A company providing purpose-built software for biopharma data management has emphasized the importance of centralized data handling for process development in the era of AI and big data.
According to Michael Barnes, lead solutions consultant at IDBS, life science companies could be leaving $180 billion on the table from failing to fully adopt digital solutions (according to a McKinsey survey).
A major contributor, according to the survey, is a lack of integrated data sources. And Barnes believes this can be tackled in process development by using centralized platforms for managing data and more refined, intelligent tech transfer.
“A centralized platform to integrate data sources is the number one point to realize the money available,” he explains.
He adds that, “[Companies also] need to move from a traditional tech transfer, which can be costly and time-consuming, to tracking process development from early on.”
Barnes, who spoke at BioProcess International in September, explains that IDBS’ vision is to create an ecosystem of software, which can be used to track the evolution of a process.
This might include recording when experiments didn’t work and providing context for the final process, creating big data for reports and later AI analyses, he says.
“What I’m proposing is to break down walls, make it easier for the end user, and ultimately help [them] to make better decisions.”
The centralized data management could incorporate existing Electronic Laboratory Notebook (ELN) and Laboratory Information Management (LIM) systems, or bespoke capabilities.
Barnes is also keen to talk about streamlining tech transfer, which currently he compares to” throwing” data ”over the wall” from process development into manufacturing.
“What I’m proposing is sending information in a better documented and more streamlined format,” he says.
“If it’s more transparent and easier to access from the manufacturing side, then that leads to a ton of cost savings.”
Streamlining data for tech transfer could include associating the data and results from an experiment, rather than just passing over an ELN, or keeping a repository of all parameters, set points, and raw materials, he says.
