Automating data management in drug discovery
“Processing data takes a long time,” says Ronnett Seddon, screening technician for the Drug Discovery and Development Centre (H3D), who recently enlisted the help of UCT eResearch to automate parts of her data management process, reducing tasks that would have taken her an entire day to one or two hours.
Seddon runs biological tests, known as assays, to screen compounds from various research projects. “On any given day I run around 200 assays,” she says. “Each run has at least 30 plates, which represent around 210 compounds. Each compound has at least 12 data points. So that is a lot of data.”
In order to process the data, Seddon must upload it to an online database. But before she does that, she has to convert the data into the correct format to be uploaded. Previously, Seddon had to copy and paste information repeatedly into a spreadsheet to obtain pre-processed data to feed into the online database, a laborious and time-consuming process with a large margin for error.
Using Python, a programming language popular in the scientific community, the eResearch team wrote a script to automate that manual pre-processing step.
For Seddon, the eResearch intervention has made a world of difference. “This automation has resulted in a minimum of 75% of my time saved.”