Robotics in the medical laboratory

Felder, Robin A.; Boyd, James C.; Margrey, K S; Holman, W.T.; Savory, John

doi:10.1093/clinchem/36.9.1534

Cited by 22 publications

(9 citation statements)

References 4 publications

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“…Processing hundreds of samples can be very time‐consuming, and thus, automatizing procedures is another priority for upscaling DNA sequencing‐based diet studies (Porter & Hajibabaei, ). Automation using laboratory robots has been standard within clinical laboratories for decades (Boyd, Felder, & Savory, ; Felder, Boyd, Margrey, Holman, & Savory, ). Many companies that offer commercial laboratory kits now also offer compatible automated solutions and this with good reason as there are a number of benefits to gain from laboratory robots.…”

Section: Upscaling Dna Sequencing‐based Dietary Studiesmentioning

confidence: 99%

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Promises and pitfalls of using high‐throughput sequencing for diet analysis

Alberdi

Aizpurua

Bohmann

et al. 2018

Molecular Ecology Resources

175

195

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The application of high‐throughput sequencing‐based approaches to DNA extracted from environmental samples such as gut contents and faeces has become a popular tool for studying dietary habits of animals. Due to the high resolution and prey detection capacity they provide, both metabarcoding and shotgun sequencing are increasingly used to address ecological questions grounded in dietary relationships. Despite their great promise in this context, recent research has unveiled how a wealth of biological (related to the study system) and technical (related to the methodology) factors can distort the signal of taxonomic composition and diversity. Here, we review these studies in the light of high‐throughput sequencing‐based assessment of trophic interactions. We address how the study design can account for distortion factors, and how acknowledging limitations and biases inherent to sequencing‐based diet analyses are essential for obtaining reliable results, thus drawing appropriate conclusions. Furthermore, we suggest strategies to minimize the effect of distortion factors, measures to increase reproducibility, replicability and comparability of studies, and options to scale up DNA sequencing‐based diet analyses. In doing so, we aim to aid end‐users in designing reliable diet studies by informing them about the complexity and limitations of DNA sequencing‐based diet analyses, and encourage researchers to create and improve tools that will eventually drive this field to its maturity.

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Section: Upscaling Dna Sequencing‐based Dietary Studiesmentioning

confidence: 99%

“…Automation using laboratory robots has been standard within clinical laboratories for decades (Boyd, Felder, & Savory, 1996;Felder, Boyd, Margrey, Holman, & Savory, 1990). Many companies that offer commercial laboratory kits now also offer compatible automated solutions and this with good reason as there are a number of benefits to gain from laboratory robots.…”

mentioning

confidence: 99%

Promises and pitfalls of using high‐throughput sequencing for diet analysis

Alberdi

Aizpurua

Bohmann

et al. 2018

Molecular Ecology Resources

175

195

View full text Add to dashboard Cite

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“…Automation, which combines process management software and laboratory robotics, has been increasingly used to reduce the need for human labor in clinical laboratories. 2 Robotic workstations are defined as automated platforms that perform selected laboratory tasks 2,3 including various aspects of molecular biology. 4 –6 For example, amplified DNA or RNA is monitored in a closed tube system using real-time fluorescence to measure product yield as a means to determine the presence of infectious agents in a clinical specimen and potentially to further characterize or genotype microorganisms by conducting DNA melt curve analysis 7 for greater clinical impact.…”

Section: Introductionmentioning

confidence: 99%

Process Evaluation of a Fully Automated Molecular Diagnostics System

Felder

Foster²,

Lizzi³

et al. 2009

JALA: Journal of the Association for Laboratory Automation

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Molecular diagnostics presents challenges to clinical laboratories that are under pressure to consolidate and automate. There is a need to evaluate molecular automation for process efficiency and suitability for high-throughput environments in core laboratories. A fully automated molecular instrument platform (the BD Viper System with XTR Technology in extracted mode [BD Viper System with XTR]), was evaluated for automation efficiency, labor requirements, and system robustness. System productivity was predicted using time and motion studies as well as process simulation. Preanalytical steps required 15 min of skilled operator time. The BD Viper System with XTR fully automated DNA extraction, amplification, and analysis of 368 specimens (736 results for Chlamydia and Gonorrhea). Time and motion studies estimated that the total hands-on full time employee (FTE) burden was approximately 35 min per run, of which 41% was high complexity, 29% medium complexity and 29% relatively unskilled labor. A skilled operator can easily operate four instruments for 8.5 h and generate data on 2944 results (four runs on each instrument for a total of 1472 clinical specimens) for Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (GC) analysis. Based on mean time between intervention data, the BD Viper System with XTR was estimated to be capable of operating for more than 1000 runs without system malfunction. We determined that fully automated molecular analysis of GC and CT is possible in a core laboratory facility with significant throughput and minimal impact on labor demand using a fully automated and robust molecular diagnostics platform (such as the BD Viper System with XTR).

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“…Felder and his group [3,17,18,19,20,21,22] have constructed an unmanned, robot operated laboratory equipped with a multi-jointed robot (polar co-ordinate), a blood gas analyser, a blood electrolyte analyser and a touch-screen computer terminal. Several systems are placed in close proximity to critical patient care areas and monitored by a central computer through a local area network.…”

Section: Introduction Of Robotics In the Clinical Laboratorymentioning

confidence: 99%