ABSTRACT

This paper aims to identify whether gradual and/or total automation of laboratories will be of general benefit to the efficiency of laboratory procedures. First of all, automation of laboratory procedures requires funding to procure the reagents, software and machines. Secondly, it may be difficult for some traditional laboratories to adapt to the new automated systems. In order to rectify whether total automation systems are worth the financial risks and effort, surveys and experimental studies were conducted in different laboratories and institutions. The results indicate that technological advancements are very much needed in laboratories; for example, the software that run these automated systems are key to maintaining a larger and more comprehensive database. Also, the Total Automation Systems of laboratories have shown to be of key importance in providing efficient, accurate result in less the time it takes to do it manually. It is recommended that these techniques be also made available to undergraduate students, which could not only provide learning opportunity for the students themselves, but will also give use to automated systems that are otherwise to be discarded by laboratories.

INTRODUCTION

Time brings about drastic changes to our technological advancement. In keeping with today's fast -paced technology, automated laboratory techniques are becoming increasingly important in modern laboratories due to its apparent precision, accuracy and efficiency. Automated laboratory techniques refer to laboratory procedures that involve automated machines and/or computers that expedite the procedure. However, these techniques are not covered in traditional undergraduate laboratories. Imposing another hurdle to the automation of laboratory techniques is the hard transition of traditional method to the new automated methods in laboratories which involves the gruesome process of procurement of these machines, briefing of staff etc. Also, seeing that these modern techniques are automated, there remains the fact that machines also create errors. In order to address this problem, this paper will discuss various automated techniques, it's handling and applications vis-a-vis with traditional laboratory techniques.MATERIALS AND METHODS

A. Automation in Clinical Biochemistry: Core, Peripheral, STAT, and Specialist Laboratories in Clinical ChemistryThrough a self-administered survey to seniors in clinical biochemistry in NATA GX/GYclassified laboratories in Australia, the impact of technology to laboratory techniques was assessed. The responses were yes, no, or not applicable and are expressed as percentages of responses. Some of the questions sourced for descriptive answers.

B. Incorporation of Automation to Undergraduate LaboratoriesREAGENTS Distilled, deionized water and HPLC grade methanol and acetonitrile were used without further purification. A mixture of natural capsaicins (65 % capsaicin, 35 % dihydrocapsaicin) was purchased from Aldrich and used to make standards ranging from 120 ppm total capsaicins in HPLC mobile phase (75 % methanol, 25 % water). 3-mL, 500-mg BAKERBOND speTMOctadecyl disposable extraction columns were purchased from VWR (Cat. No. JT7020-3) and Tabasco brand pepper sauce (McIlhenny Co., Avery Island, LA) was used as purchased from a local grocery. Students performed manual methods for the solid phase extraction of capsaicin and dihydrocapsaicin from pepper sauces similar to those described previously 1,4. First, 10 mL of acetonitrile was added to a 2-3 g sauce sample and mixed well. Then, 1 mL of this acetonitrile extract was diluted with 9 mL water. After conditioning an SPE cartridge with 5 mL acetonitrile followed by 5 mL water, the above solution was passed through the cartridge, disposing of the aqueous phase. The capsaicins were eluted with 4 mL acetonitrile, and then with 1 mL of 1 % acetic acid in acetonitrile. High performance liquid chromatography was used for analysis of this combined extract. Figure 1.Zymark Benchmate II Workstation used for acetonitrile extraction, filtration and SPE cleanup of samples prior to liquid chromatographic analysis.() AUTOMATED EXTRACTIONS A Zymark (Hopkinton, MA) Benchmate TMII Workstation with DOS-based software version 3.0 was employed for the automated sample preparation methods. The manual SPE procedure was modified in order to conduct the extraction using the robotic workstation. Undergraduate students, as independent study projects, developed the robotic method used for this experiment. Another change in the method was mandated when backpressure limitations in the system caused a leak during the SPE step. Therefore, a filtering step was added prior to SPE to minimize particulate matter that would otherwise be passed through the cartridge. In addition, the order of individual steps, vortex time and speed, and solvent flow rates, as well as other set up parameters, were all realized as important optimization variables in the sample preparation phase of the experiment. The method program, which was performed on ~1 gram of sauce (weighed accurately and loaded onto the sample tray), for the laboratory experiment reported here is shown below: Step 1.Add 5 mL acetonitrile Step 2.Vortex for 600 s at speed 1 Step 3.Pause for 1 minute Step 4.Condition column with 5 mL acetonitrile Step 5.Condition column with 5 mL waterStep 6.Prewet with 1 mL of sample and filter 0.8 mL into next tube Step 7.Add 7.2 mL water Step 8.Vortex for 120 s at speed 1Step 9.Load 5 mL sample onto columnStep 10.Collect 4 mL fraction into next tube using acetonitrile Step 11.Collect 1 mL fraction into next tube using 1 % acetic acid in acetonitrile Step 12.End the total time for completion of this method program is 37.4 minutes. CHROMATOGRAPHIC ANALYSIS All standards and capsaicin extracts were analyzed by high performance liquid chromatography during the second three-hour laboratory period. Capsaicin and dihydrocapsaicin were quantified by reversed-phase HPLC using a Kratos Spectroflow 400 dual piston solvent delivery system equipped with a 20-mL injection loop and a Kratos SF 769Z variable wavelength UV/Vis absorption detector set at 205 nm. A ZORBAX 4.6 x 150 mm column with 5 mm C18 particles was used (Agilent Technologies, Palo Alto, CA). The mobile phase was 75:25 methanol:water at a flow rate of 1.0 mL/min, and data was collected using a custom program written in LabVIEW software version 4.0 (National Instruments, Austin, TX). Extracts (as prepared above) were injected and chromatographic peak heights were compared to calibration curves generated from a series of capsaicin standards.()

C. Implementing a Laboratory Automation System: Experience of a Large Clinical LaboratoryIn this research conducted by, the following topics comparing and contrasting pre- and post-LAS have been observed and explored: turnaround time (TAT), laboratory errors, and staff satisfaction. The benefits and limitations of Laboratory Automation System (LAS) from the laboratory experience were also reviewed. Question and answers regarding staff satisfaction are descriptive while the TAT, and laboratory errors were assessed through empirical data.

D. Does Laboratory Automation for the Preanalytical Phase Improve Data Quality?

In this research conducted by G. Oliveira et al., Blood from 100 volunteers was collected into two vacuum tubes. One sample from each volunteer was respectively assigned to (G1) traditional processing, starting with centrifugation at 1200g for 10 min, and (G2) the MODULAR PRE-ANALYTICALS EVO-MPA system. The routine clinical chemistry tests were performed in duplicate on the same instrument Cobas 6000 module. G1 samples were uncapped manually and immediately placed into the instrument. G2 samples were directly fed from the MPA system to the instrument without further staff intervention. At the end, (1) the G1 samples were stored for 6 h at 4 C as prescribed in our accredited laboratory and (2) the G2 samples were stored for 6 h in the MPA output buffer. Results from G1 and G2, before and after storage, were compared.

G. Managing the Workflow of a High-Throughput Organic Synthesis Laboratory: A Marriage of Automation and Information Management Technologies

According to Dr. Burton Goodman, PhD, the procedure for this research are as follows: Production of libraries began with loading the appropriate linkers onto resins, followed by complete characterization of the resin-linker intermediate. The resins were then loaded into IRORI MiniKans and sorted using the IRORI Autosort 10Kx sorting workstation. Chemistry was then performed using standard laboratory glassware. Additional sorting and chemistry steps were then performed until the compound was ready for cleavage off of the resin. The MiniKans were then sorted into Bohdan MiniBlocks and treated with the appropriate cleavage cocktail. Collection into 48-position racks was followed by removal of cleavage solution through vacuum centrifugation. The concentrate was then dissolved in a solvent mixture that allowed for standard liquid handling automation to create 96 well plates for analysis by high throughput flow inject NMR and LC/MS.

RESULTS AND DISCUSSIONA. Automation in Clinical Biochemistry: Core, Peripheral, STAT, and Specialist Laboratories in Australia

According to G. Streitberg et al., Eighty-one laboratories responded, and the locations were 63%, 33%, and 4% in capital cities, regional cities, and country towns, respectively. Forty-two percent were public and 58% private. Clinical biochemistry was in all core laboratories of various sizes, and most performed up to 20 tests per sample. Thirty percent of the 121 surveyed laboratories had plans to install an automated line. Fifty-eight percent had hematology and biochemistry instrumentations in their peripheral laboratory, and 16% had a STAT laboratory on the same site as the core laboratory. There were varied instruments in specialist laboratories, and analyzers with embedded computers were in all laboratories. Medium and large laboratories had workstations with integrated instruments, and some large laboratories had TLA.

B. Incorporation of Automation to Undergraduate Laboratories

Although many hot sauces have been used in this work, results reported here are for Tabasco brand pepper sauce due to its availability and ability to achieve a homogeneous solution compared to other oil-based sauces that have a tendency to separate into distinct phases. Figure 2 represents example liquid chromatograms for a capsaicin standard and for a Tabasco extract prepared by the automated method. The baseline of the standard is offset for clarity. Capsaicin and dihydrocapsaicin were identified in the sauce extract Figure 3.HPLC calibration plots generated from capsaicin-dihydrocapsaicin standards. The equations of the lines were y = 0.0145x + 0.0025 (r2= 0.9995) and y = 0.0111x + 0.0010 (r2= 0.9989) for capsaicin and dihydrocapsaicin, respectively. by their chromatographic retention times of 4.1 and 5.3 min, respectively. Other peaks in the extract chromatogram are consistent with previous reports, such as the peak at 1.5 minutes being a polar constituent not removed by the SPE cleanup,1and the peaks at 5.8 and 7 min being other capsaicin compounds4that were not a focus in this work. Figure 3 presents student calibration curves generated from standards for capsaicin and dihydrocapsaicin used to quantitate the two compounds in the sauces. Plotting peak height as a function of capsaicin concentration yielded straight lines with acceptable correlation coefficients (r2= 0.9995 and 0.9989 for capsaicin and dihydrocapsaicin, respectively) for quantitation. Figure 4 presents typical data obtained by students for the concentrations of capsaicin and dihydrocapsaicin in Tabasco sauce, comparing manual and automated sample preparation methods. The error bars on the plot represent the standard deviation of several independent extractions (n = 7 for the manual extractions and n = 6 for the automated extractions). The two methods yielded statistically similar results in terms of concentrations (107 12 ppm capsaicin and 66 12 ppm dihydrocapsaicin and 117 8 ppm capsaicin and 73 7 ppm dihydrocapsaicin for preparations done manually and by the Benchmate, respectively), but better reproducibility was achieved with the automated preparation method. The results obtained here are consistent with capsaicin concentrations reported (in terms of Scoville Heat Units) for Tabasco.5It should be noted, however, that capsaicin concentrations in this, and other, pepper sauces can vary from bottle to bottle, so these reported results are from the same bottle.

C. Implementing a Laboratory Automation System: Experience of a Large Clinical Laboratory

The mean TAT for both stat and routine samples decreased post-LAS (30% and 13.4%, respectively). In the 90th percentile TAT chart, a 29% reduction was seen in the processing of stat samples on the LAS. However, no significant difference in the 90th percentile TAT was observed with routine samples. It was surprising to note that laboratory errors increased post-LAS. Considerable effort was needed to overcome the initial difficulties associated with adjusting to a new system, new software, and new working procedures.

D. Does Laboratory Automation for the Preanalytical Phase Improve Data Quality?

Results from G1 and G2, before and after storage, were compared. Significant increases were observed in G1 compared with G2 samples as follows: (1) before storage for alkaline phosphatase (ALP), lactate dehydrogenase (LDH), phosphate (P), magnesium (MG), iron (FE), and hemolysis index and (2) after storage for total cholesterol (COL), triglycerides (TG), total protein (TP), albumin (ALB), blood urea nitrogen (BUN), creatinine (CRE), uric acid (UA), ALP, pancreatic amylase, aspartate aminotransferase (AST), alanine aminotransferase (ALT), g-glutamyltransferase (GGT), LDH, creatine kinase (CK), calcium (CA), FE, sodium (NA), potassium (K), and hemolysis index. Moreover, significant increases were observed in (3) G1-after versus G1-before storage samples for COL, high-density lipoprotein cholesterol, TG, TP, ALB, BUN, CRE, UA, AST, ALT, GGT, LDH, P, CA, MG, FE, NA, K, and hemolysis index and (4) G2-after versus G2-before storage only for BUN, AST, LDH, P, and CA

CONCLUSIONA. Automation in Clinical Biochemistry: Core, Peripheral, STAT, and Specialist Laboratories in AustraliaTechnology evolution and rising demand for pathology services make it imperative for laboratories to embrace such changes and reorganize the laboratories to take into account point-of-care testing and the efficiencies of core laboratories and TLA.

B. Incorporation of Automation to Undergraduate LaboratoriesAn automated sample preparation method was developed by students for the extraction and SPE cleanup of capsaicins from commercial pepper sauce using a robotic workstation. In addition, automation was integrated into the undergraduate instrumental analysis laboratory by modifying an existing experiment without utilizing additional lab time, and students were eager to work with the workstation rather than preparing the samples by hand. The authors hope to increase awareness of the readers of the Journal about the important role of teaching institutions in implementing automation, and will also realize the pedagogical benefits of 1. industrial-academic collaborations and 2. Donations of equipment that might otherwise be discarded.

C. Implementing a Laboratory Automation System: Experience of a Large Clinical Laboratory Although some of the known advantages and limitations of LAS have been validated, the claimed benefits such as improvements in TAT, laboratory errors, and staff morale were not evident in the initial months.

D. Does Laboratory Automation for the Preanalytical Phase Improve Data Quality? Results show that MPA system improves the quality of laboratory testing. Therefore, laboratory automation for the Preanalytical phase improves data quality.

E. Automation and Expert Systems in a Core Clinical Chemistry LaboratoryAutomation of the main chemistry analyzers, including immunoassay and linking them together with preanalytical and postanalytical automation to give total laboratory automation has given predictability to result availability.

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