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Researchers devoted a great deal of time (50+ hours weekly) manually copying and pasting data from an animal study data management system to a separate laboratory information management system (LIMS). Our client wanted Arrayo to develop an integration that would allow data to flow seamlessly from one system to the other to eliminate this menial and time-consuming task for scientists.
Arrayo developed a custom software integration developed in Python with code deployed using AWS Lambda and serverless design patterns. The software automatically extracts relevant data from the animal study data management system in real time, transforms the data to match the LIMS data model, and upload/update the data into the LIMS. The software handled both updates and net-new data coming from the source data management system. The software is also able to be rerun for specific top-level entities (e.g., Experiments) resulting in data propagation for all in-scope child entities/metadata. The data updates approximate “real-time” performance with around 5 minutes from the time an object is updated from the source system to the time it is created/updated on the client’s LIMS.
Arrayo delivered a software integration that cut down on the time researchers spent on manually inputting data, allowing them to focus their time on what they do best.