May 9, 2025
[Press Release] Digitalization of Process Design for Stem Cell Culture in Regenerative Medicine — Experimental Validation of a Design Space Based on Mathematical Modeling —
A collaborative research team consisting of Prof. Hirokazu Sugiyama, Assistant Prof. Yusuke Hayashi, and graduate student Dr. Keita Hirono from the Department of Chemical System Engineering, Graduate School of Engineering, The University of Tokyo; Associate Prof. Ryuji Kato and Assistant Prof. Kenjiro Tanaka from the Graduate School of Pharmaceutical Sciences, Nagoya University; and Prof. Masahiro Kino-oka and colleagues from the Graduate School of Engineering, Osaka University has successfully developed a novel algorithm to determine the design space (DS) for the culture process of mesenchymal stem cells (MSCs), which are widely used in regenerative medicine, and has experimentally validated the identified DS.
In recent years, pharmaceutical manufacturing based on design space (DS) has gained increasing importance. However, MSC culture processes involve complex phenomena associated with living cells, making it extremely difficult to identify DS using conventional experimental approaches alone. Although mathematical model-based approaches have been suggested as effective for determining the DS of MSC culture processes, there has been a lack of sufficient experimental validation of the identified DS.
In this study, the research team developed a new algorithm that enables DS determination by simultaneously considering the dynamic characteristics and variability of cell proliferation. This was achieved by integrating a physics-based model derived from mass balance principles with statistical prediction intervals of model parameters. Furthermore, the validity of the DS identified through simulations was successfully verified through experimental studies.
This algorithm enables the identification of DS within a digital space, and is expected to contribute to rapid and efficient process design without reliance on trial-and-error experimentation, as well as to the commercialization of stem cell-based products.
The results of this study were published online in the open-access journal Communications Biology on May 8, 2025 (18:00 JST).
Nagoya University website: Press Release (in Japanese)
Key Points
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A novel algorithm was developed to determine the “design space,” defined as the operational conditions that ensure quality, for the culture process of mesenchymal stem cells, a key cell source in regenerative medicine.
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By combining a physics-based model derived from mass balance with statistical prediction intervals of model parameters, the study successfully identified a design space that accounts for both the dynamic behavior and variability of cell proliferation, and experimentally validated its reliability.
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The proposed algorithm enables the determination of design space in a digital environment through simulation, contributing to rapid and efficient process design and facilitating the commercialization of stem cell products.
Terminology
(1) Mesenchymal Stem Cells (MSCs): Stem cells present in various tissues in the body, characterized by self-renewal capability and the ability to differentiate into bone, cartilage, adipose tissue, and others, as well as immunomodulatory functions. They are considered an important cell source for regenerative medicine.
(2) Design Space (DS): A multidimensional combination of input variables and process parameters that has been demonstrated to assure quality. Defined in the ICH guideline Q8(R2) on pharmaceutical quality.
(3) Physics-based Model: A model described based on physical, chemical, and biological principles. Typically expressed using differential equations, such models offer high reliability and strong extrapolation capability when the system is well understood. However, constructing such models can be difficult when system understanding is insufficient.
(4) Prediction Interval: An estimated range within which future observations are expected to fall with a certain probability, based on a sampled population.
Funding
This research was conducted as part of the project “Development of QbD-based control strategies for manufacturing human cell-processed products and establishment of a core ecosystem” (Grant Number: JP20be0704001), under the AMED program “Development of Fundamental Technologies for Industrialization of Regenerative Medicine and Gene Therapy (QbD-based Manufacturing Platform Development),” led by Prof. Masahiro Kino-oka.
