Automated Sample Thawing System Using Derivative-Based Thaw Detection
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Solution Overview
Problem
Current methods for thawing cryogenically preserved cells lack standardization and consistency, leading to variability in cell recovery due to reliance on manual techniques and equipment that differs between laboratories, resulting in inconsistent thawing profiles and potential cell damage from temperature gradients and cryoprotectant toxicity.
Innovation Solution
A system utilizing sensors and algorithms to predict and control the thawing process, maintaining consistent and uniform conditions, including a container for thermal equilibration and a warming block with a microprocessor to manage temperature, ensuring precise control of the thawing phase and minimizing exposure to elevated temperatures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual thawing methods are used with varying equipment between laboratories, then ease of operation is improved, but manufacturing precision and reliability of cell recovery deteriorate
Solution Approach 1:
The system performs self-monitoring and self-regulation of the thawing process through integrated temperature sensors and microprocessor control, automatically adjusting heating parameters to maintain optimal thawing conditions without requiring manual intervention or specialized operator skills
Solution Approach 2:
The system dynamically adjusts temperature parameters during the thawing process based on real-time feedback from temperature sensors, transitioning from rapid initial thawing to controlled final stages to prevent temperature gradients and ensure consistent cell recovery across different operating conditions
2Productivity
If rapid thawing is performed by increasing bath temperature, then productivity is improved, but object-affected harmful factors worsen due to temperature gradients and cryoprotectant toxicity
Solution Approach 1:
The system employs dynamic temperature control that adjusts heating intensity based on the real-time thermal state of the sample, using high power initially for rapid thawing then reducing power as the sample approaches the target temperature to eliminate temperature gradients and reduce cryoprotectant toxicity
Solution Approach 2:
Temperature sensors continuously monitor the sample temperature and provide feedback to the microprocessor, which adjusts heating parameters in real-time to maintain optimal thawing conditions and prevent harmful temperature gradients and excessive cryoprotectant exposure
3Reliability
If standardized automated thawing is implemented, then reliability and manufacturing precision are improved, but device complexity increases
Solution Approach 1:
The system integrates multiple functions including heating, temperature monitoring, process control, and data recording into a single multi-functional device, eliminating the need for separate equipment and reducing overall system complexity while maintaining high reliability and standardized operation
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides a standardized, automated, and consistent thawing process, reducing cell damage and variability, thereby enhancing cell recovery by precisely controlling the thawing temperature profile and minimizing exposure to cryoprotectant toxicity.
Implementation Method 1
heating a warming block and receiving the sample container within the warming block
Implementation Method 2
A contact surface of the sample holder that is in physical contact with the outer surface of the sample vessel may be heated to a constant temperature
Implementation Method 3
The pliable material and the non-pliable material may be permanently bonded together
Data Source
AI summary
The present invention generally relates to thawing a cryogenically frozen sample. The systems, devices, and methods may be used to heat a sample holder, the sample holder configured to receive a sample container holding the frozen sample. A sample thaw start time may be identified by measuring a temperature of the sample container and/or a temperature of the sample. A sample thaw end time may be calculated as a function of the sample thaw start time. In some embodiments, the same thaw start time may be identified by a significant change in a first derivative of a warming curve of recorded temperature measurements. The sample end time may be calculated by adding a constant to the sample thaw start time. The constant may be the average sample thaw time per the sample container.