Can I benefit from laboratory automation? A decision aid for the successful introduction of laboratory automation.

The large volumes of samples to be analysed every day would be impossible to manage without laboratory automation. As laboratory procedures have progressed, so have the tasks of laboratory personnel. With this feature article, we would like to provide (bio)chemical practitioners with little or no knowledge of laboratory automation with a guide to help them decide whether to implement laboratory automation and find a suitable system. Especially in small- and medium-sized laboratories, operating a laboratory system means having bioanalytical knowledge, but also being familiar with the technical aspects. However, time, budget and personnel limitations allow little opportunity for personnel to get into the depths of laboratory automation. This includes not only the operation, but also the decision to purchase an automation system. Hasty investments do not only result in slow or non-existent cost recovery, but also occupy valuable laboratory space. We have structured the article as a decision tree, so readers can selectively read chapters that apply to their individual situation. This flexible approach allows each reader to create a personal reading flow tailored to their specific needs. We tried to address a variety of perspectives on the topic, including people who are either supportive or sceptical of laboratory automation, personnel who want or need to automate specific processes, those who are unsure whether to automate and those who are interested in automation but do not know which areas to prioritize. We also help to make a decision whether to reactivate or discard already existing and unused laboratory equipment.

Improvement of bioanalytical parameters through automation: suitability of a hand-like robotic system.

Commercial automation systems for small- and medium-sized laboratories, including research environments, are often complex to use. For liquid handling systems (LHS), development is required not only for the robot's movements but also for adapting the bioanalytical method to the automated system. This study investigates whether a more human-like automation strategy-using a robotic system (RS)-is more suitable for research laboratories than a professional automation approach utilizing a commercial automated LHS. We conducted a series of measurements for protein determination using a Bradford assay manually, with a fully automated LHS, and with our human-like RS. Although the hand-like RS approach requires more than twice the time of the LHS, it achieved the best standard deviation in this setup (RS = 0.5, manual = 0.71, LHS = 0.86). Due to the low limit of detection (LOD) and limit of quantification (LOQ), most protein samples could be quantified with the RS (samples below LOQ = 9.7%, LOD = 0.23; LOQ = 0.25) compared to manual (samples below LOQ = 28.8%, LOD = 0.24; LOQ = 0.26) and the LHS (samples below LOQ = 36.1%, LOD = 0.27; LOQ = 0.31). In another time-dependent enzymatic assay test, the RS achieved results comparable to the manual method and the LHS, although the required time could be a constraint for short incubation times. Our results demonstrate that a more hand-like automation system closely models the manual process, leading easier to accurate bioanalytical results. We conclude that such a system could be more suitable for typical research environments than a complex LHS.

Enabling high-throughput biology with flexible open-source automation.

Our understanding of complex living systems is limited by our capacity to perform experiments in high throughput. While robotic systems have automated many traditional hand-pipetting protocols, software limitations have precluded more advanced maneuvers required to manipulate, maintain, and monitor hundreds of experiments in parallel. Here, we present Pyhamilton, an open-source Python platform that can execute complex pipetting patterns required for custom high-throughput experiments such as the simulation of metapopulation dynamics. With an integrated plate reader, we maintain nearly 500 remotely monitored bacterial cultures in log-phase growth for days without user intervention by taking regular density measurements to adjust the robotic method in real-time. Using these capabilities, we systematically optimize bioreactor protein production by monitoring the fluorescent protein expression and growth rates of a hundred different continuous culture conditions in triplicate to comprehensively sample the carbon, nitrogen, and phosphorus fitness landscape. Our results demonstrate that flexible software can empower existing hardware to enable new types and scales of experiments, empowering areas from biomanufacturing to fundamental biology.

An automated, high-throughput methodology optimized for quantitative cell-free mitochondrial and nuclear DNA isolation from plasma.

Progress in the study of circulating, cell-free nuclear DNA (ccf-nDNA) in cancer detection has led to the development of noninvasive clinical diagnostic tests and has accelerated the evaluation of ccf-nDNA abundance as a disease biomarker. Likewise, circulating, cell-free mitochondrial DNA (ccf-mtDNA) is under similar investigation. However, optimal ccf-mtDNA isolation parameters have not been established, and inconsistent protocols for ccf-nDNA collection, storage, and analysis have hindered its clinical utility. Until now, no studies have established a method for high-throughput isolation that considers both ccf-nDNA and ccf-mtDNA. We initially optimized human plasma digestion and extraction conditions for maximal recovery of these DNAs using a magnetic bead-based isolation method. However, when we incorporated this method onto a high-throughput platform, initial experiments found that DNA isolated from identical human plasma samples displayed plate edge effects resulting in low ccf-mtDNA reproducibility, whereas ccf-nDNA was less affected. Therefore, we developed a detailed protocol optimized for both ccf-mtDNA and ccf-nDNA recovery that uses a magnetic bead-based isolation process on an automated 96-well platform. Overall, we calculate an improved efficiency of recovery of ∼95-fold for ccf-mtDNA and 20-fold for ccf-nDNA when compared with the initial procedure. Digestion conditions, liquid-handling characteristics, and magnetic particle processor programming all contributed to increased recovery without detectable positional effects. To our knowledge, this is the first high-throughput approach optimized for ccf-mtDNA and ccf-nDNA recovery and serves as an important starting point for clinical studies.

Rapid quantification of multi-cryoprotectant toxicity using an automated liquid handling method.

Cryopreservation in a vitrified state has vast potential for long-term storage of tissues and organs that may be damaged by ice formation. However, the toxicity imparted by the high concentration of cryoprotectants (CPAs) required to vitrify these specimens remains a hurdle. To address this challenge, we previously developed a mathematical approach to design less toxic CPA equilibration methods based on the minimization of a toxicity cost function. This approach was used to design improved methods for equilibration of bovine pulmonary artery endothelial cells (BPAEC) with glycerol. To fully capitalize on the toxicity cost function approach, it is critical to describe the toxicity kinetics of additional CPAs, including multi-CPA mixtures that are commonly used for vitrification. In this work, we used automated liquid handling to characterize the toxicity kinetics of five of the most common CPAs (glycerol, dimethyl sulfoxide (DMSO), propylene glycol, ethylene glycol, and formamide), along with their binary and ternary mixtures for BPAEC. In doing so, we developed experimental methods that can be used to determine toxicity kinetics more quickly and accurately. Our results highlight some common CPA toxicity trends, including the relatively low toxicity of ethylene glycol and a general increase in toxicity as the CPA concentration increases. Our results also suggest potential new approaches to reduce toxicity, including a surprising toxicity neutralization effect of glycerol on formamide. In the future, this dataset will serve as the basis to expand our CPA toxicity model, enabling application of the toxicity cost function approach to vitrification solutions containing multiple CPAs.

Unlocking the efficiency of genomics laboratories with robotic liquid-handling.

In research and clinical genomics laboratories today, sample preparation is the bottleneck of experiments, particularly when it comes to high-throughput next generation sequencing (NGS). More genomics laboratories are now considering liquid-handling automation to make the sequencing workflow more efficient and cost effective. The question remains as to its suitability and return on investment. A number of points need to be carefully considered before introducing robots into biological laboratories. Here, we describe the state-of-the-art technology of both sophisticated and do-it-yourself (DIY) robotic liquid-handlers and provide a practical review of the motivation, implications and requirements of laboratory automation for genome sequencing experiments.

Semi-automation of process analytics reduces operator effect.

The aim of this study was to semi-automate process analytics for the quantification of common impurities in downstream processing such as host cell DNA, host cell proteins and endotoxins using a commercial liquid handling station. By semi-automation, the work load to fully analyze the elution peak of a purification run was reduced by at least 2.41 h. The relative standard deviation of results among different operators over a time span of up to 6 months was at the best reduced by half, e.g. from 13.7 to 7.1% in dsDNA analysis. Automation did not improve the reproducibility of results produced by one operator but released time for data evaluation and interpretation or planning of experiments. Overall, semi-automation of process analytics reduced operator-specific influence on test results. Such robust and reproducible analytics is fundamental to establish process analytical technology and get downstream processing ready for Quality by Design approaches.

Cost-Effective Automated Preparation of Serum Samples for Reproducible Quantitative Clinical Proteomics.

Reproducible sample preparation remains a significant challenge in large-scale clinical research using selected reaction monitoring-mass spectrometry (SRM-MS), which enables a highly sensitive multiplexed assay. Although automated liquid-handling platforms have tremendous potential for addressing this issue, the high cost of their consumables is a drawback that renders routine operation expensive. Here we evaluated the performance of a liquid-handling platform in preparing serum samples compared with a standard experiment while reducing the outlay for consumables, such as tips, wasted reagents, and reagent stock plates. A total of 26 multiplex assays were quantified by SRM-MS using four sets of 24 pooled human serum aliquots; the four sets used a fixed number (1, 4, 8, or 24) of tips to dispense digestion reagents. This study demonstrated that the use of 4 or 8 tips is comparable to 24 tips (standard experiment), as evidenced by their coefficients of variation: 13.5% (for 4 and 8 tips) versus 12.0% (24 tips). Thus we can save 37% of the total experimental cost compared with the standard experiment, maintaining nearly equivalent reproducibility. The routine operation of cost-effective liquid-handling platforms can enable researchers to process large-scale samples with high throughput, adding credibility to their findings by minimizing human error.

Optimizing high throughput antibody purification by using continuous chromatography media.

The ability to engineer monoclonal antibodies (mAbs) with high specificity made mAbs the fastest growing segment in the drug market. mAbs represent 8 of the top 20 selling drugs with combined sales of more than 57 billion US$ per year. The ability to purify large numbers of mAbs with sufficient yields for initial screening campaigns has direct impact on the timelines of a project. Automated liquid handling (ALH)-based mAb purification platforms have been used to facilitate the production of large numbers of mAbs. However, the ongoing pressure to de-risk potential lead molecules at an early development stage by including bio-physical characterization of mAbs has further increased the demand to produce sufficient quantities from limited sample volumes. A bottleneck so far has been the limited dynamic binding capacity of these systems, which is partly due to the binding properties of commonly used Protein A affinity matrices. The present publication suggests that by using a Protein A matrix optimized for continuous chromatography applications the yields of ALH-based but also standard lab-scale mAb purifications can be significantly increased without the need to change established protocols.

Controlling cell-free metabolism through physiochemical perturbations.

Building biosynthetic pathways and engineering metabolic reactions in cells can be time-consuming due to complexities in cellular metabolism. These complexities often convolute the combinatorial testing of biosynthetic pathway designs needed to define an optimal biosynthetic system. To simplify the optimization of biosynthetic systems, we recently reported a new cell-free framework for pathway construction and testing. In this framework, multiple crude-cell extracts are selectively enriched with individual pathway enzymes, which are then mixed to construct full biosynthetic pathways on the time scale of a day. This rapid approach to building pathways aids in the study of metabolic pathway performance by providing a unique freedom of design to modify and control biological systems for both fundamental and applied biotechnology. The goal of this work was to demonstrate the ability to probe biosynthetic pathway performance in our cell-free framework by perturbing physiochemical conditions, using n-butanol synthesis as a model. We carried out three unique case studies. First, we demonstrated the power of our cell-free approach to maximize biosynthesis yields by mapping physiochemical landscapes using a robotic liquid-handler. This allowed us to determine that NAD and CoA are the most important factors that govern cell-free n-butanol metabolism. Second, we compared metabolic profile differences between two different approaches for building pathways from enriched lysates, heterologous expression and cell-free protein synthesis. We discover that phosphate from PEP utilization, along with other physiochemical reagents, during cell-free protein synthesis-coupled, crude-lysate metabolic system operation inhibits optimal cell-free n-butanol metabolism. Third, we show that non-phosphorylated secondary energy substrates can be used to fuel cell-free protein synthesis and n-butanol biosynthesis. Taken together, our work highlights the ease of using cell-free systems to explore physiochemical perturbations and suggests the need for a more controllable, multi-step, separated cell-free framework for future pathway prototyping and enzyme discovery efforts.

Downstream processing of a plant-derived malaria transmission-blocking vaccine candidate.

Plants as a platform for recombinant protein expression are now economically comparable to well-established systems, such as microbes and mammalian cells, thanks to advantages such as scalability and product safety. However, downstream processing accounts for the majority of the final product costs because plant extracts contain large quantities of host cell proteins (HCPs) that must be removed using elaborate purification strategies. Heat precipitation in planta (blanching) can remove ∼80% of HCPs and thus simplify further purification steps, but this is only possible if the target protein is thermostable. Here we describe a combination of blanching and chromatography to purify the thermostable transmission-blocking malaria vaccine candidate FQS, which was transiently expressed in Nicotiana benthamiana leaves. If the blanching temperature exceeded a critical threshold of ∼75 °C, FQS was no longer recognized by the malaria transmission-blocking monoclonal antibody 4B7. A design-of-experiments approach revealed that reducing the blanching temperature from 80 °C to 70 °C restored antibody binding while still precipitating most HCPs. We also found that blanching inhibited the degradation of FQS in plant extracts, probably due to the thermal inactivation of proteases. We screened hydrophobic interaction chromatography materials using miniature columns and a liquid-handling station. Octyl Sepharose achieved the highest FQS purity during the primary capture step and led to a final purity of ∼72% with 60% recovery via step elution. We found that 30-75% FQS was lost during ultrafiltration/diafiltration, giving a final yield of 9 mg kg-1 plant material after purification based on an initial yield of ∼49 mg kg-1 biomass after blanching.

How to measure the affinity of aptamers for membrane proteins expressed on the surface of living adherent cells.

Recently, an increasing number of aptamers have been selected against biomarkers that are expressed at the surface of cells. This class of targets, mostly membrane proteins, is in close contact with the intra- and extra-cellular matrixes and their three-dimensional structures are inextricably linked to their inclusion in lipid bilayers. Therefore, although binding studies can be performed on the isolated form of these proteins, it remains crucial to measure the affinity of these aptamers in a more physiological environment, i.e., directly on living cells. Here, we describe a procedure for radioactive binding assays that can be adapted for measuring the affinity of aptamers against different cell lines. This method has been semi-automated using a liquid handling robot in order to reproducibly measure the apparent dissociation constant Kd and the apparent number of targets per cell. Relevant issues are discussed including the labeling of aptamers, the cells preparation, the incubation, the washings, the use of non-specific competitors, the data analysis and finally the reporting.

Automated high-throughput dense matrix protein folding screen using a liquid handling robot combined with microfluidic capillary electrophoresis.

Modern molecular genetics technology has made it possible to swiftly sequence, clone and mass-produce recombinant DNA for the purpose of expressing heterologous genes of interest; however, recombinant protein production systems have struggled to keep pace. Mammalian expression systems are typically favored for their ability to produce and secrete proteins in their native state, but bacterial systems benefit from rapid cell line development and robust growth. The primary drawback to prokaryotic expression systems are that recombinant proteins are generally not secreted at high levels or correctly folded, and are often insoluble, necessitating post-expression protein folding to obtain the active product. In order to harness the advantages of prokaryotic expression, high-throughput methods for executing protein folding screens and the subsequent analytics to identify lead conditions are required. Both of these tasks can be accomplished using a Biomek 3000 liquid handling robot to prepare the folding screen and to subsequently prepare the reactions for assessment using Caliper microfluidic capillary electrophoresis. By augmenting a protein folding screen with automation, the primary disadvantage of Escherichia coli expression has been mitigated, namely the labor intensive identification of the required protein folding conditions. Furthermore, a rigorous, quantitative method for identifying optimal protein folding buffer aids in the rapid development of an optimal production process.

Modeling error in experimental assays using the bootstrap principle: understanding discrepancies between assays using different dispensing technologies.

All experimental assay data contains error, but the magnitude, type, and primary origin of this error is often not obvious. Here, we describe a simple set of assay modeling techniques based on the bootstrap principle that allow sources of error and bias to be simulated and propagated into assay results. We demonstrate how deceptively simple operations--such as the creation of a dilution series with a robotic liquid handler--can significantly amplify imprecision and even contribute substantially to bias. To illustrate these techniques, we review an example of how the choice of dispensing technology can impact assay measurements, and show how large contributions to discrepancies between assays can be easily understood and potentially corrected for. These simple modeling techniques--illustrated with an accompanying IPython notebook--can allow modelers to understand the expected error and bias in experimental datasets, and even help experimentalists design assays to more effectively reach accuracy and imprecision goals.

TidyTron: Reducing lab waste using validated wash-and-reuse protocols for common plasticware in Opentrons OT-2 lab robots.

Every year biotechnology labs generate a combined total of ∼5.5 million tons of plastic waste. As the global bioeconomy expands, biofoundries will inevitably increase plastic consumption in-step with synthetic biology scaling. Decontamination and reuse of single-use plastics could increase sustainability and reduce recurring costs of biological research. However, throughput and variable cleaning quality make manual decontamination impractical in most instances. Automating single-use plastic cleaning with liquid handling robots makes decontamination more practical by offering higher throughput and consistent cleaning quality. However, open-source, validated protocols using low-cost lab robotics for effective decontamination of plasticware-facilitating safe reuse-have not yet been developed. Here we introduce and validate TidyTron: a library of protocols for cleaning micropipette tips and microtiter plates that are contaminated with DNA, E. coli, and S. cerevisiae. We tested a variety of cleaning solutions, contact times, and agitation methods with the aim of minimizing time and cost, while maximizing cleaning stringency and sustainability. We tested and validated these cleaning procedures by comparing fresh (first-time usage) versus cleaned tips and plates for contamination with cells, DNA, or cleaning solutions. We assessed contamination by measuring colony forming units by plating, PCR efficiency and DNA concentration by qPCR, and event counts and debris by flow cytometry. Open source cleaning protocols are available at https://github.com/PlantSynBioLab/TidyTron and hosted on a graphical user interface at https://jbryantvt.github.io/TidyTron/.

ANDeS: An automated nanoliter droplet selection and collection device.

The Droplet Microarray (DMA) has emerged as a tool for high-throughput biological and chemical applications by enabling miniaturization and parallelization of experimental processes. Due to its ability to hold hundreds of nanoliter droplets, the DMA enables simple screening and analysis of samples such as cells and biomolecules. However, handling of nanoliter volumes poses a challenge, as manual recovery of nanoliter volumes is not feasible, and traditional laboratory equipment is not suited to work with such low volumes, and small array formats. To tackle this challenge, we developed the Automated Nanoliter Droplet Selection device (ANDeS), a robotic system for automated collection and transfer of nanoliter samples from DMA. ANDeS can automatically collect volumes from 50 to 350 nL from the flat surface of DMA with a movement accuracy of ±30 µm using fused silica capillaries. The system can automatically collect and transfer the droplets from DMA chip into other platforms, such as microtiter plates, conical tubes or another DMA. In addition, to ensure high throughput and multiple droplet collection, the uptake of multiple droplets within a single capillary, separated by air gaps to avoid mixing of the samples within the capillary, was optimized and demonstrated. This study shows the potential of ANDeS in laboratory applications by using it for the collection and transfer of biological samples, contained in nanoliter droplets, for subsequent analysis. The experimental results demonstrate the ability of ANDeS to increase the versatility of the DMA platform by allowing for automated retrieval of nanoliter samples from DMA, which was not possible manually on the level of individual droplets. Therefore, it widens the variety of analytical techniques that can be used for the analysis of content of individual droplets and experiments performed using DMA. Thus, ANDeS opens up opportunities to expand the development of miniaturized assays in such fields as cell screening, omics analysis and combinatorial chemistry.

Construction of a Calibration Curve for Lycopene on a Liquid-Handling Platform─Wider Lessons for the Development of Automated Dilution Protocols.

Liquid-handling is a fundamental operation in synthetic biology─all protocols involve one or more liquid-handling operations. It is, therefore, crucial that this step be carefully automated in order to unlock the benefits of automation (e.g., higher throughput, higher replicability). In the paper, we present a study, conducted at the London Biofoundry at SynbiCITE, that approaches liquid-handling and its reliable automation from the standpoint of the construction of the calibration curve for lycopene in dimethyl sulfoxide (DMSO). The study has important practical industrial applications (e.g., lycopene is a carotenoid of industrial interest, DMSO is a popular extractant). The study was also an effective testbed for the automation of liquid-handling. It necessitated the development of flexible liquid-handling methods, which can be generalizable to other automated applications. In addition, because lycopene/DMSO is a difficult mix, it was capable of revealing issues with automated liquid-handling protocols and stress-testing them. An important component of the study is the constraint that, due to the omnipresence of liquid-handling steps, errors should be controlled to a high standard. It is important to avoid such errors propagating to other parts of the protocol. To achieve this, a practical framework based on regression was developed and utilized throughout the study to identify, assess, and monitor transfer errors. The paper concludes with recommendations regarding automation of liquid-handling, which are applicable to a large set of applications (not just to complex liquids such as lycopene in DMSO or calibration curves).

Anastrozole and Tamoxifen Impact on IgG Glycome Composition Dynamics in Luminal A and Luminal B Breast Cancers.

This study examines the intricate relationship between protein glycosylation dynamics and therapeutic responses in Luminal A and Luminal B breast cancer subtypes, focusing on anastrozole and tamoxifen impacts. The present methods inadequately monitor and forecast patient reactions to these treatments, leaving individuals vulnerable to the potential adverse effects of these medications. This research investigated glycan structural changes by following patients for up to 9 months. The protocol involved a series of automated steps including IgG isolation, protein denaturation, glycan labelling, purification, and final analysis using capillary gel electrophoresis with laser-induced fluorescence. The results suggested the significant role of glycan modifications in breast cancer progression, revealing distinctive trends in how anastrozole and tamoxifen elicit varied responses. The findings indicate anastrozole's association with reduced sialylation and increased core fucosylation, while tamoxifen correlated with increased sialylation and decreased core fucosylation. These observations suggest potential immunomodulatory effects: anastrozole possibly reducing inflammation and tamoxifen impacting immune-mediated cytotoxicity. This study strongly emphasizes the importance of considering specific glycan traits to comprehend the dynamic mechanisms driving breast cancer progression and the effects of targeted therapies. The nuanced differences observed in glycan modifications between these two treatments underscore the necessity for further comprehensive research aimed at thoroughly evaluating the long-term implications and therapeutic efficacy for breast cancer patients.

Development and evaluation of three automated media pooling and molecular diagnostic systems for the detection of SARS-CoV-2.

Pooled testing combined with molecular diagnostics for the detection of SARS-CoV-2 is a promising method that can increase testing capacities and save costs. However, pooled testing is also associated with the risks of decreased test sensitivity and specificity. To perform reliable pooled testing, we developed and validated three automated media pooling and molecular diagnostic systems. These pooling systems (geneLEAD-PS, Panther-PS, and Biomek-PS) comprised existing automated molecular detection platforms, corresponding automated media pooling devices, and laboratory information management systems. Analytical sensitivity analysis and mock sample evaluation were performed, and the obtained data were used to determine the sizes of the pool for the validation study. In the validation study, a total of 2,448, 3,228, and 6,420 upper respiratory samples were used for geneLEAD-PS, Panther-PS, and Biomek-PS, respectively, and the diagnostic performances were compared with the reference RT‒PCR assay. A pool size of 6 for geneLEAD-PS and a pool size of 4 for Panther-PS and Biomek-PS were selected for the validation studies. All three systems showed high positive percent agreement values of ≥90.5% and negative percent agreement values of ≥99.8% for any specimen type. Pooled testing resulted in a 65%-71% reduction in cost per sample. The testing capacities of geneLEAD-PS, Panther-PS, and Biomek-PS were 144 samples in 3 hours, 384 samples in 5.5 hours, and 376 samples in 4 hours, respectively. The developed pooling systems showed robust diagnostic performances and will increase the testing capacities of molecular diagnostic tests while saving costs and may contribute to infection control of COVID-19.IMPORTANCEDuring the COVID-19 pandemic, there have been surges in demand for accurate molecular diagnostic testing and laboratory supply shortages. Pooled testing combined with highly sensitive molecular testing, which entails mixing multiple samples as a single sample, is a promising approach to increase testing capacities while reducing the use of consumables. However, pooled testing is associated with risks that compromise diagnostic performance, such as false negatives due to dilution of positive samples or false positives due to cross-contamination. To perform reliable pooled testing, three different pooling systems (an automated pooling device, an automated molecular detection platform, and a laboratory information management system) were developed to accurately interpret pooled testing results. These three systems were validated using multiple clinical samples and showed high concordance with individual testing. The developed pooling systems will contribute to increasing reliable molecular testing capacities while using fewer consumables and saving costs.

Development and validation of automated methods for COVID-19 PCR Master Mix preparation.

Polymerase chain reaction (PCR)-based assays were widely deployed during the SARS-CoV-2 pandemic for population-scale testing. High-throughput molecular diagnostic laboratories required a high degree of process automation to cope with huge testing demands, fast turnaround times, and quality requirements. However, process developers and optimizers often neglected the critical step of preparing a PCR Master Mix. The construction of PCR Master Mix depends on operator skill during the manual pipetting of reagents. Manual procedures introduce variation, inconsistency, wastage, and potentially risks data integrity. To address this, we developed a liquid-handler-based solution for automated, traceable, and compliant PCR Master Mix preparation. Here, we show that a fully automated PCR Master Mix protocol can replace manual pipetting, even in a diagnostic environment, without affecting accuracy or precision. Ultimately, this method eliminated operator-induced wastage and improved the consistency of the quality of results.