| 研究課題/領域番号 |
22K14535
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| 研究種目 |
若手研究
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| 配分区分 | 基金 |
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| 審査区分 |
小区分27020:反応工学およびプロセスシステム工学関連
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| 研究機関 | 東京大学 |
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研究代表者 |
バドラ サラ・サミール・レヤド 東京大学, 大学院工学系研究科(工学部), 准教授 (20842206)
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| 研究期間 (年度) |
2022-04-01 – 2025-03-31
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| 研究課題ステータス |
交付 (2023年度)
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| 配分額 *注記 |
4,550千円 (直接経費: 3,500千円、間接経費: 1,050千円)
2024年度: 1,170千円 (直接経費: 900千円、間接経費: 270千円)
2023年度: 1,950千円 (直接経費: 1,500千円、間接経費: 450千円)
2022年度: 1,430千円 (直接経費: 1,100千円、間接経費: 330千円)
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| キーワード | Freeze drying / Process optimization / Biopharmaceuticals / Modelling / Process design / Hybrid modelling / freeze-drying / process optimization / mechanistic modelling / cake collapse |
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| 研究開始時の研究の概要 |
This work develops multiscale hybrid models to rationalize the design and operation of freeze-drying processes. The models can be used for process optimization, failure detection to improve supply robustness of biopharmaceuticals, and further to increase the flexibility of drug distribution.
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| 研究実績の概要 |
Freeze drying is essential to allow the storage and distribution of unstable biopharmaceuticals, e.g., therapeutic proteins. However, the process is time-and resource-intensive. This research aims to provide design and operation improvements to save production time without affecting product quality. Collaborations with industrial partners were established. The collected data from was used to develop process models for different operations, e.g., drying. The drying process is one of the most time-consuming steps and vulnerable to issues affecting the product quality. An index was developed relating product quality issues with changes in physical properties for standard materials used as additives.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
2: おおむね順調に進展している
理由
The work is progressing according to plan. Vial scale models have been developed for the drying process. An index for product quality has been developed. Collaborations with industrial partners are proceeding smoothly.
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| 今後の研究の推進方策 |
In the future, the model will be integrated with the quality index to optimize the freeze-drying operation and provide a guide based on material properties and process conditions. Process optimization using the developed integrated model will take place.
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