A joint project by Takeda Pharmaceutical Research Center (RCPE), technology company InSilicoTrials, and the University of Graz has allowed one of the world’s largest pharmaceutical companies to gain a scientific understanding of current and future manufacturing processes while at the same time marketing new drug formulations.
A 36-month collaborative project was initiated to lay the foundation for the mechanism of the relationship between process parameters and the effects of consequent stress on the properties of protein-based drugs. Takeda and RCPE are in the process of building an ongoing partnership that has been and is currently in use to enhance scientific knowledge of biopharmaceutical products and processes.
Biopharmacy is one of the fastest growing areas of the current pharmaceutical pipeline, but it is so large because these large and complex molecules are sensitive to changes in environmental conditions and the stress of processes. Large-scale manufacturing and processing poses specific challenges for pharmaceutical scientists. Filling is the final step in the manufacturing process of liquid protein formulations and is the focus of the project.
This project will deepen our understanding of the mechanisms resulting from protein-based biopharmacy processes. It will also support the development of protein-based drug products and processes in the future, reducing material requirements and drug development timelines.
This collaboration takes an innovative approach between Takeda and its partners to design and assemble one lab-scale version of Takeda’s filling line. This line is used to simulate the Takeda filling process on a small scale, comparing the effects of various settings of process parameters (filling rate, vial shape, protein concentration, etc.). In addition, computational fluid dynamics simulations are run to estimate shear forces and the size and dynamics of the interface to which the concentrated protein solution is exposed during the filling process. The experimental and simulation data generated is used to train and test algorithms based on state-of-the-art machine learning models to predict the potential impact of these parameters on the properties of protein molecules. The ultimate goal is a set of in silico tools that can be used to guide the design and parameterization of the filling process.
The process data generated during the project is processed through the simulation platform of InSilico Trials, a startup specializing in cloud technology-based modeling and simulation for scientific data management, pharmaceutical and biomedical research and development.
DI Karl-Heinz Hofbauer, site director for Takeda Vienna, said: The project aims to improve the manufacturing process while reducing costs and accelerating the development of new drug formulations that serve patients. “
Luca Emili, CEO of InSilicoTrials, said: “The opportunity to use a platform developed for modeling and simulation enables fast and efficient data management activities that are a key element of this project. Taking advantage of the potential of a cloud-based SaaS platform Until recently, it was a significant acceleration factor for activities that required complex and heavy processes of data processing. Researchers at Takeda Yakuhin, RCPE, InSilicoTrials, and Gratz University collaborated to provide state-of-the-art, high-performance, reliable features. You can benefit from. “
Dr. Thomas Klein, CEO and Business Director of RCPE, said: “The machine learning algorithms we develop allow Takeda to narrow down process parameters in in silico and focus on a few targeted experiments.”
Takeda and Biopharmacy Technology Startup Partners
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