this instrument with 

capabilities to communicate with other instruments: the 

only thing that is necessary is that the instrument can be 

controlled by a computer, which is a default capability in 

almost all instruments nowadays. Therefore, nothing extra 

is needed from the manufacturer’s side (compare this to 

standardization, which could demand a complete overhaul 

of the production process). 

Also, scripting is very accessible for the user. No knowledge 

of electronics or low-level computing is necessary. In fact, 

scripting is probably the easiest kind of programming that 

exists. Controlling different instruments using the AutoIt 

scripting language can be very simple; for example, the 

instruction “MouseClick,” which, as the name implies, 

executes a mouse click. Another instruction, “Send,” sends 

keyboard entries. These instructions can be called at spaced 

intervals (determined by the instruction “Sleep”) and at 

different coordinates on the computer screen. Therefore, 

the synchronization of two or more graphical interfaces, 

each controlling a different instrument, can be easily and 

intuitively enabled. This means that laboratory technicians 

and scientists can develop solutions for their instrument 

compatibility problems without the need for advanced 

technical support. 

More sophisticated control is also possible with AutoIt. 

For example, signals on the screen, like a popup window 

displaying “Waiting” or a button that is normally green 

but becomes red if a certain condition arises, can be 

incorporated into the coding, thus enabling interactive 

scripting. In addition to that, control of interfaces without 

direct use of the mouse and/or keyboard is also possible, 

thereby freeing the computer for multitasking. Finally, 

even remote synchronization is possible through the 

Internet. These and other more advanced solutions can be 

implemented after a deeper study of AutoIt. 


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The following are examples of applications that can benefit 

from a scripting approach: 

• Use of low-cost, easy-to-program robotic arms as 

autosamplers 

• Extending the life of older equipment by adapting the 

sampling mechanism of one device to a different one 

• Simplifying integration of accessories by using Autolt 

• Enabling automation for nonautomated devices 

LINDA Says... 

Companies and core labs are increasingly focused on ergonomics because repetitive stress and strain 

from certain manual tasks, such as pipetting, can take a toll on employee productivity and well-being. 

Automation takes over those more mundane tasks to eliminate the risk of repetitive injuries. 

Meet LINDA 

Linda 

LINDA is a lab manager. Her job is to balance the 

scientific needs of her staff with the business needs 

of her lab. LINDA stands for: 

Leadership 

Informed 

Negotiator 

Decision-Maker 

Accountable 


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Insights into 

Automating Your… 

by Mike May, Angelo DePalma, and Joe Liscouski 

Biobaking 

Some forms of lab work might seem more suited to 

automation than others. Biobanking—collecting and storing 

samples for research and clinical applications—sounds 

like a natural for automation. Applying automation to 

biobanking enables control over the whole process around 

the sample. For example, controlling the temperature 

improves a sample’s quality. Manual biobanking subjects 

a sample to greater temperature variation as a freezer gets 

opened and closed, and even left open longer than necessary, 

which can lead to tens of degrees of temperature changes. 

By automating this process, many steps can be completed 

without opening the freezer, which can produce temperature 

stability to within single degrees. 

Also, automation adds an audit trail to a sample, so 

researchers can be confident in the products they are 

getting out of the biobank. This can be especially useful 

in any regulated industry, such as biobanking samples for 

pharmaceutical research. 

When thinking about automating a biobank, though, 

researchers need to think ahead. One should choose an 

adaptable solution to meet future needs. For example, 

standardizing tube formats for automating tube storage and 

retrieval, such as using 2-D bar codes, enables researchers 

to track and cherry-pick samples that have been stored 

previously. 

Liquid Handling 

Systems exist for nearly every lab, workflow, and throughput 

level, even for many labs that believe automation is too 

complex or too expensive. All automated systems share one 

characteristic: They all replace tedious manual operations, 

which is where most errors occur. 

Full-blown robotic liquid handling systems are formidable, 

integrated systems with steep learning curves, but complexity 

is somewhat mitigated through improved interfaces. At the 

mid-range level of complexity, vendors are taking advantage 

of their entry- or mid-level automation products to create 

application-specific systems that may be reconfigured 

down the road as workflow demands change. This product 

development strategy requires balancing immediate needs 

with future-focused flexibility. 

Lab managers typically believe that if manual pipettes are not 

enough, they have to splurge on a robotic system. However, 

they should consider options in between, which may be more 

economical and, for many workflows, more efficient. Semiautomated 

systems, for instance, are simpler than robotics and 

spare end users from extensive training 

It all comes down to understanding workflows, and whether 

one wants to ramp up a little or a lot. Without full automation, 

a ninety-six-channel pipette still improves throughput 

significantly compared with a conventional handheld pipette. 

Managers need also to consider how many people will be 

using the instrument. If it’s a dedicated system, with a single 

task, with preprogrammed methods, and if walkaway time is 

valued, then a robotic system is appropriate. 


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competitive advantage, consider having a partnership with 

companies with similar needs to jointly develop automated 

solutions. This should reduce the cost of development and 

provide a more robust system with better support. It may 

also provide enough market justification for an equipment 

vendor to step in and develop hardware to fit the application. 

Sample Preparation 

Sample preparation can be a labor-intensive and 

expensive process. Unless the process is specifically designed 

for automated implementation, the process is going to have 

to be analyzed to see what it will take to make it suitable 

for semi-automated or fully automated work. The first item 

that has to be determined is whether you are using the 

current, up-to-date description of the process, including any 

undocumented workarounds or temporary fixes. 

Next, one must evaluate whether there is anything about 

the process that precludes automation. This would include 

working with objects or materials that depend on human 

dexterity and might not be usable with robotic systems. If 

that is the case, is it possible to modify the equipment or 

process to make the automation work without altering the 

science itself ? Another consideration is whether the process 

can be optimized—this may be necessary in order to meet 

performance goals. 

Early robotic sample preparation system implementations 

mimicked human activities, carrying out the same steps, 

one at a time, that people did. This removed people from 

the system (one goal) but often didn’t process more samples 

per hour, although it did provide a means for three-shift 

operation. Process optimization may require a change in how 

the process takes place, as long as it doesn’t compromise the 

integrity of the results. 

Sample preparation methods that are based on standardized 

sample containers will reduce the effort in automating 

systems. This is particularly true of autosamplers that use 

standardized vials. The use of standardized components 

reduces development costs, increases the likelihood of 

success, and permits reconfiguration of systems as needs 

change. 

Immunoassays 

Enzyme-linked immunosorbent assays (ELISAs) detect and 

quantify a target protein in a sample, and are used in many 

industries. This technique, however, involves incubation 

and washing steps, which make it complicated to run lots of 

these assays at the same time. 

The multiple steps and their required precision in ELISAs 

make these assays worth automating. Using microplate 

handlers and automation in general, especially in 

combination with scheduling software, will help to ensure 

the correct and similar timing of all plates when running 

several plates in a batch. This provides several benefits 

over manual processes, such as higher throughput, better 

precision, and reduced labor hours. 

Despite such alluring benefits, some challenges exist. If the 

vendor stops supporting a microplate handler, a user will 

eventually need to replace it and revise the automated assays 

as needed. Older microplate handlers can also cause trouble 

when they don’t integrate with newer equipment being used 

in the assay. 

In considering a purchase, labs should look for what fills 

all of their needs. It is not practical, for instance to provide 

extensive training for all end users, but the right interfaces 

can provide a layer of separation between users and the 

automation systems. 

If your application requires a custom-designed solution 

based on individual components (robotic arm, sample 

holders, etc.), the cost of development can increase 

significantly. Unless you believe that having a particular 

automated sample preparation system provides a 


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Return on Investment 

Consider both sides of the equation when calculating your ROI. 

by Joe Liscouski 

The goals of lab automation include: 

• Overall cost reduction, including labor and materials 

• Greater consistency 

• Higher productivity 

• More extensive analyses 

• The potential for 24/7 operations 

EXPERT TIP: 

MINIMIZING COST OVERRUNS 

“A lot of times, robotics is sold on the concept of 

versatility, but reliability then becomes the Achilles’ 

heel. Then you run into cost overruns, having to repeat 

experiments and analyses. One way to minimize cost 

overruns is to minimize human or manual interactions 

that can lead to errors that are propagated down the 

pipeline. So in your design, you must have instruments 

and protocols undergo quality control so as to not amplify 

mistakes during high-throughput screening.” 

Louis Scampavia, PhD, co-director of the High- 

Throughput Screening Lead Identification Division at 

The Scripps Research Institute in Florida 

For any ROI equation, there are two sides to consider. The 

first is what you want out of it, which includes some or all of 

the points above plus metrics—what level of performance 

are you looking for, what are you willing to spend, and what 

is the schedule requirement for implementation? You also 

have to evaluate the alternatives to automated systems, 

which include increasing head count or outsourcing work 

for comparison. Those last points would have to include an 

understanding of whether the need is a temporary spike in 

testing throughput or a long-term requirement; it is going 

to take time to implement a solution, and you don’t want it 

coming online as the need evaporates. 

The other side of the equation covers the costs. They 

include the development of the user and system 

requirements, a feasibility study, and prototype 

work, followed by the actual design, implementation, 

documentation, testing, validation, and user education. 

Given a set of requirements, the next major step is the 

feasibility study—this is going to provide the basis for the 

go/no-go decision on the project and guide the design effort. 


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The Human Side 

Making the most of your staff. 

by Erica Tennenhouse 

Reduction in labor is an unavoidable consequence of lab 

automation. That’s because the greatest cost of running 

a project is typically associated with staffing. If it takes 

fewer people to get the job done, then that becomes a 

straightforward measure of ROI. But reduction in labor does 

not always mean job loss. 

Prior to automation, labs can begin developing other 

businesses to launch in conjunction with the automation 

going live. This strategy enables labs to repurpose trained 

staff members who are already familiar with the lab’s 

services and culture for positions in new or growing 

businesses. 

EXPERT TIP: 

WHICH TASKS TO 

AUTOMATE? 

“It’s important to try to not automate things that humans 

are typically good at. For instance, in some labs you see 

a lot of sophisticated equipment with long articulated 

robotic arms for picking tubes and plates or for moving 

stacks in and out of the refrigerator or freezer. People can 

do those tasks cheaply and efficiently, and accuracy can 

always be checked if the vials and plates are barcoded. 

I personally do not think it’s worth spending enormous 

amounts of money on robotics for freezer management 

and such, unless you are working with a million samples a 

year. People think that they have to automate every single 

part of a protocol, but they should really be thinking 

about automating only those parts that are very routine 

and prone to errors.” 

Harold Swerdlow, PhD, vice president of sequencing 

at the New York Genome Center 

When automation opens up new and more challenging roles, 

it is often a boon to both the business and the staff. Using 

smaller, user-friendly systems to automate routine, tedious 

tasks can not only enhance reproducibility and eliminate 

user error, but it can also boost morale and productivity by 

freeing up scientists to do science rather than mindless tasks 

better suited to robots. 


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Lab Automation

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