The use of automation and robotics has become pervasive in clinical laboratories around the world. Laboratories face unrelenting pressure to produce faster turnaround times and reduce errors to improve patient care. Since the development of the continuous flow analyzer in the 1950s, laboratory automation has continued to evolve and expand its capabilities to become an indispensable necessity. Current technologies can automate specimen transportation, sorting, accessioning, and inspection.

As pressure has increased to cut healthcare costs over the last decade, laboratories have relied on automation to maintain profitability as well. Laboratory automation is designed to maximize efficiency and minimize errors by integrating mechanical, electronic, and informatics tools to perform an ever expanding variety of laboratory tasks. Following the installation of automation error reduction rates exceed 70%, while staff time per specimen collection is reduced by over 10%. Patient safety is increased by an average 50% reduction in specimen turnaround time directly attributable to automation.

Currently, more than 30% of laboratories in Japan, Europe, and North America have implemented a significant degree of central laboratory automation. In addition, many laboratories report that automation creates excess capacity to expand testing without the need to increase their workforce. As a result, the proper sizing of laboratory automation systems with current and anticipated testing volume is important.

Defining the State of the Art
There is virtually no limit to the number and complexity of tasks that can be automated. For example, at least one company is currently working to automate phlebotomy(1). Called the Veebot, this instrument would locate forearm veins and then chart the trajectory for a needle-wielding venipuncture robot. Failed venipuncture procedures can injure patients due to so-called bad veins. In fact, nearly 25% of procedures fail to draw blood on the first attempt, and almost a million needle stick injuries are reported each year (2).

Modern laboratory automation resembles a traditional assembly line, termed total laboratory automation (TLA). TLA consists of a specimen sorter that can sort specimens by analytical needs and transport specimens requiring serum or plasma testing to an automated centrifugation station for processing. Following sample separation the serum or plasma is then transported for sampling to various chemistry and immuno­assay analyzers. The sorter can also identify whole blood specimens and convey them to automated instruments for complete blood counts and other hematology testing. Remaining specimens are automatically sent to racks that are specific for each analytical ­platform. These specimens can then be manually transported and inserted into the instrument of choice.

Currently, approximately 80% of the testing and only about 50% of the manual labor performed in a clinical laboratory is impacted by automation, leaving many opportunities for novel automation technologies in sample collection, centrifugation, accessioning, sample inspection, transportation, and more.

The Ideal Automation Blueprint
When first considering the purchase of a fully automated laboratory, the layout of the laboratory and shape of the room is critical for maximizing the return on investment. The ideal physical plant and layout for an automated clinical laboratory is a linear “bowling alley” design.

  • Specimen arrivals should take place at the proximal end of the laboratory where accessioning can occur immediately after unpacking, and the automated sorter should be readily accessible at the end of the accessioning line.
  • Each analytical automation line should run in parallel so that bench scientists can service several analytical areas with as few steps as possible.
  • Completed specimens should be automatically stored at the distal end of the laboratory conveyor belt so that they may participate in reflex, repeat, or add-on testing without human intervention. Automated specimen refrigerators (4°C) and freezers (either -20°C or -80°C) are available that are capable of performing these tasks.
  • Laboratories that anticipate making their medical waste available for research may install automated aliquoting and labeling systems, as well as biorepository-sized automated storage systems.
  • Delivery and storage of analytical reagents is ideally accomplished in a bank of refrigerators/freezers with doors on both sides of the laboratory installed parallel to the analytical systems they serve. Stocking occurs from the back of each unit and retrieval of reagents from the front.
  • Finally, medical and reagent packaging waste should exit the laboratory at the distal end, accessible to automated pickup carts and vehicles.

A Look at the Future
Given that automation is becoming a commodity in larger laboratories, laboratorians need to stay up-to-date on new opportunities. For each area below, I forecast what form laboratory automation may take in the future, perhaps in the next decade or two.

Automated Specimen Separation
Blood separation into serum or plasma has been an insuperable bottleneck in all clinical laboratories. Ideally, sample separation should be done at the point of sample collection and incorporate automated labeling. An elegant point-of-care separation solution, the Axial Separation Module, was developed for separating formed elements from plasma in a whole blood specimen in under one minute immediately after phlebotomy (3). Unfortunately, this technology failed to gain market acceptance. Similar technologies are under development that uses creative means to impart increased centrifugal forces on the blood specimen. Hopefully, some of these will be commercialized in the near future.

Specimen Transportation
Despite the variety of methods of transportation currently available, all have considerable flaws. Human and robotic courier services have inflexible pickup times and delays, while pneumatic tube systems have potential for specimen damage and limited carrying capacity (4). Electric track vehicles reduce the damage risks of tube systems and the lack of flexibility from the courier service, but they take up large amounts of space. One alternative is automated specimen delivery using mobile robots that can negotiate the halls of a hospital (5, 6). Once in the laboratory, the robot can automatically deliver its payload and continue service without having to interrupt a laboratory technologist (7). In the near future, drones may provide both extra-laboratory as well as inter-laboratory delivery. A drone’s ability to rapidly move small numbers of specimens from a clinic to a laboratory can avoid automobile traffic delays. Inside a laboratory, drone deliveries can make a 200 foot journey in less than 2 seconds, according to Donald Nagy, CEO of California Computer Research and member of the Society for Laboratory Automation and Screening.

Pre-Analytical Automation
Once specimens arrive in the laboratory there are new pre-accession processors that can start with a bucket of randomly oriented specimens and finish with racked and processed specimens for downstream analytical processing. Researchers at the University of Utah are developing an automated specimen inspector that examines critical specimen quality issues such as proper labeling, sufficient volume, and correct vial additive. In the future, the inspector will also determine the presence of lipemia, icterus, or hemolysis through several overlaid labels (8). From the inspector, next-generation­ linear motor conveyors will transport the tubes very rapidly: 3,000–18,000 tubes an hour moving at a rate of 20–120 meters a second. The system will also employ an automated sorting area where specimens can be automatically centrifuged or passed on directly to the hematology/coagulation robotic area, according to Charles D. Hawker, PhD, MBA, FACB, scientific director of automation and special projects at ARUP Laboratories. Essentially the entire accessioning process will be automated so that time from phlebotomy to result will be 30 minutes or less.

Sample Labeling
Mistakes in sample labeling can lead to sample misplacement and mislabeling, resulting in a loss of samples and inaccurate results. The progression from manual labeling to 2- and 3-D barcodes has dealt with many labeling problems and significantly cut down on sample misplacement and mislabeling. However, the development affordable radio-frequency identification (RFID) is poised to allow positive passive specimen tracking as samples are moved from patient bedside to analysis. While barcodes often require manual scans, RFID completely eliminates human involvement. Reduced costs for the technology, and advantages such as error reduction and reduced labor demand, have put RFID in the spotlight at the Mayo Clinic and other organizations (9). Disruptive Analytical Methods and Trends Several emerging methods closely related to laboratory automation are poised to shift the landscape of laboratory testing. In addition, the push for expanding biobanking and home monitoring cannot be ignored.

The most disruptive use of automation in the laboratory will come in the form of rapid sequencing of entire microbe DNA/RNA. Advanced computer software can identify each individual organism in an infection, as well as the organism’s susceptibility to specific antimicrobials. Technologies such as Ion Torrent, Myseq, ionPGM, and PackBio are already demonstrating improved turnaround time and positive microbe identification in clinical settings. Coupled with software algorithms that can match DNA/RNA sequences with those from known pathogens, these technologies might one day replace much of today’s conventional microbiological laboratory procedures similar to the Lawrence Livermore Microbial Detection Array (10).

Cell Based Assays
Another disruptive technology will be the use of living cells from patients as diagnostic tools. Cell-based assays are being used for diagnosis, as well as predicting clinical outcomes and response to therapy in an increasing number of diseases including cancer, organ rejection, and diabetes (11). Exfoliated organ cells have the potential to supplement current biomarker-based analyses since cell-based assays can measure aberrations in cell activity that may be present in complex chronic diseases. For example, salt sensitivity of blood pressure is a major public health challenge and a disease for which there is no convenient diagnostic test. We demonstrated that cells isolated from urine in normal subjects not only provided a personalized cell-based diagnostic test for salt sensitivity, but also provided a personal salt index, which is the amount of sodium each person should safely consume in a day (12). Like conventional analytical techniques, cell based assays will be readily automated when sufficient volume justifies the investment.

Biobanking is the process of storing left over medical specimens along with data describing the phenotype and genotype of the patient from which the specimen was obtained. This material is valuable to diagnostic and pharmaceutical companies for research and development. Most of the steps in biobanking have been automated, such as specimen aliquoting, labeling, freezing, and storing. Even the retrieval of selected specimens in order to prepare a disease representative cohort can be automated using “cherry pickers” that operate at freezing temperatures. Thus, automation can turn medical waste (i.e. leftover medical specimens) into profit for the laboratory and tools for researchers.

The Final Frontier: Home-Based Monitoring
Monitoring is pervasive with the advent of wearable sensors that communicate with smartphones. The hope is that individuals will use this medical data to adopt healthier lifestyles. Increasingly, biomarkers in body fluids will also be the target of ubiquitous personal sensors. For example, Google recently announced that it was developing a contact lens that would measure glucose secreted in tear fluid in order to provide passive sensing for diabetic patients. Similar technology is being developed in a more convenient “insertable” and therefore body resident format (13). The future will provide an ever broadening number of biomarkers—such as cortisol for stress monitoring—and physiologic parameters that will guide lifestyle choices.

Laboratory automation has become a well-accepted technology that allows high quality, efficient, and patient-centric operation with low operating costs. Automation should also be the foundation on which a Six Sigma program can be built and maintained. Technological advances will increase the number of laboratory unit ­operations that can be either ­partially or fully automated. Near patient or personal wellness testing should be considered an extension of the laboratory automation ­enterprise.


  1. Boyd JC, Hawker CD. Automation in the clinical laboratory. In: Burtis CA, Ashwood ER, Bruns DE, eds. Tietz textbook of clinical chemistry and molecular diagnostics. 5th Ed. Phildelphia: W.B. Saunders 2012:469–85.
  2. Occupational Safety & Health Administration. Healthcare wide hazards: Needlestick/sharps injuries. (Accessed October 2014).
  3. Estey CA, Felder RA. Clinical trials of a novel centrifugation technique: Axial separation. Clin Chem 1996;42:402–9.
  4. Felder RA. Preanalytical errors introduced by sample-transportation systems: A means to assess them. Clin Chem 2011;57:1349–50.
  5. Rosetti MD, Kumar A, Felder RA. Simulation of robotic courier deliveries in hospital distribution services. Health Care Man Science 2000;3:201–13.
  6. Felder RA. Laboratory systems integration: Robotics and automation. Ann Biol Clin 1991;49:298–300.
  7. Patent US6543983 B1 - Robotic pickup and delivery system. (Accessed October 2014).
  8. Hawker CD, McCarthy W, Cleveland D, et al. Invention and validation of an automated camera system that uses optical character recognition to identify patient name mislabeled samples. Clin Chem 2014;60:463–70.
  9. ODIN. ODIN introduces EasySpecime RFID-based lab tracking solution. (Accessed September 1, 2014).
  10. Dark Daily. (Accessed October 28, 2014). 
  11. Rahmoune H, Thompson PW, Ward JM, et al. Glucose transporters in human renal proximal tubular cells isolated from the urine of patients with non-insulin-dependent diabetes. Diabetes 2005;54:3427–34. 
  12. Gildea JJ, Lahiff DT, Van Sciver RE, et al. A linear relationship between the ex-vivo sodium mediated expression of two sodium regulatory pathways as a surrogate marker of salt sensitivity of blood pressure in exfoliated human renal proximal tubule cells: The virtual renal biopsy. Clin Chim Acta 2013;421:236–42. 
  13. Patent US8090426 B2 - Micro­elec­tronic biosensor plug. (Accessed October 2014).
Robin Felder, PhD, is a professor of pathology and associate director of clinical chemistry at the University of Virginia Health System in Charlottesville, Virginia and chair of