Automation of biochemical assays using an open-sourced, inexpensive robotic liquid handler

IF 2.5 4区 医学 Q3 BIOCHEMICAL RESEARCH METHODS SLAS Technology Pub Date : 2024-10-11 DOI:10.1016/j.slast.2024.100205
George Moukarzel , Yi Wang , Weiyue Xin, Carl Hofmann, Anjali Joshi, John W. Loughney, Amy Bowman
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Abstract

High Throughput Screening is crucial in pharmaceutical companies for efficient testing in drug discovery and development. Our Vaccines Analytical Research and Development (V-AR&D) department extensively uses robotic liquid handlers in their High Throughput Analytics (HTA) group for assay development and sample screening. However, these instruments are expensive and require extensive training. Opentrons' OT-2 liquid handler offers a more affordable option (<∼ $10,000) with Python programming language and open-source flexibility, reducing training requirements. OT-2 allows broadening of testing capabilities and method transfer without significant capital investments. Two biochemical assays were conducted to assess OT-2′s performance, and it demonstrated accurate pipetting with low covariance compared to Tecan EVO liquid handlers. Though OT-2 has some limitations such as lack of a crash detection system and limited deck space, it is a cost-effective, medium-throughput, and accurate liquid handling tool suitable for early-stage development and method transfer.
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使用开源、廉价的机器人液体处理装置实现生化测定自动化
高通量筛选是制药公司在药物发现和开发过程中进行高效测试的关键。我们的疫苗分析研发部门(V-AR&D)在其高通量分析 (HTA) 小组中广泛使用机器人液体处理机进行检测开发和样品筛选。然而,这些仪器价格昂贵,而且需要大量培训。Opentrons的OT-2液体处理机提供了一种更经济实惠的选择(小于10,000美元),采用Python编程语言,具有开源灵活性,减少了培训要求。OT-2 可扩大测试能力和方法转移,无需大量资金投入。为了评估 OT-2 的性能,我们进行了两项生化测定,与 Tecan-EVO 液体处理仪相比,OT-2 的移液准确度高,协方差小。虽然 OT-2 有一些局限性,如缺乏碰撞检测系统和甲板空间有限,但它是一款经济高效、中等通量和精确的液体处理工具,适合早期开发和方法转让。
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来源期刊
SLAS Technology
SLAS Technology Computer Science-Computer Science Applications
CiteScore
6.30
自引率
7.40%
发文量
47
审稿时长
106 days
期刊介绍: SLAS Technology emphasizes scientific and technical advances that enable and improve life sciences research and development; drug-delivery; diagnostics; biomedical and molecular imaging; and personalized and precision medicine. This includes high-throughput and other laboratory automation technologies; micro/nanotechnologies; analytical, separation and quantitative techniques; synthetic chemistry and biology; informatics (data analysis, statistics, bio, genomic and chemoinformatics); and more.
期刊最新文献
Model-Based Interactive Visualization for Complex Systems Requirements and Design in Joint Tests. Implementing enclosed sterile integrated robotic platforms to improve cell-based screening for drug discovery. Life Sciences Discovery and Technology Highlights. Notes on AEMS methods development for high throughput experimentation in drug discovery. Prosthesis repair of oral implants based on artificial intelligenc`e finite element analysis.
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