UC Berkeley

Organ transplantation represents one of the greatest medical advancements of the past century and is often the final option for patients suffering from end-stage organ disease. Despite our ability to perform these lifesaving operations, our simple inability to preserve organs for extended periods during ex vivo handling has caused immense logistical constraints that result in a majority of otherwise healthy donor organs not being transplanted. The current clinical standard for organ preservation, static cold storage, takes advantage of the Arrhenius temperature dependence of metabolism by placing organs on ice in order to slow expiration but enables just a few hours of viable preservation. Lower temperatures could further suppress metabolism and extend preservation, however ice crystallization results in irreversible damage. Being an activated process, freezing does not occur immediately at the equilibrium phase transition temperature, allowing water to remain metastably supercooled below 0°C. By preserving an organ in a supercooled state, the metabolism suppressing benefits of lower temperature can be attained while entirely avoiding ice formation. Ice crystallization is initiated by heterogeneous nucleation however, which is an inherently random process whose rate scales unfavorably with temperature, volume, and supercooled duration. This unpredictability poses significant challenges to the advancement and ultimate clinical translation of supercooled preservation techniques. This thesis has two primary objectives. The first is to identify methods, such as aspects of device and preservation solution design, that increase stability of supercooled systems. This involves both the development of new experimental tools necessary for probing supercooling stability and accompanying mathematical models for contextualizing key observations, such as the effect of rigid confinement. The second objective is to develop models to characterize the inherent stochastic nature of heterogeneous nucleation. These models enable prediction of freezing probability as a function of temperature, supercooled duration, volume, and solution composition. Ultimately, by applying engineering methods to understand the underlying molecular processes and model stochastic nucleation processes, these efforts establish a framework that enables the rational design of robust supercooled preservation protocols.