M-Star Simulations & Pfizer Offer Advanced Modeling Strategies To Accelerate Vaccine Development, Scale-up & Tech Transfer

ELLICOTT CITY, Md., Nov. 9, 2021 /PRNewswire/ -- The global response to the COVID-19 pandemic triggered an unprecedented demand for a faster, safer and more flexible biopharmaceutical manufacturing solution. In response to this challenge, bioprocess researchers and engineers from M-Star Simulations, LLC, and Pfizer, Inc., recently published the article "Modeling Mass Transfer in Stirred Microbioreactors" in Chemical Engineering Science. The article outlines advanced modeling strategies that helped Pfizer accelerate its vaccine and other drug development process, from product scale-up to tech transfer for contracted production, using M-Star CFD (computational fluid dynamics) software.

While safety, quality and efficacy are of primary importance in drug development and manufacturing, velocity of these efforts in scaling up production capacity is critical. Quick, reliable, cost effective and good manufacturing practice (GMP)-compliant technology platform development, with understanding and optimization of processes as they move from lab scale to industrial scale, support safe and effective vaccines and drugs to be delivered to everyone worldwide, with speed. But as a pharmaceutical company moves from small scale to large scale to increase production capacity, the physics, chemistry and biology within the unit operations need to be well understood. 

Drug and vaccine development scientists typically perform a large set of experiments due to the extensive range of operating parameters. Once an appropriate set of operating conditions is identified, the fluid mechanical environment realized in a microbioreactor must be reproduced at large production scales. 

M-Star CFD software handles fluid dynamics simulations with millions of individually tracked bubbles, allowing biopharma companies to model complex bioreactor physics problems – including mass transfer and multiphase fluid flow – accurately and in minutes.

The Chemical Engineering Science article explains a generalized framework for modeling mass transfer in two-phase stirred-tank bioreactors. Using predictive tools like M-Star CFD can reduce the number of experiments and streamline the scale-up process. It can also make it easier to replicate the process with contract manufacturers of a vaccine or drug.

"The approach we present in the Chemical Engineering Science article can be utilized as a digital scape-up and tech-transfer strategy for bioreactors used in the biopharma industry," says John A. Thomas, Ph.D., President, M-Star Simulations. "M-Star CFD creates a 'digital twin' with computational fluid dynamics to validate things other CFD tools cannot. I am proud that our software helped advance Pfizer's COVID-19 vaccine and other vaccines and drugs with companies like AbbVie, AstraZeneca and Bristol Myers Squibb."

The Chemical Engineering Science article is authored by Hooman Yadollahi Farsasni of Bioprocess Research and Development, Pfizer, Inc.; Johannes Wutz, Brian Devincentis and John A. Thomas of M-Star Simulations; and Seyed Pouria Motevalian, formerly with Pfizer (now with Thermo Fisher Scientific).

About M-Star Simulations, LLC

M-Star Simulations, LLC, is a software company focused on the development of computational tools for modeling momentum, energy and mass transport within engineering and biological systems. By pairing modern algorithms with graphical processing card (GPU) architectures, this software enables users to quickly perform calculations with predictive fidelity that rivals physical experiment. These outcomes are achieved using a simple graphical interface that requires minimal user specification and setup times. Founded in Maryland in 2014, M-Star Simulations has grown to include commercial, government and academic users across North America, South America, Europe and Asia. For more information, visit https://mstarcfd.com/.

CONTACT: Patty Pologruto, [email protected]

SOURCE M-Star Simulations

Related Links

http://mstarcfd.com/