Digitalizing the design-make-test-analyze workflow in drug discovery with an electronic inventory platform

IF 2.5 4区 医学 Q3 BIOCHEMICAL RESEARCH METHODS
Ting Qin, Aparna Chandrasekaran, Jason Shiers, Matthew Crittall, Ciaran O’Reilly, Colin Sambrook Smith
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引用次数: 0

Abstract

Drug discovery is a collaborative endeavor that often involves scientists from various disciplines and global collaborators. Efficient real-time sharing and updating of design-make-test-analyze (DMTA) information remains a challenge in drug discovery, hindering timely decision-making and project advancement. We propose a novel approach utilizing existing electronic inventory systems as DMTA workflow tracking platforms. Our approach at Sygnature Discovery leverages the inherent flexibility of these systems, allowing us to tailor stages and compound information to individual project needs, resulting in significant cost savings compared with building an in-house solution or purchasing a commercial solution. Given the wide adoption of electronic inventory platforms in drug discovery, our strategy holds immense potential for easy adoption and broad application across the industry.
利用电子库存平台实现药物研发设计-制造-测试-分析工作流程的数字化。
药物发现是一项合作努力,通常涉及来自不同学科和全球合作者的科学家。设计-制造-测试-分析(design-make-test- analysis, DMTA)信息的有效实时共享和更新一直是药物发现的挑战,阻碍了决策的及时制定和项目的推进。我们提出了一种利用现有电子库存系统作为DMTA工作流跟踪平台的新方法。我们在signature Discovery的方法利用了这些系统固有的灵活性,允许我们根据单个项目的需求定制阶段和复合信息,与构建内部解决方案或购买商业解决方案相比,可以显著节省成本。鉴于电子库存平台在药物发现中的广泛应用,我们的战略在整个行业中具有易于采用和广泛应用的巨大潜力。
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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.
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