A joint project between Takeda, the Research Center Pharmaceutical Engineering (RCPE), the technology company InSilicoTrials and the University of Graz will allow one of the world’s largest pharmaceutical companies to increase scientific understanding of current and future manufacturing process while accelerating the go-to-market of new drug formulations.
The 36-month joint project has been initiated to establish the mechanistic basis of the relationship between process parameters and the effect of the resulting stresses on the characteristics of protein-based drugs. Takeda and RCPE are in the process of building an ongoing partnership which has been and is currently being used to increase the scientific knowledge for biopharmaceutical products and processes.
Biopharmaceuticals represent one of the fastest growing segments in current drug pipelines, but their large-scale manufacturing and processing pose specific challenges to the drug formulation scientist, as these large and complex molecules are sensitive to variations of environmental conditions and process-induced stress. Filling is the final step of the manufacturing process for liquid protein formulations and the focus of the project.
The project will enhance the understanding of the process-induced mechanisms for protein-based biopharmaceuticals. It will also support product and process development of protein-based drugs in the future, resulting in reduced material requirements and drug development timelines.
The collaboration will adopt an innovative approach between Takeda and the partner companies where a lab scale version of one of Takeda’s filling line will be designed and assembled. The line will be used to simulate the Takeda filling process on a smaller scale, comparing the effect of various settings of process parameters (filling speed, vial shape, protein concentration etc). In addition, computational fluid dynamics simulations will be performed to estimate the shear forces, as well as size and dynamics of interfaces the concentrated protein solution is exposed to during the filling process. The generated experimental and simulation data will then be 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 the protein molecule. The final 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 will be handled through the simulation platform of InSilicoTrials, a start-up specialised in modelling and simulation based on cloud technologies for scientific data management, pharmaceutical and biomedical research and development.
DI Karl-Heinz Hofbauer, Site Head Takeda Vienna said: “Our innovative approach to continuously improving our processes is demonstrated by partnerships like this one. With this project, we aim to improve our manufacturing process while reducing costs and accelerating the development of new drug formulations – in the service of our patients.”
Luca Emili, CEO of InSilicoTrials said: “The opportunity to use the platform that we developed for modelling and simulation will allow a quick and efficient data management activity, a key factor for this project. Leveraging the potential of a cloud-based SaaS platform is an element of huge acceleration of activities that, until recently, required complex and heavy processes of data handling. The researchers at Takeda, RCPE, InSilicoTrials and the University of Graz will be able to cooperate and benefit from cutting-edge, high-performance and reliable features.”
Dr. Thomas Klein, CEO and business director of RCPE said: “The machine learning algorithm we are going to develop will allow Takeda to narrow down the process parameters in-silico and focus on a few targeted experiments.”