By Dr. Ramnath Babu
Cryopreservation encompasses the freezing of biological materials, such as cells, tissues, and even whole embryos, for long-term storage. It forms a vital part of both biobanking and fertility treatment and is thus, an enabling technology in medical research. Long-term viability depends on a long regime of constant vigilance and often very precise controls of the storage conditions. However, over the last few years, AI has emerged as a transformative technology in this domain, with 24/7 vigilant monitoring fundamentally reshaping how cryopreservation facilities operate.
Traditional cryopreservation monitoring has relied on manual checks and rudimentary automated systems that track temperature, liquid nitrogen levels, and other key parameters. While these methods have been reasonably effective to a certain degree, they have their drawbacks. Manual monitoring is an extremely time-consuming and error-prone job; moreover, it always misses minor fluctuations that might take away the biological integrity of the samples.
It is here that AI intervenes with a real-time, continuous monitoring system for cryopreserved samples with unparalleled accuracy. Advanced sensors and machine learning algorithms are put into use by AI-driven systems to continuously monitor the environment of storage in progress and detect even the most minute deviations from optimal conditions.
Probably the biggest flex of AI in cryopreservation is its predictability. Algorithms can analyze historical patterns using AI and show patterns likely to precede a problem. This, for example, enables AI to predict when liquid nitrogen levels are approaching the critically low level, based on patterns of use and gives staff a warning. This proactive approach arrests any form of emergency and ensures that the integrity of all the samples stored remains intact.
AI-enhanced cryopreservation monitoring systems showed a reduction in damage by a huge margin than traditional methods. The same study reported that AI systems further increased the general productivity of cryopreservation facilities as fewer resources were required to maintain optimal conditions.
Furthermore, since AI can work tirelessly without fatigue or oversight, cryopreservation facilities can be in a constant state of vigilance. This is particularly the case for large biobanks that can store several thousand samples and face an extremely high level of stakes. AI monitoring across such facilities ensures that literally every single sample is looked after 24/7, irrespective of any changes in staffing levels or other operational challenges.
AI monitoring also contributes to better regulatory compliance and management of data. AI systems automatically log all relevant data; therefore, they provide a full audit trail in real-time, which simplifies compliance and reduces the risk of penalties. Such automated record-keeping further aids continuous improvement studies since facilities can easily analyze performance data and identify areas for enhancement.
AI-driven cryopreservation monitoring is setting new standards for the field, enabling all-day and all-night vigilant watch over stored samples. This development therefore serves to enhance not only safety and reliability in cryopreservation but even opens new frontiers in research and medicine, further extending toward fertility treatments. As AI technology continues on its growth path, it also becomes ever-more integrally positioned in cryopreservation, leading toward an era of unprecedented security and efficiency for biobanking.
This article is written by Dr. Ramnath Babu T J, Co-Founder & CEO at SpOvum┬о Technologies.
(DISCLAIMER: The views expressed are solely of the author and ETHealthworld.com does not necessarily subscribe to it. ETHealthworld.com shall not be responsible for any damage caused to any person/organisation directly or indirectly)
