Computational optimisation of slow cooling profiles for the cryopreservation of cells in suspension

Fuente: arXiv
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Bibliographic Details
Main Authors: Jennings, Jack Lee, Bojic, Sanja, Breitwieser, Lukas, Sharpe, Alex, Bauer, Roman
Format: Preprint
Published: 2025
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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