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

TL;DR

This paper introduces a mathematical method to optimize slow-cooling profiles in cryopreservation, aiming to minimize cell injury by deriving from first principles and validating with literature and experimental data.

Contribution

It presents a novel computational approach for designing improved slow-cooling protocols in cell cryopreservation based on first-principles modeling.

Findings

The method predicts optimized cooling profiles that reduce cell injury.

Validation shows the approach aligns with literature data.

Experimental results support the computational predictions.

Abstract

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.