Fluid sample classification

Abstract

A method 100 for classifying a fluid sample is disclosed. The method includes the following steps: a. at least partially separating 110 one or more of the chemical components of the fluid sample; b. measuring and recording 120 the amounts of the separated chemical components of the sample during or after the chemical separation; c. measuring and recording 130 a spatial or temporal separation profile of the sample components during or after the separation to provide a data set; d. comparing 140 the amounts of the separated components to one or more reference samples; e. comparing 150 the spatial or temporal separation profile to corresponding profiles of the or each reference sample; f. assigning 160 a similarity score to the sample based on the similarity of the amounts or profiles of the separated components, or both, as performed under steps d.140 and e.150 above, with equivalent amounts and / or profiles of the or each reference sample; and g. providing a classification of the sample based on the similarity score 170.

Description

[Technical field]

[0001] The present invention relates to methods and computer programs for the classification of samples that have undergone separation of their components, for example by either chromatography or electrophoresis, and more particularly to methods for classifying such samples based on relative abundance and component profile similarity to a reference sample. [Background technology]

[0002] In the production of biopharmaceuticals such as vaccines, antibodies, recombinant proteins, gene therapy vectors, etc., several chromatographic separation steps are usually required to remove various contaminants and impurities from the product. At each step of the manufacturing process, both quantity and purity need to be checked against reference samples. Summary of the Invention [Problem to be solved by the invention]

[0003] However, separation profiles often show multiple molecular peak bands that may overlap. Analysis of such complex separation profiles adds significant cost and process time. Furthermore, separation profiles of complex samples are difficult to analyze accurately and may introduce individual operator bias. Therefore, there is great interest in rapid automated analysis to eliminate personal bias and reduce the manufacturing time of biopharmaceuticals. Therefore, there is a need for methods and computer programs for sample comparison that can be rapid and automated as needed. [Means for solving the problem]

[0004] One aspect of the present invention is to provide a method for comparing different samples in a biopharmaceutical process, which can be implemented by a computer program. This is achieved by the introduction of a similarity score based on a two-dimensional analysis of the relative abundance and component profile similarity to a reference sample. The relative abundance is a measure of the magnitude of the different chemical components of a sample compared to the magnitude of the components of the reference sample. The component profile similarity calculation is a measure of the similarity of the spatial or temporal profile of the separated components generated by a separation process compared to the profile of one or more reference samples that have undergone the same separation process. The resulting two-dimensional data set forms the basis for the classification of the samples by providing a similarity score for each sample that allows an estimation of the similarity between the subject sample and the reference sample. The analysis method can be automated and implemented using computer analysis software and appropriate hardware after the classification criteria have been established.

[0005] One advantage is that such an analytical method allows for a rapid and operator-independent classification scheme, and limits for grouping samples can be easily set for automated analysis. This method allows for decisions to be made, for example, if the manufacturing process is working satisfactorily or if the separation parameters need to be changed. Furthermore, it is common for the separation of sample components to be incomplete, in other words, for the bands of the measured components to overlap, resulting in data that are difficult to analyze. The proposed method allows for such incomplete separation by not only looking at certain peaks of the measurement, but by comparing the measured profile with a reference in the manner described immediately above.

[0006] Further preferred embodiments of the invention are set forth in the dependent claims. [Brief description of the drawings]

[0007] [Figure 1]Shown is an image of the analyzed Coomassie stained gel. The different samples (1-10) were separated on a polyacrylamide gel and subsequently stained with Coomassie stain. The gel was analyzed using the analysis software Image Quant TL (available from Cytiva Life Sciences). [Diagram 2] Electrophoretic lane profile of sample 5 in FIG. 1 is shown. [Diagram 3] Figure 3 shows a two-dimensional similarity score plot of the samples of Figures 1 and 2. The relative amounts of the samples (y-axis) and lane profile similarity scores (x-axis) are displayed in one plot. In this example, sample number 8 was taken as the reference sample. [Figure 4] One way to group the different samples in FIG. 3 into three groups (A-C) is shown. [Diagram 5] Chromatograms of two protein samples are shown. [Figure 6] 1 shows a 2D similarity scatter plot of 185 chromatograms from different cycles in a protein purification process produced using an embodiment of the present invention. [Figure 7A] 1 illustrates a graphical user interface (GUI) for presenting results generated using an embodiment of the present invention. [Figure 7B] 1 illustrates a graphical user interface (GUI) for presenting results generated using an embodiment of the present invention. [Figure 8] 1 illustrates methods according to various embodiments of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0008] definition As used herein, the terms "comprises," "comprising," "containing," "having," and the like can have the meanings ascribed to them and can mean "include," "comprise," and the like; "consisting essentially of" or "consisting essentially of" likewise have the meanings ascribed to them in patent law, and the terms are open-ended, allowing for the presence of more than what is recited, but excluding prior art embodiments, so long as the basic or novel characteristics of what is recited are not changed by the presence of more than what is recited.

[0009] In one aspect, the present invention discloses a computer-assisted method for the automated analysis of a sample that has undergone separation, which term includes the formation of at least some of the components of the sample into more concentrated aliquots, fractions or streams. The term separation includes partial separation.

[0010] In certain embodiments, the sample may be an intermediate or final product in a biopharmaceutical manufacturing process. Additionally, the reference sample may either undergo chemical separation and subsequent analysis when the process is created, or may be stored for chemical separation analysis at a later stage. How to store reference samples for future analysis is well known in the field of biopharmaceutical manufacturing. Stored reference sample data may also be used for comparison.

[0011] In some embodiments, the separation is performed by electrophoresis and the separated molecules are detected using color stains or fluorescent dyes. The lane profiles of the electrophoretic separation are then compared with respect to both the amount of sample components present in the lane and how similar the lane spatial profile is compared to a reference sample.

[0012] In some embodiments, the separation is performed by chromatography, and the separated molecules are detected using optical absorption measurements. The separation profiles are then compared, both in terms of the amount of sample eluted from the chromatography column and the similarity of the sample profiles (also called chromatograms). In this way, the reproducibility of different batches in a bioprocessing manufacturing process can be quickly evaluated, and decisions regarding the continuation of the process can be easily made.

[0013] Working Example Example 1 Different protein samples were analyzed using SDS-PAGE electrophoresis. The resulting Coomassie stained gel is shown in FIG. 1. Some samples contain multiple proteins and the lane profiles obtained after electrophoretic separation are complex, i.e., show many overlapping peaks. Such lane profiles are difficult to compare manually by eye. The opacity (also called optical density) of each lane or lanes of interest can be measured with respect to spatial position along the lane. Such measurements are given in the graph shown in FIG. 2 only for lane 5 of FIG. 1, but similar measurements can be made for the other lanes shown in FIG. 1. Using the data generated from the graph of FIG. 2 (which does not have to be shown in a graph but can exist purely as data), the lane profiles were analyzed with respect to the amount of protein (in this case opacity=optical density) and with respect to how the different lane profiles correlate spatially, using the Pearson correlation coefficient. This calculation compares two arrays of data, in this case sample lane profile data of the type illustrated in FIG. 2, with a reference sample lane profile (in this case lane 8). Calculated values ​​can range from -1 (negative correlation) to 0 (no correlation) to 1 (positive correlation). The Pearson pairwise correlation calculation is one method for correlating different lane profiles using a reference lane profile or a reference average of several lane profiles. However, there are many other methods that can be used to correlate lane profiles.

[0014] The results of the correlation calculations for each of the ten lanes shown in FIG. 1 are displayed in a two-dimensional plot in FIG. 3. If a particular lane is found to correlate well with the reference sample in terms of the amount of sample components, the separated proteins in this lane will give rise to the opacity bands shown in FIG. 1 and will be given a score close to 1 (y-axis), and if the entire lane profile for a particular lane correlates well with the reference lane, it will be given a score close to 1 (x-axis). These data provide two similarity comparisons: the amount of chemical component (e.g., protein) similarity (y-axis) and the actual chemical component profile similarity (x-axis). It is also clear that the samples in this example are classified into different groups based on the separation profile similarity scores.

[0015] As shown in Figure 4, data points can be easily categorized by grouping samples. Such a classification allows for rapid analysis and does not rely on the user's estimation of how similar different profiles are. Restrictions for grouping samples can be set based on: A) only the amount of sample similarity; B) Chemical separation profile similarity only; C) Sample quantity and chemical separation profile similarity.

[0016] Thus, depending on which samples were analyzed, different rules for grouping the samples can be applied, for example, only samples in group C in Figure 4 would be classified as falling within an acceptable range of similarity to the reference sample.

[0017] Example 2 As shown in FIG. 5, a similar technique to that described above can be applied to chromatographic separations, where a spectrophotometer is used to measure bands of chemical components such as proteins (typically UV absorbance to measure protein concentration) emerging from a column containing a chromatographic medium. The resulting data (called a chromatogram) is shown in FIG. 5 with two chromatograms overlaid, with the data set including photodetector output readings, equivalent to the opacity / component amount measurements in FIG. 2, and time (time-related) data, equivalent to the space / distance data also shown in FIG. 2. The data set is processed as above to again provide a comparative score of component amount and chemical similarity with a reference sample or average sample data. The processed data then classifies the samples, for example, as a pass or fail outcome in a biopharmaceutical manufacturing process. In FIG. 5, two chromatograms of two protein samples with the same starting concentration were compared using an Aekta pure 25 chromatography system (available from Cytiva Life Sciences). The samples differed in the type of Strep-Tactin tag used in the separation. As a result, the chromatograms (i.e., time separation profiles) showed different peak shapes and subtle changes in the separation profile. For this portion of the chromatogram, similarity score analysis yielded a similarity score of (0,90;0,87) for sample 1, where 0,90 is the separation profile similarity score and 0,87 is the relative amount, indicating that sample 1 differs both in the amount eluted and to some extent also in chemical binding to the separation matrix compared to the reference sample.

[0018] Those skilled in the art will appreciate that various analyses can be performed according to the present invention. For example, when considering the example of chromatography, the additional dimensions in the chromatography analysis can be, for example, one or more of pH, conductivity and / or pressure. Thus, chromatography run data, such as time-related data corresponding to pressure, pH and / or conductivity data, can be used to classify samples. It should be noted that such parameters may be used as y-axis data (ordinate data) for a similarity plot instead of or in addition to relative amounts.

[0019] FIG. 6 shows a 2D similarity scatter plot of 185 chromatograms from different cycles in a protein purification process produced using an embodiment of the present invention. The plot shows how the chromatogram relative peak areas correlate with the separation profile similarity scores. Such plot data showed that using embodiments of the present invention, many runs can be analyzed at high resolution, further identifying data points that, for example, cannot be easily determined by a skilled operator. Thus, various embodiments of the present invention can be used to alert operators to outliers and / or can be used in automated processing systems to optimize control parameters of a chromatography-based bioprocessing system.

[0020] In Figure 6, data was obtained for each of 185 chromatograms from a purification cycle with pH step elution using a Fibro HiTrap PrismA™ chromatography unit in an Aekta Pure 25™ system. A reference sample was selected as the first chromatogram in the series. All chromatograms were clearly very similar, but a Pearson correlation coefficient calculation was used to detect two runs that differed in terms of peak shape. These two values ​​appear as outliers on the left side of Figure 6. After inspection, all cycle chromatograms were judged to pass. (Note: some values ​​in these chromatograms are saturated and therefore the peak areas are not proportional to the relative amounts in this particular data set.)

[0021] FIG. 7 shows a graphical user interface for presenting results generated using one embodiment of the present invention. The GUI includes a window that provides a 2D visualization of the data. In this example, a similarity score vs. relative volume plot is shown. Such a 2D scatter plot provides easy visualization for the user. The GUI may also, or alternatively, display profiles, such as electrophoretic lanes or chromatograms, and allow user selection of a reference profile to show the two-dimensional sample data in a scatter plot.

[0022] Additionally, in various embodiments, the 2D scatter plot allows the user to select an area of ​​interest for analysis, remove all data points from the analysis that reach the maximum limits of the detector, and / or set limits for grouping samples into different groups using the scatter plot. Additionally, various embodiments may also allow the scatter plot to track the protein purification process, for example, by using trend lines or color gradients.

[0023] 8 shows a method according to various embodiments of the present invention. The method 100 includes the steps of: a. at least partially separating 110 one or more of the chemical components of a fluid sample; b. measuring and recording 120 the amount of the separated chemical components of the sample during or after the chemical separation; c. measuring and recording 130 the spatial or temporal separation profile of the sample components during or after the separation to provide a data set thereof; d. comparing 140 the amount of said separated components with one or more reference samples; e. comparing 150 the spatial or temporal separation profile with the corresponding profile of the or each reference sample; f. assigning 160 a similarity score to the sample based on the similarity of the amount or profile comparison of the separated components, or both, as performed under steps d.140 and e.150 above, with the equivalent amount and / or profile of the or each reference sample, respectively; g. providing 170 a classification of the sample based on the similarity score.

[0024] In various embodiments related to electrophoresis, the method 100 can include one or more of the following steps:

[0025] Selecting a region of interest in an image: For electrophoresis, the user can create lane boxes, for example, using a GUI of the type described above.

[0026] 2a. Optionally, saturated regions of the lane profile, i.e. regions where the detector has reached its maximum, can then be excluded from the analysis. This can be automated or user-driven.

[0027] Correcting Uneven Migration: The user can adjust the lane boxes and lanes to correct for uneven migration across the electrophoretic gel. Optionally, the lane profile scale may be corrected by the user or automatically by comparison to marker samples, i.e. samples with known molecular weights, in other lanes.

[0028] In various chromatographic embodiments, the method 100 can include one or more of the following steps:

[0029] Selecting regions of interest in the chromatogram either manually or automatically by analysis software. This step is optional, alternatively the complete chromatogram can be analyzed.

[0030] 2b. Optionally, exclude from the analysis saturated regions of the lane profile, i.e., regions where the detector has reached its maximum value.

[0031] 3b. Aligning the chromatograms for comparison. Alignment of the chromatograms can be done automatically by a software algorithm or automatically by the user. Alignment is typically based on the time of the performed chromatographic run, e.g., the start of a phase or the elution of a known reference sample. This step is optional and in some cases no alignment is required.

[0032] The following steps can then be applied to both the electrophoretic and chromatographic analysis:

[0033] 4. If the data sets have different numbers of data points, individual electrophoretic lane profiles or chromatograms can be sampled or interpolated to obtain the same number of data points per sample.

[0034] 5. An analysis of all data points or a user defined analysis range can then be performed. For example, if there is only one peak of interest, the analysis range can be adjusted accordingly, either automatically or by the user.

[0035] 6. Calculate the integrated signal of the lane or sample in the chromatogram. Alternatively, sum the volumes of all detected bands or peaks for each lane.

[0036] 7. In a preferred embodiment, all possible pairwise comparisons of N samples are made. This results in NXN arrays, e.g. one array for relative abundance and one array for profile similarity scores. These can also be used to compare pressure, pH and / or conductivity data sets for chromatography.

[0037] 8. The GUI allows the user to select one reference lane or chromatogram and then generate a 2D scatter plot showing relative abundance on the y-axis and profile similarity scores on the x-axis.

[0038] Various embodiments and features of the present invention have been described above. This written description further uses examples to disclose the invention, including preferred embodiments, and is provided to enable one skilled in the art to practice the invention, including making and using any device or system, and performing any incorporated methods. The patentable scope of the invention is defined by the claims, and may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they have structural elements that do not differ from the language of the claims, or if they include equivalent structural elements that do not differ substantially from the language of the claims. Any patents or patent applications or commercially available products, such as systems or software, mentioned in the body of this specification are hereby incorporated by reference in their entirety, where permitted, as if they were individually incorporated.

Claims

1. 1. A method (100) for classifying a fluid sample, the method comprising: a. at least partially separating (110) one or more chemical components of the fluid sample; b. measuring and recording (120) the amount of the separated chemical components of the sample during or after chemical separation; c. measuring and recording (130) a spatial or temporal separation profile of the sample components during or after the separation to provide a data set; d. comparing the amounts of the separated components to one or more reference samples (140); e. comparing (150) the spatial or temporal separation profile to a corresponding profile of the or each reference sample; f. assigning (160) a similarity score to the sample based on the similarity of the amounts and profiles of the separated components compared to equivalent amounts and profiles of the or each reference sample, respectively, as performed under step d (140) and step e (150) above; g. providing a classification of the samples based on the similarity scores (170); A method (100).

2. 2. The method (100) of claim 1, further comprising classifying a plurality of samples, step b comprising providing (120) for each of the samples a dataset of the separated components or amounts of each separated component, and step c comprising providing (130) for each sample a dataset of the spatial or temporal separation profile, the two datasets being processed by an algorithm to provide a two-dimensional sample dataset for each sample used in steps d to g.

3. 3. The method (100) of claim 2, wherein the different groups of samples represent pass or fail results in a quality control of a biopharmaceutical manufacturing process.

4. The method (100) of claim 2 or 3, wherein the presence or absence of samples in the different groups results in a change in the manufacturing process of the biopharmaceutical.

5. 5. The method (100) of any one of claims 1 to 4, wherein the chemical separation is electrophoresis.

6. 5. The method (100) of any one of claims 1 to 4, wherein the chemical separation is chromatography.

7. 7. The method (100) of claim 6, wherein chromatographic run data, such as time series of pressure, pH and / or conductivity data, or a combination thereof, is used to classify the samples.

8. 8. The method (100) of any one of claims 1 to 7, wherein the spatial or temporal separation profile similarity score is calculated using a Pearson correlation function.

9. A computer program comprising a program code for performing the method (100) according to any one of claims 1 to 8, when the program is run on a computer.

10. 10. The computer program of claim 9, further operable to provide a graphical user interface (GUI) for user selection and / or presentation of reference profiles and / or regions of interest for analysis and / or data, and / or electrophoretic lanes and / or chromatograms and / or two-dimensional scatter plots.

11. 11. The computer program of claim 10, wherein the GUI is further configured to allow a user to remove data points from the analysis that have reached a maximum detector limit.

12. 12. The computer program of claim 10 or 11, wherein the GUI is configured to present a two-dimensional scatter plot that can be used to set limits for grouping samples into different groups and / or to track a protein purification process.

13. 13. The computer program of claim 12, wherein the GUI is configured to present trend lines and / or color gradients to assist in tracking a protein purification process.

14. A biopharmaceutical manufacturing plant configured to carry out the method (100) according to any one of claims 1 to 8 for checking and / or controlling a biopharmaceutical manufacturing process.

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