Models of biopharmaceutical production processes are more accurate and predictive if all downstream steps are considered together rather than individually. At least that’s according to researchers at Boehringer Ingelheim and the Karlsruhe Institute of Technology (KIT) in Germany. The researchers looked at how mechanistic models—mathematical process representations that incorporate both data and fundamental laws of natural sciences—could be improved.
They focused on downstream unit operations like chromatography and filtration, setting out to determine how these processes are modeled at present. The key finding is that, while current modeling approaches can contribute to understanding of downstream processing steps, their accuracy is reduced when each unit operation is considered separately.
“Mechanistic modeling has been shown to contribute greatly to the process understanding of chromatography and filtration processes,” write the investigators. However, these are mostly considered individually and not connected for an entire downstream process.”
Instead, the researchers linked models for each operation into an in-silico representation of all post-bioreactor steps—termed a “connected mechanistic process model” (CMPM)—in a bid to provide a more accurate representation of an antibody fragment production process.
And the results were promising, according to the authors, who noted: “The presented downstream process model could predict online and offline data recorded at 12,000 L manufacturing scale. Process variations of twenty-three manufacturing batches were adequately reproduced by the model based on the consideration of input process parameter variations.”
They concluded: “This study shows a downstream process can be represented by a CMPM, which opens unexplored possibilities to accelerate the process development whilst saving resources.”
Efficiencies
More accurate models have the potential to make production processes more efficient, which is a particular focus for drug companies making antibody-based therapies, according to the authors.
“Antibody-based therapy for cancer has become one of the most successful and important strategies for treatment of various tumors. However, the biopharmaceutical industry is experiencing an increasingly competitive environment and thus a requirement for cost savings and efficiency,” according to the scientists, who add that linked models of downstream unit operations would also help manufacturers meet with regulators’ demand for more detailed process information, according to the authors.
“The connection of mechanistic models to a CMPM would allow in silico investigations of multidimensional combination and interaction of input variables and process parameters across unit operations.
“Consequently, a cross-process understanding emerges that would meet demands by the regulatory authorities,” they wrote, citing ICH Q8 (R2)—which covers the design, analysis, and control of biopharmaceutical manufacturing processes—as an example.
