Computational prediction of blend time in a large-scale viral inactivation process for monoclonal antibodies biomanufacturing

Chadakarn Sirasitthichoke, Duc Hoang, Poonam Phalak, Piero M. Armenante, Barak I. Barnoon, Ishaan Shandil

Research output: Contribution to journalArticlepeer-review

Abstract

Viral inactivation (VI) is a process widely used across the pharmaceutical industry to eliminate the cytotoxicity resulting from trace levels of viruses introduced by adventitious agents. This process requires adding Triton X-100, a non-ionic detergent solution, to the protein solution and allowing sufficient time for this agent to inactivate the viruses. Differences in process parameters associated with vessel designs, aeration rate, and many other physical attributes can introduce variability in the process, thus making predicting the required blending time to achieve the desired homogeneity of Triton X-100 more critical and complex. In this study we utilized a CFD model based on the lattice Boltzmann method (LBM) to predict the blend time to homogenize a Triton X-100 solution added during a typical full-scale commercial VI process in a vessel equipped with an HE-3-impeller for different modalities of the Triton X-100 addition (batch vs. continuous). Although direct experimental progress of the blending process was not possible because of GMP restrictions, the degree of homogeneity measured at the end of the process confirmed that Triton X-100 was appropriately dispersed, as required, and as computationally predicted here. The results obtained in this study were used to support actual production at the biomanufacturing site.

Original languageEnglish (US)
JournalBiotechnology and Bioengineering
DOIs
StateAccepted/In press - 2022

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Bioengineering
  • Applied Microbiology and Biotechnology

Keywords

  • bioprocess
  • blend time
  • CFD analysis
  • large scale manufacturing
  • viral inactivation

Fingerprint

Dive into the research topics of 'Computational prediction of blend time in a large-scale viral inactivation process for monoclonal antibodies biomanufacturing'. Together they form a unique fingerprint.

Cite this