MGiant-Q1000

MGiant-Q1000 is the first fully automatic fluorescence luminescence immunoassay analyzer in the industry, which integrates the functions of experiment operation, experiment master data maintenance, historical results and analysis. Given the complex business data in the protein joint detection project, this platform provides clear user operation guidance to assist users in entering information quickly and correctly, allowing users to monitor the device’s status in real time, lowering the threshold to use and strengthening the user’s control over the device. In addition, its functions are highly expandable, and it has the ultra-high-throughput processing capability, which can provide users with accurate and fast experimental results, and help speed up laboratory diagnosis. MGiant-Q1000 is ideal for a wide range of applications and research fields, including immunoassay, nucleic acid research, enzymatic analysis, receptor and ligand recognition.
The interface design is adapted to the real detection scene, and the visual design is used to classify information to help users obtain the feedback information to implement hardware operation at different distances, and process it accurately.
MGiant-Q1000 adopts an innovative closed-loop information framework to improve experimental efficiency:
When maintaining host data from small to large, it will guide users to input information from the smallest level; use host data from large to small when running experiments, and bring out the material information contained under it according to the user’s choice, and ensure that the user loading materials according to the page content, helping users quickly get started and complete the experimental process, developing user habits. It not only simplifies the tedious data selection process, but also ensures the accuracy of the data and the ease of use of the device, bringing users a convenient and safe experience. In addition, it supports users to load samples for testing in a loop, which can meet the needs of target users with a large number of test samples. One run setting can run through multiple experimental processes, which not only reduces user operation costs, but also greatly improves experimental efficiency.