LDM: A web application for automated management and visualization of laboratory screening data

IF 2.5 4区医学 Q3 BIOCHEMICAL RESEARCH METHODS

SLAS Technology Pub Date : 2025-02-21 DOI:10.1016/j.slast.2025.100258

David Meyer , Anastasia Escher , Eva Riegler , David Keller , Michael Prummer , Stephanie Huber , Tijmen Booij

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引用次数: 0

Abstract

High-throughput screening (HTS) is essential in preclinical research to identify new drug candidates for specific diseases. This process typically generates large amounts of data that require effective storage, management, and analysis. Traditional methods for handling HTS data involve several standalone solutions, which can present challenges regarding data accessibility and reproducibility. We introduce Lab Data Management (LDM), an open-source web application developed to automate the management and visualization of HTS data. LDM provides a highly customizable data management system with an intuitive user interface for handling output data from various laboratory instruments, such as plate readers, microscopes, liquid handlers, and barcode readers. The app allows for results visualization and calculation of quality control metrics. An integrated Jupyter notebook can be used to retrieve the stored data and proceed with a more detailed analysis.

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来源期刊

SLAS Technology Computer Science-Computer Science Applications

CiteScore

6.30

自引率

7.40%

发文量

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.