Alongside beakers, pipettes and microscopes, another set of tools has become indispensable in today’s laboratories: computerized, networked systems that allow scientists to monitor experiments in real time, make decisions faster and share results easily.
At CSL’s Parkville headquarters, business systems analyst Alistair Grevis-James draws on his expertise in biochemistry, data science and IT to make sure researchers can use technology to push their work further.
“There used to be a clear distinction between science and information technology,” said Grevis-James. “For today’s scientists, that line doesn’t exist anymore.”
Now that biology and medicine work at the level of molecules – where a single strand of DNA is 3 billion letters long – it’s becoming routine to use the tools of data science for working with the substantial amounts of information.
And the first step is taking care of the data.
“There is huge interest and potential in big data and machine learning and artificial intelligence, but all of these technologies rely on correctly gathering and storing data.”
Grevis-James took a roundabout path to where he is. After completing a chemistry degree, he spent a year on a biochemistry research project at Melbourne’s Bio21 Institute. Next, he took a year away from the lab, travelling around Western Australia as a science communicator delivering presentations at schools and public venues designed to inspire public interest in science.
He returned to chemistry in 2014, working at a commercial lab in Sydney where he analyzed the contents of different foods to gather the data for nutrition panels on food labels.
In 2016, he came to work at CSL as an analytical biochemist. He was working on biopharmaceutical products to treat hemophilia and the effects of diabetes.
That’s when he really began to appreciate how important data has become.
“You have to think just as much about your data as about your experiment,” Grevis-James said.
So he returned to study in the evenings – starting a Master's degree in data science at the Royal Melbourne Institute of Technology (RMIT) in 2017 – and a year later moved into the business systems unit at CSL.
And at the same time, Grevis-James has had to build his skills in traditional information technology (IT) areas such as networking and data storage.
“At the moment we are really focusing on connectivity. For example, we make sure new instruments can link to the network. It gives better version control and you don’t have to be emailing data around or taking USB sticks to the lab.”
Keeping data in central repositories also makes it easier for researchers to see what others have done in the past. It means less duplication of work and more data for analysis, plus it saves a lot of time.
Grevis-James is also one of the leaders of a group called Master Our Data at CSL. One of the group’s first initiatives is teaching researchers how best to take care of their data and giving programming tutorials. There has been a strong response, he said.
“Data science follows the same process as biology or chemistry, or any other scientific discipline. You formulate a hypothesis, conduct experiments and figure out how things work.”