Method and system for cooling conditions of biological specimens

Abstract

To provide a new cooling device.SOLUTION: A computer-implemented method is disclosed, including the steps of: obtaining first data indicating electric power supplied to a cooling device during a cooling operation on a biological sample, the cooling operation having a given cooling condition; obtaining second data associated with a reference cooling condition; determining, based on the first data and the second data, whether the given cooling condition has a predetermined relationship with the reference cooling condition; and in response to a determination in the determining step that the given cooling condition has the predetermined relationship with the reference cooling condition, outputting a control signal. The given cooling condition for a "live" data cooling operation may thus be validated against the reference cooling condition.SELECTED DRAWING: Figure 1

Description

[Background technology]

[0001] Biological materials such as (for example) cells, vaccines and proteins often need to be preserved. For example, biological materials may need to be preserved so that they can be studied or used in scientific experiments at a later time. In another example, human oocytes or fertilized eggs may be preserved as part of an in vitro fertilization (IVF) process. In these examples, it is important that the biological material is preserved in such a way that damage or deterioration of the biological material is minimized. Freezing techniques are often used to preserve biological materials. There are various ways of freezing biological materials in order to preserve them. For example, cryopreservation is a process in which biological materials are frozen and then stored in a frozen state, while lyophilization is a process in which a biological sample is frozen and, following the freezing step, water is removed from the sample so that the sample is stored in a dry state.

[0002] Cryopreservation is a technique used to maintain the long-term viability of biological samples for later applications in medicine, biotechnology and veterinary medicine. Cryopreservation involves cooling samples to low temperatures, typically -196 degrees Celsius (°C) - the boiling point of liquid nitrogen - and potentially maintaining them at that temperature for extended periods of time. By cooling biological samples to -196°C, the rates of chemical and / or enzymatic reactions that might otherwise degrade the sample are slowed to such an extent that the sample is no longer degraded. In this way, biological samples can be stored for extended periods of time and then returned to ambient temperature as needed.

[0003] Cryopreservation is useful for cell and gene therapies, particularly immunotherapies. Effective clinical delivery of these therapies can employ a cold chain, e.g., a temperature-controlled supply chain that comprises a series of steps for the production, distribution, and storage of cryopreserved biological specimens.

[0004] During such a cold chain, an initial biological sample, e.g., containing biological cells, having a volume of (for example) 200 milliliters (ml) to 600 ml, may be frozen to allow shipment to a so-called manufacturing site. For clinical supply, the final cell therapy product, having a volume ranging from, e.g., 10 ml to 500 ml, may be cryopreserved to allow quality control of the cell therapy product to be performed, to enable patient scheduling, and to facilitate transport of the biomass to the bedside.

[0005] Relatively large volume cryopreservation can also be related to other biological samples, such as plasma, cell suspension, bone marrow (adult stem cells) and organoid system.Such relatively large volume cell suspension is routinely cryopreserved in cryopreservation bag or "freezing bag" (for example, 5ml to 1000ml full capacity).To protect freezing bag from mechanical damage during long-term storage, they can be sealed in another bag ("outer packaging") and / or put into metal cassette.

[0006] Other specialized freezing containers can be used to hold samples for cryopreservation, such as straws, which are thin-walled tubes, typically 2 mm to 4 mm in diameter, up to 140 mm in length and 0.2 ml to 0.5 ml in volume; cryovials, which are short tubes, typically with a wider diameter than a typical straw (e.g., 12.5 mm), and 0.5 ml to 5.0 ml in volume; as well as multi-well plates, matrix tubes, and other SBS (Society for Biomolecular Science) formats utilized in robotics, high throughput screening, etc.

[0007] To reduce cell damage during freezing and thawing, protective compounds (so-called "cryoprotective additives") may be added to the samples. A commonly utilized additive is dimethyl sulfoxide (DMSO), typically used at a concentration of 5% w / v to 15% w / v, where % w / v refers to mass concentration. Several other cryoprotective additives are known, such as glycols, including ethylene glycol, propylene glycol, and glycerol. [Brief description of the drawings]

[0008] [Figure 1] 1 illustrates a schematic diagram of an example cooling system. [Diagram 2] FIG. 1 is a flow diagram of an example method. [Diagram 3] 1 shows a representation of an example data series of power values ​​and corresponding temperature values. [Figure 4] 1 shows a schematic diagram of an example hardware architecture for performing the example methods described. [Diagram 5] 1 shows a schematic diagram of an example system with hardware for implementing the example methods described. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] The methods and devices presented herein perform monitoring of cooling operations performed on samples based on data indicative of power supplied to the cooling device during the cooling operation. Such data may be considered, in examples, as "live" data measured during monitoring of a live cooling operation and may be compared to the reference data to determine whether the cooling conditions of the cooling operation are substantially the same as or different from those of the reference data. The cooling conditions may include data for parameters such as sample volume; sample composition; number of samples; sample container size; sample container type; cooling device type; cooling rate; cooling profile; and / or initial temperature of the heat sink of the sample or cooling device. In this way, the cooling conditions (referred to elsewhere herein as given cooling conditions) or parameters thereof for a live cooling operation may be verified against the reference cooling conditions (or parameters thereof) to inform the user, for example, that the correct sample volume, sample composition, number of samples, as examples, are as expected with respect to the reference cooling conditions. In examples, if it is determined that the cooling condition values ​​of the live cooling operation are not substantially the same as the cooling condition values ​​associated with the reference data, an alert may be generated and transmitted (and / or stored as part of the generated report or log data) and / or the cooling operation may be stopped due to a determination that the sample being cooled in the live cooling operation is not as expected relative to the reference cooling conditions.

[0010] Such methods and devices may therefore be used in validating parameters of a biological sample, a cooling device and / or a cooling operation (which may be included as part of a given cooling condition) against the same parameters of a reference sample (which parameters may have been measured or entered for a hypothetical reference sample). This may be particularly useful for high value biological samples, for example those containing patient-specific cells for treatment of the patient, and which need to be handled with care.

[0011] In accordance with certain examples of the present method and apparatus, specific details are set forth in the following description to explain and elaborate on specific features thereof.

[0012] There are various devices for cooling or freezing samples. The sample may include a fluid or liquid, such as an aqueous solution, to be cooled or frozen. A sample containing biological material (or "living material", "biological medium") may be considered a biological sample. As described in more detail below, the sample may be contained in a container, such as a freezing container. The container may be, by way of example, a vessel, a test tube, a vial, a straw, a multi-well plate, a well, or a bag.

[0013] Such cooling equipment includes devices that utilize liquid nitrogen as a cryogen and devices that are cooled by mechanical refrigeration. Passive cooling devices also exist. Following freezing, the sample may be kept frozen (or "cryopreserved") at cryogenic temperatures, for example below -50°C or below -180°C, for example in the range of the boiling point of liquid nitrogen (-196°C). At around -196°C, the cell viability of the biological sample may be considered independent of the duration of storage of the sample, provided that the cells have survived the cooling step. When the cells need to be used, the biological sample may be thawed, for example in a water bath maintained at 37°C. Thawing may be more rapid than the cooling step. Before using the cryopreserved cells, for example for therapy, the cryoprotectant may be removed from the sample.

[0014] Biological samples, for example those containing cells, can be damaged or "injured" during cooling. For example, if ice nucleation occurs during cooling and ice crystals form, the biological material can suffer direct damage from the ice crystals, as well as damage caused by the increasing concentration of solutes in the sample as more and more ice forms.

[0015] Cooling a biological sample in a controlled manner can mitigate damage to biological material caused by such effects, thereby helping to preserve cell viability and function after thawing the sample for use. For example, a biological sample may be cooled at a controlled rate, which may be constant or may vary over time, according to a cooling protocol during the cooling operation.

[0016] The cooling protocol may be implemented by a cooling device, for example, included as part of a cooling system, such as a VIA Freeze™ instrument manufactured by Asymptote Limited. Some cooling systems blow cold gas onto the sample, which may cause a non-uniform cooling rate or profile (e.g., representing a change in cooling rate over time or temperature) across the sample or between samples if multiple samples are to be cooled by the cooling system. The VIA Freeze™ cooling system cools the sample by conduction under the sample, so every sample may experience the same cooling profile.

[0017] An example cooling (or "freezing") protocol programmable within the VIA Freeze™ cooling system may include a hold period a few degrees below the theoretical freezing point of the sample to absorb energy released from the latent heat of fusion. For example, if the theoretical freezing point is -3°C, the cooling protocol may include a hold period of 8 minutes at -10°C.

[0018] The cooling rate beyond the freezing transition may depend on the nature of the sample being frozen. This may be, for example, 0.3°C / min (degrees per minute) for certain types of cells and 2°C / min for others. If the cooling rate after freezing is too fast or slow, sample quality upon thawing, such as cell viability or function, may be severely compromised. Once frozen, for example to -80°C or -100°C, the sample may be removed from the VIA Freeze™ system and transferred to long-term frozen storage.

[0019] In known systems, the rate-controlled cooling action on the sample may be monitored by measuring the temperature within the sample or within the cooling device and / or cooling system. Such temperature measurements may be performed using one or more thermocouples and / or one or more resistance thermometers, e.g. made of platinum.

[0020] FIG. 1 illustrates an example cooling system 100 that includes a cooling device 110 for cooling a sample 105. The cooling system 100 may include a refrigerator or freezer device, such as a controlled rate freezer. In one example, the cooling device 110 includes a cryocooler that can be used to cool the sample 105, such as a biological sample, to a cryogenic temperature. A cryogenic temperature can be considered to be a temperature below −50° C. or below −180° C., such as the boiling point of liquid nitrogen (−196° C.), as discussed above. The sample 105 is contained in a container, a freezing bag in this example, and is positioned in contact with a thermally conductive plate 120 of the cooling device 110 in the example cooling system 100 illustrated in FIG. 1. The thermally conductive plate 120 is cooled by a “cold finger” 115 of the cooling device 110, which is the localized portion of the cooling device 110 that will be cooled during operation of the cooling device 110. In this manner, the specimen 105 may be cooled by conductive heat transfer from the specimen 105 to the plate 120 and from the plate 120 to the cold finger 115 during operation of the cooling apparatus 110. In such an example, the cold finger 115 and / or the conductive plate 120 may be considered to be a "heat sink" for the cooling apparatus 110, i.e., an area or portion of the cooling apparatus 110 that will absorb or withdraw thermal energy, for example, from the specimen 105, during a cooling operation on the specimen 105.

[0021] In other examples, the vessel containing the sample 105 may be positioned within a cooling chamber of the cooling device 110, e.g., an enclosed space into which a cryogenic fluid is introduced to surround and cool the sample 105 by convection. Examples of cryogenic fluids include helium, hydrogen, neon, nitrogen, air, fluorine, argon, oxygen, and methane. In such examples, the cooling chamber may be considered to be a heat sink for the cooling device 110.

[0022] Examples of cryocoolers that can be used as cooling device 110 include Stirling cryocoolers, "acoustic Stirling" cryocoolers, Klimenko cycle cryocoolers, pulse tube cryocoolers, and Joule-Thomson cryocoolers.

[0023] The cooling device 110 may perform a cooling operation on the biological sample 105, and the cooling operation may be associated with a cooling profile. A cooling profile may be a data set consisting of a target or goal temperature at a time interval of a cooling process. For example, a cooling profile may describe how, for example, the temperature of the sample 105 should change with time during a cooling operation. A target cooling rate, for example, a change in temperature over time, may be set at various stages of the cooling profile. In some examples, a constant target cooling rate may be set in the cooling profile.

[0024] The cooling profile or "temperature profile" may be pre-programmed into a control module 140 of the cooling system 100. The control module 140 may comprise control circuitry, including, for example, one or more processors and computer readable storage, and may be configured to control the operation of the cooling device 110. For example, the control module 140 may be coupled to the power source 130 of the cooling device 110, as shown in FIG. 1, and thus may regulate the amount of power provided to the cooling device 110 at a given time.

[0025] The power supply 130 of the cooling device 110 may convert electrical current from a source (e.g., from a power grid via an electrical outlet or from one or more energy storage devices, such as a battery, fuel cell, generator, or alternator) to provide electricity with appropriate characteristics (e.g., current, voltage, and / or frequency) to the cooling device 110 for powering the cooling device 110. The power supply 130 may in some examples be a separate, stand-alone device relative to the cooling system 100, while in other examples the power supply 130 may be part of, e.g., integrated into, the cooling system 100, as illustrated in FIG.

[0026] The control module 140 may adjust the amount of power provided from the power source 130 to the cooling device 110 based on a particular cooling profile that may be programmed into or obtained by the control module 140. For example, the control module 140 may receive temperature data from one or more temperature sensors or "probes," which in some examples represent the measured temperature of the specimen 105 and / or the cooling chamber at a given time during the cooling operation. The control module 140 may compare the received temperature data to a target temperature value according to the particular cooling profile at the corresponding time, and may adjust the power provided to the cooling device 110 based on the results of the comparison. For example, if the measured temperature at a given time is higher than the target temperature at the corresponding time according to the temperature profile, the control module 140 may increase the amount of power provided to the cooling device 110 to reduce the temperature of the entity being measured, such as the specimen and / or the chamber in the described example. Such comparisons and possible resulting adjustments may occur at predetermined times during the cooling operation and / or may occur at regular time intervals. In this manner, the control module 140 may track the cooling profile during cooling operation and adjust the amount of power provided to the cooling device 110 to follow the set cooling profile.

[0027] However, temperature measurements made within the sample 105 cannot provide any information regarding the volume of the frozen sample 105. For quality control of samples that are to be used clinically, such as samples that can be thawed and injected directly into a patient, it would be useful to ascertain the frozen volume.

[0028] Similarly, temperature measurements made at or within the sample container may not provide accurate information regarding the composition of the sample 105. Thermocouples placed near the ice nucleation site in a supercooled sample can provide sample composition information in a manner similar to a freezing point osmometer. However, at large distances from the ice nucleation site, temperature measurements may not provide accurate sample composition information. For quality control of cryopreserved samples, it would be useful to verify that the correct concentration of cryoprotectant was added to the sample 105 prior to freezing. Cell viability and function upon thawing may be compromised as a result of an incorrect amount of cryoprotectant being added, e.g., if its concentration in the sample 105 is too high or too low. The effectiveness of clinical treatments may also be compromised accordingly.

[0029] Furthermore, for samples that will later be used clinically, placing a temperature measurement probe into the sample 105 may not be possible, for example, due to the resulting contamination and / or the physical dimensions of the probe and sample 105 involved.

[0030] As described above, the methods and devices presented herein allow for validation of certain parameters of a biological sample, cooling device and / or cooling operation (which may be included as part of a given cooling condition) against the same parameters of a reference sample (which parameters may have been measured or input, for example, for a hypothetical reference sample).

[0031] The method and apparatus implement monitoring of a cooling operation based on data indicative of power supplied to a cooling device during a cooling operation performed on a sample. The data may consist of one or more power values, or one or more values ​​of parameters from which the power values ​​may be derived, such as, for example, voltage and / or current values. Such data may be measured during the cooling operation and compared to reference data to determine whether the cooling conditions of the cooling operation are substantially the same as or different from a reference cooling condition associated with the reference data. The cooling conditions or parameters thereof for the cooling operation may be checked against the reference cooling conditions (or parameters thereof) to inform a user that, for example, sample volume, sample composition, number of samples, etc., are as expected with respect to the reference cooling conditions. In one example, if it is determined that the cooling condition values ​​of the cooling operation are not substantially the same as the cooling condition values ​​associated with the reference data, a warning may be generated (e.g., transmitted and / or stored as part of a generated report or log data) and / or the cooling operation may be stopped due to a determination that the samples being cooled in the cooling operation are not as expected with respect to the reference cooling conditions.

[0032] The reference data may consist of a so-called "signature power curve" or "fingerprint power curve" associated with a reference cooling condition, where power values ​​were recorded during a cooling operation on a "reference sample". A cooling operation may have been performed with power values ​​and any associated parameter values ​​measured during the cooling operation. Alternatively, the cooling operation may be simulated and / or the reference data may be input without a cooling operation being performed. For example, the cooling operation and indeed the reference sample may be virtual. Once a cooling operation is performed on a biological sample, data indicative of the power supplied to the cooling device during the cooling operation may be obtained, for example according to any of the methods described herein, and compared against reference data, e.g., signature power curves, associated with one or more reference cooling conditions. Thus, as part of the method, based on the data indicative of the power supplied to the cooling device and the signature power curves of the reference cooling conditions, it may be determined whether a given cooling condition (of a cooling operation on a biological sample) has a predetermined relationship with a particular reference cooling condition. A given cooling condition and a particular reference cooling condition having or not having a predetermined relationship may be interpreted as a biological sample and a reference sample associated with a reference cooling condition having or not having a predetermined relationship, respectively. For example, if the predetermined relationship between entities "A" and "B" is that A and B are substantially the same, then a determination that a given cooling condition and a particular reference cooling condition are substantially the same may be interpreted as the biological sample and the reference sample being substantially the same. In the examples described herein, whether entities A and B, such as a given cooling condition and a reference cooling condition, are determined to have a predetermined relationship, e.g., are substantially the same, may depend on a predetermined threshold, which may be manually set. For example, a metric, such as a difference, determined based on A and B may be compared to a predetermined threshold. A determination that the metric is less than; less than or equal to; equal to; greater than; or greater than or equal to a predetermined threshold may indicate that A and B have a predetermined relationship, e.g., are substantially the same. A complementary determination, for example, that the metric is greater than or equal to; greater than; not equal to; less than or equal to; or less than, respectively, may indicate that A and B do not have a predetermined relationship, e.g., are not substantially the same. In some examples, the complementary determination may indicate two different predetermined relationships, respectively.For example, a complementary determination may indicate that A and B are substantially the same or substantially different.

[0033] Examples of methods and features thereof will now be described in detail, and some specific examples will be described with reference to FIGS.

[0034] 2 shows a flow diagram illustrating a method 200 that entails obtaining, at block 210, first data indicative of power supplied to a cooling device during a cooling operation on a biological sample having a given cooling condition. As described above, the first data indicative of power may consist of one or more power values ​​or may consist, for example, of one or more values ​​of electrical parameters from which power may be derived, such as voltage and / or current. The first data may consist of other parameter values ​​as well as those indicative of power, as explained in the examples below.

[0035] A given cooling condition may include values ​​for one or more parameters such as sample volume; sample composition; number of samples; sample container size; sample container type; cooling device type; cooling rate; cooling profile; and / or initial temperature of the sample or heat sink of the cooling device. The heat sink may be the cold finger of the cooling device in some examples. At least some of such data for a given cooling condition may be unknown or unverified at the time of the cooling operation. For example, the sample volume and / or sample composition may be assumed or estimated but unverified.

[0036] The method 200 calls for obtaining second data associated with the reference cooling condition at block 220. The second data may be pre-stored data, e.g., electronic data stored in a computer-readable storage. The reference cooling condition may include values ​​for one or more parameters, such as sample volume; sample composition; number of samples; sample container size; sample container type; cooling device type; cooling rate; cooling profile; and / or initial temperature of the heat sink of the sample or cooling device. The given cooling condition and the reference cooling condition may include values ​​for one or more common parameters.

[0037] The method 200 also involves determining, at block 230, whether the given cooling condition has a predetermined relationship with a reference cooling condition based on the first data and the second data. For example, the predetermined relationship between the given and reference cooling conditions may be that they are substantially the same, e.g., within a first tolerance, or substantially different, e.g., outside a second tolerance. In an example, there may be multiple tolerances that define multiple predetermined relationships.

[0038] As an example, the given cooling condition may include an unknown value of a first cooling condition parameter, such as sample volume. The reference cooling condition may include a known value of the first cooling condition parameter, for example, 5 ml. Based on first data associated with, e.g., measured during, a cooling operation having the given cooling condition; and second data associated with the reference cooling condition, block 230 may require determining whether the unknown sample volume value is substantially the same as the known value, in this case 5 ml, for example, within a set tolerance.

[0039] At block 240, method 200 calls for outputting a control signal in response to determining that the given cooling condition has a predetermined relationship to the reference cooling condition. Thus, the control signal may be generated and output in response to determining that the given cooling condition has a predetermined relationship to the reference cooling condition by same. For example, in the above case where the predetermined relationship comprises the given and reference cooling conditions being substantially the same, if it is determined that the unknown sample volume value is substantially the same as the known sample volume value, e.g., within a set tolerance, then the control signal may be output at block 240. If it is determined that the given and reference cooling conditions are not substantially the same based on the first and second data, then the control signal may not be output at block 240.

[0040] In another example, the predetermined relationship may comprise the given cooling condition and the reference cooling condition being substantially different, in which case, if it is determined at block 230 that the given cooling condition and the reference cooling condition are substantially different, a control signal will be output at block 240. Otherwise, a control signal may not be output.

[0041] In an example, the control signal output at block 240 causes the cooling operation to be discontinued. For example, the control signal may be sent to a control module of the cooling device or of the cooling system as a whole to stop the cooling operation, such that, for example, no further power is used in continuing the cooling operation if, at block 230, it is determined that the given cooling condition and the reference cooling condition are substantially different, e.g., the sample volume and / or composition parameters of the given cooling condition are substantially different from those of the reference cooling condition.

[0042] In other examples, the control signal output in block 240 is to cause an output via a user interface indicative of a predetermined relationship between the given cooling condition and the reference cooling condition. For example, if the predetermined relationship comprises the given cooling condition and the reference cooling condition being substantially the same and this is determined to be the case in block 230, an output indicative of the given cooling condition and the reference cooling condition being substantially the same may be output by the user interface. The user interface may be a display device, such as a light emitting diode (LED) or an electronic visual display. The output indicative of the predetermined relationship may comprise words displayed on the electronic visual display, or a particular color, such as a green or red light. In these examples, if the predetermined relationship involved in block 230 is that the given cooling condition and the reference cooling condition are substantially different, the output indicative of the predetermined relationship by the user interface may alert the user to manually discontinue the cooling operation.

[0043] In some cases, the control signal output at block 240 may result in the storage of data representative of the determination at block 230 that the given cooling condition has a predetermined relationship to the baseline cooling condition. For example, a report or data log may be generated that represents the parameter values ​​during the cooling operation. The data representative of the determination that the given cooling condition has a predetermined relationship to the baseline cooling condition may be stored as part of the report or data log, in an example.

[0044] In an example, the first data obtained in block 210 comprises a first power value, e.g., P1, and the second data obtained in block 220 comprises a second power value, e.g., P2. Determining in block 230 whether the given cooling condition has a predefined relationship to a reference cooling condition may include determining a difference between the first and second power values, e.g., (P1-P2) or |P2-P1|. The first power value may correspond to a peak value of power supplied to the cooling device during a cooling operation. For example, this may be implemented when the cooling device does not need to reach a maximum power usage during a cooling operation, e.g., the power supplied to the cooling device does not need to reach 100 percent (%) of the maximum power supply in order to follow a cooling profile for the cooling operation. In such a case, the first and second data may comprise respective peak values ​​of power supplied to the cooling device during the respective cooling operation. These peak values ​​may then be compared, e.g., to determine whether the given cooling condition and the reference cooling condition are substantially the same or substantially different.

[0045] In an example, the first data obtained in block 210 consists of a first power value, e.g., P1, and a first value of an associated parameter, e.g., x1. For example, the first data may consist of a tuple (P1, x1) of the first power and the associated parameter value.

[0046] The relevant parameter may correspond to a time or a temperature of a heat sink of the cooling device. The first data may thus consist of a first power value, P1, together with a corresponding time value or heat sink temperature value, x1, during the cooling operation. The heat sink temperature value may be measured by one or more temperature sensors positioned on the heat sink. If more than one temperature sensor is positioned on the heat sink to measure its temperature, a representative, e.g. an average temperature, may be calculated from the multiple temperature measurements.

[0047] The second data obtained in block 220 may consist of a second power value, e.g. P2, and a second value of the associated parameter, e.g. x2. The second data may consist of a tuple (P2, x2) of the second power and the associated parameter value.

[0048] In an example, the method 200 involves determining a difference between a first value, x1, of the related parameter and a second value, x2, of the related parameter, e.g., (x2-x1), where the first power value P1 and the second power value P2 correspond to each other. For example, the first power value P1 and the second power value P2 may be substantially the same.

[0049] For example, the method may include obtaining a first data set of power values ​​and corresponding associated parameter values, such as time or temperature values, recorded during the cooling operation; and a second data set of power values ​​and corresponding associated parameter values. Obtaining the first data set consisting of the first power value P1 and the corresponding associated parameter value, x1, may thus include selecting the first data set from the first data set based on the first power value P1, e.g., P max is the maximum amount of power supplied to the cooling device during cooling operation, then 0.8P max Similarly, obtaining second data consisting of a second power value P2 and a corresponding associated parameter value x2 may thus include selecting second data from the second data set based on the second power value P2 corresponding to the first power value P1, e.g., P max Let be the maximum power value in the second data set, 0.8P max As an illustrative example, for a cooling device including a cryocooler with a freeze plate as a heat sink, the first data set may include selecting a data point in the second data set having a corresponding particular power value such as 0.8P, where the first temperature is the absolute measured temperature of the freeze plate, e.g., as measured by a thermocouple on the freeze plate. maxThe first data set may include a first data consisting of a first temperature value T1 of −58° C. at 0.8P. The first data set may be associated with an unknown given (first) cooling condition. In some cases, the temperature data may consist of a relative measured temperature representing, for example, the difference between a freeze plate measured temperature and an ambient temperature. In this example, the second data set may include a first data consisting of a first temperature value T1 of −58° C. at 0.8P. max The second data set may include a second data consisting of a second temperature value T2 of -68.45±3.66°C at 100 ml, the second data set being associated with a reference (second) cooling condition comprising the parameters: 100 ml sample volume, 10% w / v DMSO, 0.9% w / v NaCl (sodium chloride). Thus, based on the first and second data, a difference |T1-T2|=10.45°C may be determined. The predefined threshold, in this example, is based on the measurement uncertainty and may be, for example, 3.66°C. A difference |T1-T2|=10.45°C greater than the predefined threshold 3.66°C may thus indicate that the first and second cooling conditions are not substantially the same in this example.

[0050] In this illustrative example, the third data set is 0.8P max The third data set may include a third data consisting of a third temperature value T3 of -59.1±1.45°C at 150 ml sample volume, the third data set being associated with a third cooling condition including the parameters: 150 ml sample volume, 10% w / v DMSO, 0.9% w / v NaCl. Thus, based on the first and third data, a difference |T1-T3|=1.1°C may be determined. The predefined threshold may be 1.45°C in this case based on the measurement uncertainty. The difference |T1-T3|=1.1°C being less than the predefined threshold 1.45°C may thus indicate that the first and third cooling conditions are substantially the same in this example. In this way, a given cooling condition associated with a cooling operation on a biological sample may be interpreted as having substantially the same parameter values ​​as the third cooling condition, e.g., 150 ml sample volume, 10% w / v DMSO, 0.9% w / v NaCl.

[0051] In another example, the first and second power values ​​may be substantially the same, such that a difference (x2-x1) is calculated between associated parameter values, x1 and x2, corresponding to the same power value (P1=P2) in the respective first and second data sets.

[0052] In another example, the method 200 may involve determining a difference between the first power value P1 and the second power value P2, assuming that the first value x1 of the relevant parameter and the second value x2 of the relevant parameter are substantially the same. For example, the method 200 may involve obtaining the first and second data sets described above, and selecting a first data point from the first data set based on the first value x1 of the relevant parameter, e.g., selecting a data point in the first data set having a particular heat sink temperature value, e.g., 173 Kelvin (K), during a cooling operation. Obtaining the second data may similarly involve selecting a second data point from the second data set based on a second value x2 of the relevant parameter that is substantially the same, e.g., corresponds to the first relevant value x1, e.g., 173 K, in this example.

[0053] In some examples, the first data comprises a first data sequence of power values ​​and corresponding values ​​of related parameters, eg, as described above with respect to the first data set.

[0054] The second data may similarly comprise a second data series of power values ​​and corresponding values ​​of related parameters, for example as described above with respect to the second data set.

[0055] FIG. 3 shows a representation of an example data sequence 300 consisting of power values ​​and corresponding temperature values. As mentioned above, where the example data sequence 300 corresponds to a first data sequence, the temperature values ​​may be, for example, of a heat sink during a cooling operation. Such a representation of the data sequence 300 may be referred to as a "power curve." The power curve illustrated in FIG. 3 is with respect to temperature, but as mentioned above, other example power curves may be with respect to time as the relevant parameter. The example data sequence 300 may be stored in a data structure, for example an array or table, that associates each power value in the data sequence 300 with a corresponding temperature value. In the example data sequence represented by the power curve of FIG. 3, the power value may be a maximum power value P max The power values ​​in the first and / or second data sequences may similarly be normalized with respect to a particular power value, for example the maximum power value of the respective data sequence.

[0056] Determining whether the given cooling condition has a predetermined relationship to the reference cooling condition at block 230 of the method 200 may be based on a statistical comparison between the first data series and the second data series.

[0057] For example, a first value of a statistical metric, such as an integral of the power curve, may be determined based on the first data series, and a second value of the statistical metric, e.g., the power curve integral, may be determined based on the second data series. The first and second values ​​of the statistical metric may be compared, and a determination of whether the given cooling condition has a predetermined relationship to a reference cooling condition may be based on the comparison. For example, if the first and second values ​​of the statistical metric are determined to be substantially the same within a predetermined tolerance, the given cooling condition may be determined to have a predetermined relationship to the reference cooling condition.

[0058] In some examples, the first and second data series represented by the respective power curves may be analyzed to determine respective relevant parameter values ​​at spikes in each of the first and second data series. For example, during cooling of the sample, the sample temperature may suddenly increase (e.g., with a change in the rate of change of temperature of more than 50%) or "spike" at the point (in temperature or time) where ice nucleation begins to occur and ice crystals begin to form within the sample, but because ice nucleation is an exothermic reaction, when it occurs, thermal energy is released, increasing the sample temperature. The suddenly increasing sample temperature may also suddenly increase the heat sink temperature, e.g., a conductive plate or cold chamber in a cooling device. If the cooling system implements a temperature feedback system between the temperature sensor and the power supply via a cooling system control module, as described above with reference to FIG. 1, an increase in the measured temperature may result in an increase in the amount of power supplied to the cooling device as the cooling device attempts to reduce the temperature to match the cooling profile. The cooling profile may, for example, consist of cooling the sample at a substantially constant rate. In this manner, the cooling system control module may respond when a temperature measurement spikes during ice nucleation within the sample by increasing the amount of power supplied to the cooling device to substantially maintain a constant cooling rate as defined by the cooling profile. Such a sudden increase in the amount of power supplied to the cooling device may result in a spike 305 in the power curve representing the data series 300, as illustrated in FIG.

[0059] Method 200 may therefore in some cases involve determining where such spikes occur in the power curve, e.g., at what relevant parameter (temperature, time) values ​​the power spikes occur. This may be done by determining the rate of change of power with respect to the relevant parameter, e.g., by calculating the derivative of the power with respect to the relevant parameter in each data series. A predefined threshold for the power derivative may be set such that a determined power derivative value above the predefined threshold indicates the presence of a spike in the power curve. In such a case, determining in block 230 based on the first and second data whether the given cooling condition has a predefined relationship to the reference cooling condition may involve comparing the determined relevant parameter values ​​in the first and second data series at which the power spikes occur.

[0060] In some examples, multiple spikes in the power curve may be determined in a given data series. In such examples, determining whether the given cooling condition has a predetermined relationship to the reference cooling condition in block 230 based on the first data and the second data may require determining one or more "outlier" spikes. For example, clusters of power spikes in the first and second data series may correspond to each other, but the first data series may include a power spike that is determined to be at a given associated parameter value that is more than a predetermined threshold away from the associated parameter value of the closest power spike in the second data series. In this case, the given cooling condition may be determined to have a predetermined relationship, e.g., substantially different, from the reference cooling condition.

[0061] In an example, the method 200 involves determining a similarity metric based on the first data and the second data. For example, if the first and second data are one-dimensional (1D), e.g., comprise one or more values ​​of a single parameter, such as power as discussed above, the similarity metric may be a difference between a first power value P1 of the first data and a second power value P2 of the second data, e.g., (P1-P2) or |P2-P1|.

[0062] In another example, as described, the first and second data are two-dimensional (2D) and consist of one or more respective values ​​of two parameters, such as power and a related parameter, e.g., time or temperature. In such an example, the similarity metric may correspond to a difference between a first value of the related parameter, x1, and a second value of the related parameter, x2, e.g., (x2-x1), as described in the example above, where the first power value P1 and the second power value P2 correspond to each other. Alternatively, the similarity metric may correspond to a difference between a first power value P1 and a second power value P2, e.g., (P2-P1), as described in the example above, where the first value of the related parameter, x1, and the second value of the related parameter, x2, are substantially the same.

[0063] In further examples, the first and second data may be 2D and consist of a first data series of power values ​​and corresponding values ​​of related parameters; and a second data series of power values ​​and corresponding values ​​of related parameters, respectively, as described above. In these examples, the similarity metric may be determined based on a statistical comparison between the first data series and the second data series. For example, a first value of the statistical metric may be determined based on the first data series, and a second value of the statistical metric may be determined based on the second data series, as described above. The similarity metric in this example may correspond to a difference between the first and second values ​​of the statistical metric.

[0064] Determining whether the given cooling condition has a predetermined relationship with the reference cooling condition at block 230 of method 200 may be based on a comparison of the similarity metric to a predetermined threshold. For example, the given cooling condition may be determined to have a predetermined relationship with the reference cooling condition if the similarity metric is less than; less than or equal to; equal to; greater than; or greater than or equal to the predetermined threshold. The predetermined relationship between the given cooling condition and the reference cooling condition may be that they are substantially the same, e.g., similar; or substantially different, e.g., not the same.

[0065] In some examples of method 200, the control signal is a first control signal and the predetermined relationship is a first predetermined relationship. In such examples, method 200 may further involve determining whether the given cooling condition has a second predetermined relationship with the reference cooling condition based on the first data and the second data.

[0066] Such a "second determination" of whether the given cooling condition has a second predetermined relationship with the reference cooling condition may follow any of the above-mentioned examples of the "first determination" of whether the given cooling condition has a predetermined relationship with the reference cooling condition. In an example, the first and second determinations may result from a single determination: for example, a difference or similarity metric is determined based on the first and second data, and the difference or similarity metric is compared to a predetermined threshold; a first result of the comparison (e.g., the difference or similarity metric is greater than the predetermined threshold) may indicate that the given cooling condition has the first predetermined relationship with the reference cooling condition, while a second result (e.g., the difference or similarity metric is equal to or less than the predetermined threshold) may indicate that the given cooling condition has the second predetermined relationship with the reference cooling condition. Such first and second results of the comparison may be complementary, as in the described examples.

[0067] In other examples, the first determination and the second determination may be separate determinations made as part of the method 200. For example, the first determination may involve a first predefined threshold as the predefined threshold in the described example, while the second determination may involve a second predefined threshold as the predefined threshold in the example.

[0068] In response to determining that the given cooling condition has a second predetermined relationship with the reference cooling condition, the method 200 may include outputting a second control signal. Thus, the second control signal may be generated and output in response to determining, by the same determining, that the given cooling condition has the second predetermined relationship with the reference cooling condition. Similar to the first control signal example described above, in some cases the second control signal may result in the interruption of the cooling operation and may additionally or alternatively result in an output via a user interface indicative of the second predetermined relationship between the given cooling condition and the reference cooling condition. The user interface may be the same user interface as the first control signal would result in an output in some examples. For example, the first control signal may be output in response to determining that the given cooling condition has a first predetermined relationship with the reference cooling condition and may result in a first output indicative of the first predetermined relationship via the first user interface. A second control signal may be output in response to determining that the given cooling condition has a second predetermined relationship with the reference cooling condition, resulting in a second output indicative of the second predetermined relationship via the second user interface.

[0069] For example, a first predetermined relationship between a given cooling condition and a reference cooling condition may be that they are substantially the same, e.g., similar, and a second predetermined relationship may be that they are substantially different, e.g., not the same. Thus, the first control signal may indicate that the cooling conditions are substantially the same, e.g., via a first user interface resulting in the output of a green LED, the display of a first image on a display screen, or the storage and / or transmission of text data in a report or data log, indicating that the cooling conditions or parameters thereof, e.g., biological sample volume and reference sample volume, are substantially the same. The second control signal, on the other hand, may indicate that the cooling conditions are substantially different, e.g., via a second user interface resulting in the output of a red LED, the display of a second image on a display screen, or the storage and / or transmission of text data in a report or data log, indicating that the cooling conditions or parameters thereof, e.g., biological sample volume and reference sample volume, are substantially different.

[0070] In some examples, the first and second user interfaces are the same interface, or in other words the first and second control signals result in respective outputs via the same, e.g., first, user interface. For example, the user interface may be capable of displaying various information, and the first and second control signals may determine what particular information is displayed by the user interface, e.g., the color of an LED, the text or image displayed, etc.

[0071] In any of the examples of method 200 described above, the cooling operation implemented by, for example, a cooling device as part of a cooling system may cool the biological sample at a substantially constant rate. For example, the cooling device may cool the biological sample according to a cooling profile (representing the change in cooling rate over time or temperature and / or the change in temperature over time, for example, during a cooling operation). A substantially constant cooling rate (e.g., within acceptable measurement tolerances) may be implemented for at least a portion of the cooling profile. For example, the substantially constant cooling rate may be substantially (e.g., within acceptable measurement tolerances) 1 degree Celsius per minute in an example, such that the cooling device objectively cools the biological sample by 1 degree Celsius per minute of the cooling operation for the corresponding at least a portion of the cooling profile.

[0072] As noted above, different target cooling rates, e.g., rate of temperature change with respect to time, may be set at different stages of the cooling profile. In some cases, a constant target cooling rate may be set for the cooling profile.

[0073] 4 illustrates a non-transitory computer-readable storage medium 420 having stored thereon a set of computer-readable instructions 425. The computer-readable storage medium 420 may be communicatively coupled to at least one processor 450, as shown. The set of computer-readable instructions 425 may be executed by the at least one processor 450 to cause the at least one processor 450 to perform a method according to any of the examples described herein.

[0074] At least one processor 450 may include a microprocessor, a microcontroller, a processor module or subsystem, a programmable integrated circuit, a programmable gate array, or another control or computing device. The computer-readable storage medium 420 may be implemented as one or more computer-readable storage media. The computer-readable storage medium 420 may include various forms of memory, including semiconductor memory devices such as dynamic or static random access memory modules (DRAM or SRAM), erasable and programmable read-only memory modules (EPROM), electrically erasable and programmable read-only memory modules (EEPROM) and flash memory; magnetic disks such as fixed, floppy and removable disks; other magnetic media including tape; optical media such as compact disks (CDs) or digital video disks (DVDs); or other types of storage devices. The computer-readable instructions 425 may be stored in one computer-readable storage medium, or alternatively, may be stored in multiple computer-readable storage media. The one or more computer readable storage media 420 may be provided in the cooling system or at a remote site where the computer readable instructions 425 may be downloaded over a data network for execution by the at least one processor 450 .

[0075] The at least one processor 450 and the computer readable storage medium 420 may be, for example, parts of a cooling system. The cooling system may comprise a cooling system similar to the cooling system 100 described with reference to FIG.

[0076] 5 illustrates a system 500 that includes a processor 550 (which may comprise one or more processors) and computer-readable storage 540. The processor 550 may be configured, e.g., the processor is operable, to perform any of the example methods described herein.

[0077] In the example, the processor 550 corresponds to at least one of the processors 450 described in the example with reference to Figure 4. For example, the processor may be communicatively coupled to a computer storage medium, which may be separate from or part of the computer readable storage 540, and may store a set of computer readable instructions that, when executed by the processor 550, cause the processor 550 to perform the subject methods.

[0078] The processor 550 is configured to obtain second data associated with a reference cooling condition from the computer-readable storage 540. For example, the second data associated with a particular reference cooling condition may be selected, for example, by a user, as reference data for a cooling operation. For example, a biological sample to be cooled by the cooling device may be considered by a user to consist of 150 ml of fluid with 10% concentration DMSO and 0.9% concentration NaCl. The user may therefore select the second data associated with the reference cooling condition having a corresponding sample volume and sample composition parameter value (150 ml volume, 10% DMSO, 0.9% NaCl in this example). In other examples, multiple sets of second data associated with multiple reference conditions may be selected or pre-programmed to be obtained by the processor 550 from the computer-readable storage 540. In such examples, a method according to any of the examples described herein may be performed with first data indicative of power supplied to the cooling device during a cooling operation, and with each of the multiple second data associated with different reference cooling conditions respectively. In this manner, the method performed by the processor 550 may determine that the given cooling condition has a predetermined relationship to one or more of the various reference cooling conditions. In some cases, such as when the predetermined relationship consists of the given cooling condition and the reference cooling condition being substantially the same, the method performed by the processor 550 may determine which of the various reference cooling conditions included in the second data is most similar to the given cooling condition. In this manner, the control signal output by or via the processor 550 may provide an indication of the reference cooling condition to which the given cooling condition is most similar.

[0079] In some examples, the system 500 includes a programmable power supply 530. The programmable power supply 530 is configured to supply power to the cooling device 510 during a cooling operation. The power supply 530 and the cooling device 510 may correspond to the power supply 130 and the cooling device 110, respectively, described with reference to FIG. 1. For example, the power supply 530 and the cooling device 510 may be part of a cooling system 505, which corresponds to the cooling system 100 of FIG. 1. The programmable power supply 530 may modulate the power supplied to the cooling device 510 by interaction with a control module, which corresponds to the control module 140 described with reference to FIG. 1, for example. Thus, the power supply may be considered programmable because it may be programmed, under the control of the control module, to output a desired power at a given time during a cooling operation.

[0080] The programmable power supply 530 may transmit first data indicative of the power supplied to the cooling device 510. In an example, the programmable power supply 530 may transmit the first data directly to the processor 550, which receives and processes the first data as part of the method implemented. In some cases, the power supply 530 may transmit the first data to the processor 550 via other components, if present, such as a control module of the cooling system 505. The first data for transmission may be generated by the programmable power supply. For example, the programmable power supply may determine a value of the power currently supplied to the cooling device and based thereon generate the first data such that the first data is indicative of a value of the power supplied to the cooling device at a given time, and the first data is then transmitted as described above.

[0081] The processor 550 may be connected to the power source 530 and the computer-readable storage 540, directly or indirectly, through a data network. In such an example, the processor 550 may receive the first and second data over the data network. For example, the first and second data may be transmitted to a server connected to the data network, and the processor may download the first and second data from the server when obtaining the first and second data as part of the implemented method.

[0082] In one example, system 500 includes a cooling device 510, which may be, for example, a cryocooler, as described above. The cooling device 510 and power supply 530 may be part of a cooling system 505, which may be remote from the processor 550 and / or storage 540. For example, the cooling system 505 may be located at a first location and communicatively coupled, for example, via a data network, to the processor 550 and / or storage 540, which may be located at a second and third location, respectively.

[0083] In some other examples, cooling system 505 includes a processor 550 and / or storage 540 as components thereof. For example, processor 550 is configured to perform a method according to any of the examples described herein and may be an internal component of cooling system 505. Similarly, computer readable storage 540 may additionally or alternatively be an internal component of cooling system 505. In some examples, internal components of cooling system 505 may be communicatively physically coupled, while external components of cooling system 505 may be communicatively coupled wirelessly, for example through a data network.

[0084] In some examples, the cooling operation on the biological sample may be implemented by multiple cooling devices 510. For example, the cooling system 505 may include multiple cooling devices 510, e.g., multiple cryocoolers. The processor 550, in such examples, may obtain first data indicative of the power supplied to each of the cooling devices 510 and / or indicative of the power supplied to all of the cooling devices 510. The power source 530 may be configured to supply and modulate power to each of the cooling devices individually during the cooling operation. For example, a temperature sensor, such as a thermocouple, may be positioned at the heat sink of each cooling device 510, and the power supplied to each cooling device 510 may be modulated by the power source 530 based on the measured temperature of the respective heat sink and the implemented cooling profile. In some cases, the heat sink temperature data and the power data may each be averaged, e.g., arithmetically averaged, by the number of cooling devices 510. In other cases, the heat sink temperature data may be averaged by a number of cooling devices 510, while the power data may consist of the total amount of power supplied to all of the cooling devices 510 at each given data point, for example, over a time or temperature interval.

[0085] In some cases, the multiple cooling devices 510 may share a common heat sink, such as a thermally conductive plate or freezing chamber, for directly cooling the sample. In such cases, heat sink temperature data may be obtained via one or more temperature sensors positioned on or in the heat sink, and if there are multiple temperature sensors, the temperature data may be averaged. Each of the multiple cooling devices 510 may have a different cooling capacity in some examples.

[0086] The above examples should be understood as illustrative examples. As a further example, a computer program product, such as computer software, is envisaged, comprising instructions that, when executed by a computer, cause the computer to perform a method according to any of the example methods described herein.

[0087] As a further example, it is also envisaged that the first data is indicative of power supplied to the cooling device during a cooling operation on a calibration sample or without a sample, and a reference cooling condition is associated with a cooling operation on a calibration sample or without a sample, respectively, performed by a reference cooling device (which may be assumed and for example the second data may be generated or measured data), so that the method may be used to assess the state of the cooling device relative to the reference cooling device. Such a method may therefore be implemented as a cooling device diagnostic method.

[0088] In such examples, the diagnostic method may include determining a diagnostic metric value based on the first data and the second data, e.g., in a manner similar to determining the similarity metric in certain described examples. Determining whether the cooling device is in a predetermined state, e.g., good or bad state, relative to a reference cooling device may be based on a comparison between the diagnostic metric value and a predetermined threshold.

[0089] It should be understood that any feature described with respect to any one example may be used alone or in combination with the other described features, and may also be used in combination with one or more features of any other example or any combination of any other examples. Furthermore, equivalents and modifications not described above may also be utilized without departing from the scope of the appended claims. [Explanation of symbols]

[0090] 100 Cooling System 105 Samples 110 Cooling device 115 Coldfinger 120 Heat Conduction Plate 130 Power supply 140 Control Module 200 ways 300 Data Series 305 Spike 420 Computer-readable storage medium 425 Computer Readable Instructions 450 processor 500 Systems 505 Cooling System 510 Cooling device 530 Programmable Power Supply 540 Computer Readable Storage 550 Processor

Claims

1. 1. A system comprising a processor, a programmable power supply, and a cooling device, The programmable power supply comprises: providing power to the cooling device during a cooling operation; modulating the power supplied to the cooling device to control a temperature of the cooling device according to a predetermined cooling profile; Transmitting the first data; It is structured as follows: the cooling device is a cryocooler configured to perform the cooling operation; The processor, obtaining the first data indicative of power supplied from the programmable power supply to the cooling device during a cooling operation on a biological sample, the cooling operation having a given cooling condition, the first data including a first power value and a first value of a related parameter; obtaining second data associated with a reference cooling condition recorded during a cooling operation on a reference sample, the second data including a second power value and a second value of the relevant parameter; determining whether the given cooling condition has a predetermined relationship with the reference cooling condition based on the first power value and a first value of the related parameter in the first data and the second power value and a second value of the related parameter in the second data; outputting a control signal in response to the determining step determining that the given cooling condition has the predetermined relationship with the reference cooling condition; configured to implement said relevant parameter being time or the temperature of the heat sink of the cooling device; the predetermined relationship is that the given cooling condition and the reference cooling condition are substantially the same; a sample volume and a sample composition in the biological sample are substantially the same as a sample volume and a sample composition in the reference sample when the given cooling condition has a predetermined relationship with the reference cooling condition; The control signal causes an interruption of the cooling operation.

2. 1. A system comprising a processor, a programmable power supply, and a cooling device, The programmable power supply comprises: providing power to the cooling device during a cooling operation; modulating the power supplied to the cooling device to control a temperature of the cooling device according to a predetermined cooling profile; Transmitting the first data; It is structured as follows: the cooling device is a cryocooler configured to perform the cooling operation; The processor, obtaining the first data indicative of power supplied from the programmable power supply to the cooling device during a cooling operation on a biological sample, the cooling operation having a given cooling condition, the first data including a first data series of power values ​​and corresponding values ​​of related parameters; obtaining second data recorded during a cooling operation on a reference sample and associated with a reference cooling condition, said second data including a second data series of power values ​​and corresponding values ​​of said related parameters; determining whether the given cooling condition has a predetermined relationship with the reference cooling condition based on the first data series of the first data and the second data series of the second data; outputting a control signal in response to the determining step determining that the given cooling condition has the predetermined relationship with the reference cooling condition; configured to implement said relevant parameter being time or the temperature of the heat sink of the cooling device; the predetermined relationship is that the given cooling condition and the reference cooling condition are substantially the same; a sample volume and a sample composition in the biological sample are substantially the same as a sample volume and a sample composition in the reference sample when the given cooling condition has a predetermined relationship with the reference cooling condition; The control signal causes an interruption of the cooling operation.

3. The processor of the system is configured to perform a step of determining a similarity metric based on the first data and the second data; 3. The system of claim 1 or 2, wherein the determining whether the given cooling condition has the predetermined relationship with the reference cooling condition is based on a comparison of the similarity metric to a predetermined threshold.

4. 4. The system of claim 1, wherein the control signal a) causes an interruption of the cooling operation, or b) causes an output via a user interface indicative of the predetermined relationship between the given cooling condition and the reference cooling condition.

5. the control signal is a first control signal, the predetermined relationship is a first predetermined relationship, and the processor of the system: determining whether the given cooling condition has a second predetermined relationship with the reference cooling condition based on the first data and the second data; outputting a second control signal in response to the determining step determining that the given cooling condition has the second predetermined relationship with the reference cooling condition; 5. The system of claim 1 , configured to implement:

6. 2. The system of claim 1, wherein the processor of the system is configured to perform the steps of: a) determining a difference between the first value of the related parameter and the second value of the related parameter, wherein the first power value and the second power value match one another; or b) determining a difference between the first power value and the second power value, wherein the first value of the related parameter and the second value of the related parameter are substantially the same.

7. 3. The system of claim 2, wherein determining whether the given cooling condition has a predetermined relationship to the reference cooling condition is based on a statistical comparison between the first data series and the second data series.

8. 1. A system comprising a processor, a programmable power supply, and a cooling device, The programmable power supply comprises: providing power to the cooling device during a cooling operation; modulating the power supplied to the cooling device to control a temperature of the cooling device according to a predetermined cooling profile; Transmitting the first data; It is structured as follows: the cooling device is a cryocooler configured to perform the cooling operation; The processor, obtaining the first data indicative of power supplied from the programmable power supply to the cooling device during a cooling operation on a biological sample, the cooling operation having a given cooling condition; obtaining second data recorded during a cooling operation on the reference sample and associated with a reference cooling condition; determining whether the given cooling condition has a predetermined relationship with the reference cooling condition based on the first data and the second data; outputting a control signal in response to the determining step determining that the given cooling condition has the predetermined relationship with the reference cooling condition; configured to implement the first data includes a first power value corresponding to a peak value of power supplied to the cooling device during the cooling operation on the biological sample and associated parameters; the second data includes a second power value corresponding to a peak value of power supplied to the cooling device during the cooling operation on the reference sample and related parameters; said relevant parameter being time or the temperature of the heat sink of the cooling device; a sample volume and a sample composition in the biological sample are substantially the same as a sample volume and a sample composition in the reference sample when the given cooling condition has a predetermined relationship with the reference cooling condition; The control signal causes an interruption of the cooling operation.

9. 9. The system of claim 1, wherein the cooling operation cools the biological sample at a substantially constant rate.

10. 10. The system of claim 9, wherein the substantially constant rate is 1 degree Celsius per minute.

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