Experiences with Automated Sample Preparation in Bioanalysis

1994 ◽  
pp. 61-69
Author(s):  
V. S. Picot ◽  
R. D. McDowall
Keyword(s):  
Sample Preparation ◽  
Automated Sample Preparation

Optimization of Automated Sample Preparation for Vitamin D Determination on a Biomek i7 Workstation

2021 ◽  
pp. 247263032110302
Author(s):  
Anna Bach ◽  
Heidi Fleischer ◽  
Bhagya Wijayawardena ◽  
Kerstin Thurow
Keyword(s):  
Vitamin D ◽  
Sample Preparation ◽  
Reference Method ◽  
Positive Pressure ◽  
Additional Risk Factor ◽  
Serum Samples ◽  
Recovery Rates ◽  
Preparation Methods ◽  
Sample Throughput ◽  
Automated Sample Preparation

Vitamin D belongs to the fat-soluble vitamins and is an integral part of bone metabolism. In the human body, a decreased vitamin D level can be an additional risk factor for diseases like cancer, diabetes, and mental diseases. As a result, an enormous increase in the demand for vitamin D testing has been observed in recent years, increasing the demand for powerful methods for vitamin D determination at the same time. Automation is the key factor in increasing sample throughput. This study compares three fully automated sample preparation methods for the determination of 25(OH)D2 and 25(OH)D3 in plasma and serum samples. Starting from a semiautomated reference method, the method is tested manually and subsequently fully automated on the Biomek i7 Workstation by integrating a centrifuge and a positive pressure extractor into the workstation. Alternatively, the centrifugation for the separation of protein aggregates and supernatant is replaced by a filter plate. Finally, the sample throughput is further increased by using phospholipid removal cartridges. The results show that phospholipid removal significantly increases the recovery rates in liquid chromatography–mass spectrometry. With the phospholipid removal cartridges, recovery rates of 97.36% for 25(OH)D2 and 102.5% for 25(OH)D3 were achieved, whereas with the automated classic automated preparation method, the recovery rates were 83.31% for 25(OH)D2 and 86.54% for 25(OH)D3. In addition to the technical evaluation, the different methods were also examined with regard to their economic efficiency. Finally, the qualitative and quantitative performance of the developed methods is benchmarked with a selected semiautomatic reference method.

scholarly journals Automated Sample Preparation and Data Collection Workflow for High-Throughput In Vitro Metabolomics

Metabolites ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 52
Author(s):  
Julia M. Malinowska ◽  
Taina Palosaari ◽  
Jukka Sund ◽  
Donatella Carpi ◽  
Gavin R. Lloyd ◽  
...  
Keyword(s):  
Sample Preparation ◽  
High Throughput ◽  
High Throughput Screening ◽  
In Vitro Screening ◽  
Chemical Safety ◽  
Experimental Conditions ◽  
Well Location ◽  
Relative Standard ◽  
Automated Sample Preparation

Regulatory bodies have started to recognise the value of in vitro screening and metabolomics as two types of new approach methodologies (NAMs) for chemical risk assessments, yet few high-throughput in vitro toxicometabolomics studies have been reported. A significant challenge is to implement automated sample preparation of the low biomass samples typically used for in vitro screening. Building on previous work, we have developed, characterised and demonstrated an automated sample preparation and analysis workflow for in vitro metabolomics of HepaRG cells in 96-well microplates using a Biomek i7 Hybrid Workstation (Beckman Coulter) and Orbitrap Elite (Thermo Scientific) high-resolution nanoelectrospray direct infusion mass spectrometry (nESI-DIMS), across polar metabolites and lipids. The experimental conditions evaluated included the day of metabolite extraction, order of extraction of samples in 96-well microplates, position of the 96-well microplate on the instrument’s deck and well location within a microplate. By using the median relative standard deviation (mRSD (%)) of spectral features, we have demonstrated good repeatability of the workflow (final mRSD < 30%) with a low percentage of features outside the threshold applied for statistical analysis. To improve the quality of the automated workflow further, small method modifications were made and then applied to a large cohort study (4860 sample infusions across three nESI-DIMS assays), which confirmed very high repeatability of the whole workflow from cell culturing to metabolite measurements, whilst providing a significant improvement in sample throughput. It is envisioned that the automated in vitro metabolomics workflow will help to advance the application of metabolomics (as a part of NAMs) in chemical safety, primarily as an approach for high throughput screening and prioritisation.

A simple and automated sample preparation system for subsequent halogens determination: Combustion followed by pyrohydrolysis

2018 ◽  
Vol 1010 ◽  
pp. 29-36 ◽  
Author(s):  
L.S.F. Pereira ◽  
M.F. Pedrotti ◽  
P. Dalla Vecchia ◽  
J.S.F. Pereira ◽  
E.M.M. Flores
Keyword(s):  
Sample Preparation ◽  
Automated Sample Preparation

scholarly journals A new approach to mixing techniques for enhanced performance in automated sample preparation

1995 ◽  
Vol 17 (5) ◽  
pp. 169-171
Author(s):  
François Qian ◽  
Eric Vérette ◽  
Atika El-Sayed
Keyword(s):  
Sample Preparation ◽  
Glucose Solution ◽  
New Approach ◽  
Relative Standard ◽  
Different Types ◽  
Mixing Method ◽  
Automated Sample Preparation ◽  
Standard Deviations ◽  
Mixing Techniques ◽  
Sample Dilution

In the automation of sample dilution or derivatization, the performance of the mixing technique employed when adding solvents or reagents to samples is critical. This paper presents a newly developed mixing method, based on conventional aspiration and dispensing of liquid techniques, but which considerably improves the precision of mixing. The paper discusses the results of a comparison of the technique with other methods and describes the application of the technique to several different types of sample solutions, including a highly concentrated glucose solution. The mixing technique was performed on a Gilson XL Sampling Injector, with a 1/25 dilution of a paraben solution in 2 ml vials to give relative standard deviations of 0.2 to 0.3% (N =10).

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