Computational optimisation of slow cooling profiles for the cryopreservation of cells in suspension
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866911336076673024 |
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| author | Jennings, Jack Lee Bojic, Sanja Breitwieser, Lukas Sharpe, Alex Bauer, Roman |
| author_facet | Jennings, Jack Lee Bojic, Sanja Breitwieser, Lukas Sharpe, Alex Bauer, Roman |
| contents | The cryopreservation of biological materials is a highly complex process, as it involves numerous factors such as the cooling and thawing procedures, the administration of cryoprotective agents (CPAs), as well as the type and composition of cells. While theoretical work has yielded a better understanding of the processes occurring during cryopreservation, the design of cryopreservation protocols and their parameters is currently predominantly based on heuristic optimization. Here, we propose a mathematical method to optimise the cooling dynamics in slow-cooling, to reduce the risk of injury. We derive our method from first principles and provide computational predictions. Moreover, we assess the predictions with data obtained from the literature, as well as novel experimental results. Overall, we provide a generic computational approach to generate improved slow-cooling profiles for the cryopreservation of cells in suspension. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_20805 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Computational optimisation of slow cooling profiles for the cryopreservation of cells in suspension Jennings, Jack Lee Bojic, Sanja Breitwieser, Lukas Sharpe, Alex Bauer, Roman Other Quantitative Biology The cryopreservation of biological materials is a highly complex process, as it involves numerous factors such as the cooling and thawing procedures, the administration of cryoprotective agents (CPAs), as well as the type and composition of cells. While theoretical work has yielded a better understanding of the processes occurring during cryopreservation, the design of cryopreservation protocols and their parameters is currently predominantly based on heuristic optimization. Here, we propose a mathematical method to optimise the cooling dynamics in slow-cooling, to reduce the risk of injury. We derive our method from first principles and provide computational predictions. Moreover, we assess the predictions with data obtained from the literature, as well as novel experimental results. Overall, we provide a generic computational approach to generate improved slow-cooling profiles for the cryopreservation of cells in suspension. |
| title | Computational optimisation of slow cooling profiles for the cryopreservation of cells in suspension |
| topic | Other Quantitative Biology |
| url | https://arxiv.org/abs/2512.20805 |