CN-122029606-A - Method and system for controlling the processing of biological material

Abstract

A method for controlling processing of biological material includes receiving at least one input parameter associated with biological material, retrieving, by a data retrieval module, a first data set from a data store based on the at least one input parameter, selecting, by an algorithm selection module, a first machine learning algorithm for processing the at least one input parameter from a plurality of candidate machine learning algorithms, wherein the first machine learning algorithm is selected based on the at least one input parameter or the first data set, training the first machine learning algorithm using at least a portion of the first data set, applying the trained first machine learning algorithm to the at least one input parameter to determine a first processing parameter for subsequent processing of the biological material, and outputting the first processing parameter for subsequent processing of the biological material.

Inventors

• B owens
• S. Macaron
• S. CAMERON

Assignees

• 维特拉菲生命科学有限公司

Dates

Publication Date

20260512

Application Date

20240904

Priority Date

20230905

Claims (20)

1. 1. A method for controlling the processing of biological material, comprising: receiving at least one input parameter associated with a biological material; retrieving, by the data retrieval module, the first data set from the data store based on the at least one input parameter; Selecting, by an algorithm selection module, a first machine learning algorithm for processing the at least one input parameter from a plurality of candidate machine learning algorithms, wherein the first machine learning algorithm is selected based on the at least one input parameter or the first data set; training the first machine learning algorithm using at least a portion of the first data set; applying the trained first machine learning algorithm to the at least one input parameter to determine a first processing parameter for subsequent processing of the biological material, and Outputting the first processing parameter for subsequent processing of the biological material.
2. 2. The method of claim 1, further comprising storing the input parameters and the first processing parameters in the data store.
3. 3. The method of claim 2, further comprising determining whether the first processing parameter is valid; Wherein the input parameters and the first processing parameters are stored in the data store only when the first processing parameters are valid and immediately after determining that the first processing parameters are valid.
4. 4. The method of claim 3, wherein determining whether the first processing parameter is valid comprises: Determining a confidence level, and When the confidence level is above a predetermined threshold, the first processing parameter is determined to be valid.
5. 5. The method of any of the preceding claims, wherein the first machine learning algorithm is selected based on the at least one input parameter.
6. 6. The method of any of claims 1-4, wherein the first machine learning algorithm is selected based on the first data set.
7. 7. The method of any one of the preceding claims, Characterized in that the at least one input parameter comprises a plurality of data types, each data type being associated with a respective data value, and Wherein retrieving the first data set includes retrieving a data record having one or more corresponding data types and associated data values.
8. 8. The method of claim 1, wherein the first data set is also retrieved based on an output data type.
9. 9. The method of claim 1, wherein the candidate machine learning algorithm is stored in an algorithm library, and wherein selecting the first machine learning algorithm comprises: The first machine learning algorithm is retrieved from the algorithm library.
10. 10. The method as recited in claim 9, further comprising: at least one candidate machine learning algorithm in the algorithm library is added, deleted or updated.
11. 11. The method of claim 1, wherein the data store stores data including device data or sample data uploaded from at least one biological material processing device.
12. 12. The method of claim 11, wherein the device data or sample data comprises one or more process parameters generated by the at least one biological material processing device performing the method of any one of claims 1-9.
13. 13. A method according to claim 11 or 12, wherein the uploading of device data or sample data is started after its generation as soon as a suitable data channel is available.
14. 14. The method of any of the preceding claims, further comprising using a portion of the first data set as a training data set and using the remaining portion of the first data set as a test data set.
15. 15. The method of claim 14, wherein a proportion of the first data set used as a training data set is determined at least in part by a size of the first data set.
16. 16. The method of any of the preceding claims, further comprising: retrieving, by the data retrieval module, a second data set from the data store based on the input parameters; Selecting, by the algorithm selection module, a second machine learning algorithm from the plurality of candidate machine learning algorithms for processing the input parameter, wherein the second machine learning algorithm is selected based on the input parameter or the second data set; Training the second machine learning algorithm using the second data set; applying the trained second machine learning algorithm to the input parameters to determine second processing parameters for subsequent processing of the biological material, and Outputting the second processing parameter for subsequent processing of the biological material.
17. 17. The method of any one of claims 1-15, further comprising: Retrieving, by the data retrieval module, a second data set from the data store based on the first processing parameter; selecting, by the algorithm selection module, a second machine learning algorithm from the plurality of candidate machine learning algorithms for processing the first processing parameter, wherein the second machine learning algorithm is selected based on the first processing parameter or the second data set; Training the second machine learning algorithm using the second data set; applying the trained second machine learning algorithm to the first processing parameters to determine second processing parameters for subsequent processing of the biological material, and Outputting the second processing parameter for subsequent processing of the biological material.
18. 18. The method of any one of the preceding claims, wherein the biological material comprises one or more of the following: a) Whole blood; b) Blood components such as platelets, erythrocytes, leukocytes, plasma and other blood products; c) Stem cells such as hematopoietic stem cells, mesenchymal stem cells, and embryonic stem cells; d) Modifying the cell; e) Engineering cells; f) Gametes such as egg cells and sperm; g) Blastula (blastula); h) Oocytes; i) An organ including a portion thereof, and J) Organization.
19. 19. The method of any of the preceding claims, wherein the subsequent biological material treatment comprises at least one of: packaging, storing or transporting biological material; Refrigerating, freezing, thawing and preserving biological materials at low temperature; measuring and developing; collecting a sample; cell diagnosis; bioreactor-based treatment, and Amplification of biological material.
20. 20. The method of any of the preceding claims, wherein the at least one input parameter is received by an orchestration module, the method further comprising: The arrangement module sends the input parameters to the data retrieval module; The orchestration module receives the first data set from the data retrieval module; The orchestration module sending the at least one input parameter or the first data set to the algorithm selection module for use in selecting the first machine learning algorithm; the orchestration module receives a first processing parameter determined by the first machine learning algorithm.

Description

Method and system for controlling the processing of biological material Technical Field The present disclosure relates to a method and system for controlling the processing of biological materials. Background Biological material is collected for a range of purposes including, but not limited to, medical, procedures, diagnostics, and research. Depending on the purpose of collecting the material, it may undergo a number of processing steps, which may include transport, handling and storage of the biological material, etc. For example, in personalized and accurate medical fields, such as cell and gene therapy, biological material may be collected from a patient or donor and transported to a processing facility for processing to generate therapeutic products before being transported again and applied to the patient. These treatment steps typically involve making a series of selections and decisions to obtain the desired treatment results. For example, in packaging and shipping biological materials, the type of packaging may be selected from a plurality of packaging options to package the biological materials in a manner that aids in preserving the biological materials and facilitating subsequent handling (including shipping and storage). As another example, when cooling or cryogenically preserving biological material, it may be necessary to set operating conditions of the cooling device, which may involve setting a number of parameters, which may include, for example, cooling temperature and cooling time. In the past, these selections/decisions were made by human experts and/or operators. These choices and decisions must be based on empirical data available to the relevant operator, or on fixed operating protocols, which makes it difficult to ensure that the decisions or selected parameters (including machine operating parameters) are optimized to ensure that the quality of the biological material is adequately or optimally maintained during its processing. Erroneous decisions or mistakes are also difficult to avoid in the case of selections or decisions made according to a fixed protocol, or otherwise limited by the experience of the operator. These may have an adverse effect on the results of the treatment, for example, the quality of the biological material being treated. There is a need to address or ameliorate one or more of the disadvantages or limitations associated with the prior art, or at least to provide a useful alternative. Disclosure of Invention According to at least a first aspect of the present invention there is provided a method for biological material processing comprising: receiving at least one input parameter associated with a biological material; retrieving, by the data retrieval module, the first data set from the data store based on the at least one input parameter; Selecting, by an algorithm selection module, a first machine learning algorithm for processing the at least one input parameter from a plurality of candidate machine learning algorithms, wherein the first machine learning algorithm is selected based on the at least one input parameter or the first data set; training the first machine learning algorithm using at least a portion of the first data set; applying the trained first machine learning algorithm to the at least one input parameter to determine a first processing parameter for subsequent processing of the biological material, and Outputting the first processing parameter for subsequent processing of the biological material. According to at least a second aspect of the present invention there is provided a method for biological material processing comprising: receiving at least one input parameter associated with a biological material; Selecting, by an algorithm selection module, a first machine learning algorithm for processing the at least one input parameter from a plurality of candidate machine learning algorithms, wherein the first machine learning algorithm is selected based on the input parameter; Retrieving a first data set from a data store based on the first machine learning algorithm; training the first machine learning algorithm using at least a portion of the first data set; applying the trained first machine learning algorithm to the at least one input parameter to determine a first processing parameter for subsequent processing of the biological material, and Outputting the first processing parameter for subsequent processing of the biological material. According to at least a third aspect of the present invention, there is provided a system for controlling the processing of biological material, the system comprising: at least one processor, and A memory storing computer program instructions that, when executed by the at least one processor, cause the system to perform the method of the first or second aspect of the invention. Brief description of the drawings Some embodiments of the invention are described below, by way of non-limiting example only, wit