Automated Sampling
Automated Sampling - Related Videos
10:12
Shotgun Proteomics Sample Processing Automated by an Open-Source Lab Robot
0 Views •
Cited by 8 •
2021
Detailed protocol and three Python scripts are provided for operating an open-source robotic liquid handling system to perform semi-automated protein sample preparation for mass spectrometry experiments, covering detergent removal, protein digestion, and peptide desalting steps.
07:26
A Simple Method for Automated Solid Phase Extraction of Water Samples for Immunological Analysis of Small Pollutants
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Cited by 2 •
2016
A protocol for the extraction and pre-concentration of estradiol from water samples by using an automated and miniaturized system is presented.
08:06
Automated Acoustic Dispensing for the Serial Dilution of Peptide Agonists in Potency Determination Assays
0 Views •
Cited by 1 •
2016
Peptide adsorption to plasticware during traditional tip-based serial dilutions can significantly impact potency determination and confound the understanding of structure-activity relationships used for lead identification and lead optimization phases of drug discovery. Here methods for automated acoustic non-contact serial dilution of peptide samples are described.
06:19
Low-Cost Automated Flight Intercept Trap for the Temporal Sub-Sampling of Flying Insects Attracted to Artificial Light at Night
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Cited by 1 •
2021
To study the impacts of artificial light at night (ALAN) on nocturnal flying insects, sampling needs to be confined to nighttime. The protocol describes a low-cost automated flight intercept trap that allows researchers to sample at user-defined periods with increased replication.
07:12
A Plasma Sample Preparation for Mass Spectrometry using an Automated Workstation
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Cited by 26 •
2020
Here, we present an automated plasma protein digestion method for mass spectrometry-based quantitative proteomic analysis. In this protocol, the liquid transferring and incubation steps for protein denaturation, reduction, alkylation, and trypsin digestion reactions are streamlined and automated. It takes approximately five hours to prepare a 96-well plate with desired precision.
FAQs
Consistency depends on controlling several variables together: timing, location, condition, volume, and transfer. A programmed protocol establishes when and where collection occurs, while instrument settings standardize how much material moves through the system. This coordination matters in repeated or time-sensitive studies, where differences in collection can affect the reliability of later measurements.
Sensors, pumps, and laboratory information systems support different parts of the workflow. Sensors can help monitor defined conditions, pumps regulate specimen movement, and information systems connect programmed sampling with laboratory processing. Their integration helps maintain consistent handling and transfer, particularly when a study requires coordinated operations across multiple sampling times or locations.
Programmed collection limits the influence of individual operator actions on timing, volume, and transfer. By applying the same preset protocol across repeated samples, the system can reduce differences introduced during manual handling. This standardization improves reproducibility and may help preserve sample integrity, making measured differences more likely to reflect the biological process rather than inconsistent collection.
A typical workflow begins by defining the sampling times, locations, conditions, volumes, and transfer requirements. The instrument or robotic system then follows those settings to collect and move specimens. Sensors, pumps, or laboratory information systems may be integrated as needed to support the programmed sequence. Consistent execution allows subsequent laboratory processing to use comparable samples.
The approach is especially useful when studies require repeated collection, tightly defined sampling times, or higher throughput than manual handling can provide. Pharmacokinetic studies can use it to support consistent sampling across scheduled time points, while clinical research can benefit from more reproducible specimen collection. These advantages are most relevant when timing and handling affect measurement reliability.
In diagnostic testing, standardized collection and transfer can support more consistent specimen processing before measurement. In bioprocess monitoring, programmed sampling can provide specimens from defined conditions and times, helping investigators follow process-related changes. Across both settings, improved reproducibility and reduced operator variability can strengthen comparisons among samples and support more reliable interpretation of results.