Advances in process modeling have given industry the tools to better understand the complex operations used to make medicines. The challenge now is understanding how best to combine the various modeling techniques that are available.
Drug makers have embraced modeling, according to Arne Stably, PhD, senior principal scientist at Novo Nordisk.
“Most, if not all companies are employing modeling for process development and manufacturing to various degrees,” he says. “The benefits of modeling vary from company to company and may include increased process understanding and control, optimized process steps and improved process economy, optimized production scheduling, and improved facility utility.”
Stably and colleagues examined the modeling options available to the biopharmaceutical industry in a recent paper to characterize the current landscape and identify areas for improvement. Some approaches like biophysical modeling, which looks at interactions on the molecular level, are well established and widely employed in the discovery lab and in downstream processing operations.
Mechanistic modeling, in contrast, is used primarily in manufacturing Stably says, explaining the approach “provides drug makers with tools for unit operation trouble shooting, process development, and identification of worst-case conditions.”
He also cites computational fluid dynamics as a popular modeling tool. “CFD is used to describe flow and mixing processes, including in fermentation and formulation tanks, and is important during scaleup to ensure ideal mixing,” he continues. “The tools help industry to design proper geometries for tanks, propellers, tubing etc. and to avoid dead spots.”
A more recent trend has seen biopharmaceutical companies seeking to combine modeling approaches to gain a better understanding of the entire process.
“Plant modeling utilizes the sum of the previous three tool models [biophysical, mechanistic, and computational fluid dynamics] combined with statistical empirical models for some unit operations to establish an overall model of a given facility,” says Stably. “Plant models may thus provide a digital twin that may be used by manufacturers for numerous purposes. including de-bottlenecking, impact of implementation of new alternative technologies, and facility design.”
How well a company can embrace plant modeling is largely dependent on resources, he adds.
“In general, companies have different abilities statistical vs mechanistic modeling, and implement accordingly. On the more operational level, ensuring enough qualified workforce and skills combined with management attention are required to secure a proper and improved implementation of modeling in the industry,” he says.
“Successful implementation of a hybrid process modeling strategy depends on having qualified personnel with the requisite engineering skills as well as a corporate culture that understands the value of innovation.”