Automated detection of cell packed volume

Abstract

A system may include a container holder configured to (i) hold a container containing a sample and (ii) rotate the container axially. A system may include a sensor having a sensing axis passing through the container. A system may include a controller operatively coupled to the container holder and the sensor and configured to: control the container holder to rotate the container axially; control the sensor to capture sensor data of the container at multiple axial rotation angles; analyze the captured sensor data to determine the shape of the top surface of the sample; and determine the sample volume based on the shape of the top surface.

Description

Technical Field

[0001] This application relates generally to the manufacturing process of biopharmaceutical products, and more specifically to the automated detection of cell hematocrit (PCV) during the manufacturing process of biopharmaceutical products and / or other centrifugation processes. Background Technology

[0002] In the manufacture of certain biopharmaceutical products (e.g., biotherapeutic proteins), bioreactors are used to culture cells prior to harvesting the desired drug product. For some biopharmaceutical products, harvesting is achieved via a centrifugation process, in which the biopharmaceutical product is agitated to form a liquid drug product. Prior to the centrifugal harvesting process, the precipitate of the biopharmaceutical product is placed in a container (e.g., vial, cartridge, syringe, dish, seal, etc.). The cell volume (PCV) of this precipitate is measured to configure the centrifugation process. For example, PCV can be used to configure the centrifuge drum discharge interval of a stainless steel centrifuge or to calculate the split flow rates of the heavy phase (cell discharge / waste) and light phase (supernatant / product) of a disposable centrifuge. Therefore, accurately determining the cell volume (PCV) of the precipitate in the container is important because errors in measuring the PCV of the precipitate can directly affect the yield of the manufacturing process and / or the operation of any post-filtration steps in the manufacturing process.

[0003] Conventionally, the PCV of a precipitate is determined by manually inspecting the container and comparing the height of the top surface of the precipitate to a measurement line printed on the container surface. This manual process is highly variable (up to 10%–20% relative error), thus affecting the accuracy of PCV measurements. This error has several sources. First, the manual dilution and visual verification process itself is susceptible to measurement errors associated with parallax. Second, the top surface of the precipitate is often not flat or orthogonal to the container axis. This makes it difficult to accurately determine the height of the top surface. Third, the printed measurement line on the container side has errors in its position (typically with a specified accuracy of 1%). Furthermore, in many cases, the printed measurement line is incomplete or worn. Summary of the Invention

[0004] The systems and methods described herein typically employ automated techniques to measure the PCV of sediment within a container. For example, the system may include sensors (e.g., image sensors or laser sensors) capable of automatically detecting the height of the leading edge of the sediment within the container. The techniques may include using mechanical means to rotate the container to capture a series of heights of the top surface of the sediment. These techniques can then apply fitting algorithms to this series to define the shape of the top surface of the sediment. Thus, the disclosed techniques enable modeling of the actual geometry of the top surface of the sediment when calculating PCV. This corrects for inaccuracies in conventional techniques that assume a uniform top surface at maximum height. Additionally, in some embodiments, to reduce reliance on container measurement lines, these techniques may include comparing sensor data with model data of the container (e.g., manufacturer specifications for container dimensions) combined with a derived shape of the top surface of the sediment to determine the PCV of the sediment. Therefore, by applying the PCV measurement techniques disclosed herein, the accuracy of PCV measurement is improved. Consequently, when more accurate PCV values ​​obtained through the methods disclosed herein are used to configure a centrifugal harvesting process, the resulting process produces higher yields. In some scenarios, the ability to accurately measure the PCV of the sediment completely eliminates the need for manual dilution.

[0005] In some aspects, the technology described herein relates to an automated visual inspection system comprising: a container holder configured to (i) hold a container containing a sample and (ii) rotate the container axially; a sensor having a sensing axis passing through the container; and a controller operatively coupled to the container holder and the sensor and configured to: (1) control the container holder to rotate the container axially; (2) control the sensor to capture sensor data of the container at multiple axial rotation angles; (3) analyze the captured sensor data to determine the shape of the top surface of the sample; and (4) determine the sample volume based on the shape of the top surface.

[0006] In some respects, the technology described herein relates to a method for automated analysis of a sample contained in a container, the method comprising: (1) controlling a container holder holding the container via a controller to rotate the container axially; (2) controlling a sensor via the controller to capture sensor data of the container at multiple axial rotation angles; (3) analyzing the captured sensor data via the controller to determine the shape of the top surface of the sample; and (4) determining the sample volume based on the shape of the top surface.

[0007] In some respects, the techniques described herein relate to one or more non-transitory computer-readable media storing instructions that, when executed by the processing hardware of a controller, cause the controller to perform the following actions: (1) controlling a container holder that holds the container to rotate the container axially; (2) controlling a sensor to capture sensor data of the container at multiple axial rotation angles; (3) analyzing the captured sensor data to determine the shape of the top surface of the sample; and (4) determining the sample volume based on the shape of the top surface. Attached Figure Description

[0008] Those skilled in the art will understand that the accompanying drawings described herein are included for illustrative purposes and are not intended to limit the scope of this disclosure. The drawings are not necessarily drawn to scale, but rather focus on illustrating the principles of this disclosure. It should be understood that in some cases, various aspects of the described embodiments may be exaggerated or enlarged to aid in understanding the described embodiments. In the drawings, similar reference numerals generally refer to components that are functionally similar and / or structurally similar.

[0009] Figure 1A and Figure 1B This is a simplified block diagram of an example system for automatically determining the PCV of a sample.

[0010] Figure 2A The image data shows example images of a container holding sediment, captured by sensors at multiple rotation angles.

[0011] Figure 2B This demonstrates the container evaluation application in analysis. Figure 2A A detailed view of the extracted data from the image data.

[0012] Figure 3 It is a curve showing the height of the leading edge of the top surface of the precipitate.

[0013] Figure 4 An example process is described for a container evaluation application to preprocess a set of image data to align the image data.

[0014] Figure 5 An example process is described for a container evaluation application to project measurement lines onto a container.

[0015] Figure 6 A flowchart is shown for an example method used to automatically inspect containers. Detailed Implementation

[0016] The various concepts described above and discussed in more detail below can be implemented in any of a variety of ways, and the described concepts are not limited to any particular implementation. Examples of implementations are provided for illustrative purposes.

[0017] While the examples described herein typically involve determining the PCV of a precipitate, these techniques can be applied to other biopharmaceutical product manufacturing techniques. For example, in other embodiments, these techniques can be adapted to determine PCV during platelet counting or to determine resin slurry concentration during chromatography.

[0018] Figure 1A This is a simplified block diagram of an example PCV system 100 that can be used to automatically determine the sample. System 100 includes a container 105, a sensor 110, a holder 115a, a controller 130, and in some embodiments includes a light source 120.

[0019] Container 105 can be any suitable vessel, device, or system for containing precipitate 107 (such as a sample or biopharmaceutical product). For example, the container can be a vial, cartridge, syringe, glassware, etc. Container 105 is at least partially transparent so that precipitate 107 can be sensed by sensor 110 while contained within container 105. In some embodiments, precipitate 107 is a biopharmaceutical product about to undergo a centrifugation harvesting process. In these embodiments, container 105 can be the same container used during the centrifugation harvesting process.

[0020] As shown, sensor 110 is configured to have a sensing axis 111 oriented toward container 105 and / or the sediment 107 contained in the container. In some embodiments, sensor 110 is an image sensor or camera configured to capture image data of container 105. In these embodiments, sensing axis 111 may also be referred to as optical axis 111. As will be described in more detail below, controller 130 may analyze the image data generated by sensor 110 to detect the height of the top surface 108 of sediment 107. Therefore, it is preferred that camera 110 includes a telecentric lens to avoid optical aberrations associated with endoscopes when measuring the height of the top surface 108. For this purpose, the spatial uniformity associated with the telecentric lens significantly reduces the need to account for optical distortion when measuring the height of the top surface 108.

[0021] In embodiments where sensor 110 is an image sensor or camera, system 100 may further include a light source 120. The light source 120 may be a light-emitting diode (LED) light source configured to have an illumination axis 121 reflected from the top surface 108 of the deposit 107. In some embodiments, the light source 120 provides uniform backlighting to the container 105 to improve scene uniformity when analyzing captured image data. Additionally, in some embodiments, the light source 120 may emit light in the infrared band to improve the ability to distinguish the leading edge of the top surface 108 from the rest of the top surface 108. This improves the ability of the controller 130 to accurately determine the height of the top of the top surface 108 when analyzing image data.

[0022] In other embodiments, sensor 110 is a laser depth sensor. For example, laser sensor 110 may be a laser point sensor configured to sense depth at a specific point along sensing axis 111, or a laser line sensor configured to sense multiple depths along a plane defined by the sensing axis. Although Figure 1A Sensor 110 is depicted as being positioned horizontally relative to container 105, but in some embodiments where sensor 110 is a laser sensor, sensor 110 may be positioned at other angles relative to container 105.

[0023] System 100 also includes a holder 115a configured to hold the top portion of container 105, a plug inserted into container 105, a lid placed on container 105, etc. Holder 115a may include clamps and / or other holding elements configured to securely hold container 105 in a controllable pose. For example, holder 115a may be configured to rotate container 105 about a vertical axis such that the entire sweep of sediment 107 passes through sensing axis 111. Because the shape of top surface 108 is typically non-uniform, this allows controller 130 to accurately model the actual shape of top surface.

[0024] In some embodiments, the holder 115a and / or sensor 110 are arranged such that the sensing axis 111 is offset from the lateral axis of the container 105. For example, the holder 115a may be configured to hold the container 105 at an offset angle (e.g., 5°, 10°, 15°) relative to the vertical axis. Similarly, the sensor 110 may be configured, for example, by raising the sensor 110 above the top surface 108 and tilting the sensing axis 111 downward, to make the sensing axis 111 at an offset angle (e.g., 5°, 10°, 15°) relative to the container 105. By holding the container 105 at an offset angle, the illumination axis 121 can be incident on a larger portion of the top surface 108, thereby improving the contrast between the top surface 108 and the sides of the sediment 107. This contrast improves the ability of the controller 130 to identify the height of the top surface 108, thereby improving the accuracy of height measurement. Although Figure 1A An embodiment is depicted in which the holder 115a holds the upper portion of the container 105, but in other embodiments, the holder 115a or 115b may alternatively hold the lower portion of the container 105.

[0025] refer to Figure 1B A simplified block diagram of example system 150 is shown, in which holder 115b holds the lower portion of container 105. In example system 150, holder 115b can be configured to receive container 105 when an operator places container 105 into the cavity. Therefore, the operator may not need to operate the clamping mechanisms included in many types of holders 115a. This can increase the speed at which multiple containers 105 can be analyzed via the automated inspection techniques disclosed herein. It should be understood that in this embodiment, the bottom of container 105 is not visible to sensor 110. Therefore, in these embodiments, controller 130 can obtain a model of container 105 indicating the dimensions of container 105 to determine the depth to which the bottom of container 105 is held within holder 115b. Therefore, controller 130 can utilize this depth information when calculating the height of top surface 108.

[0026] In any embodiment, controller 130 may be operatively coupled to sensor 110, holder 115a or 115b, and in some embodiments to light source 120. Controller 130 may be a server, desktop computer, laptop computer, tablet device, dedicated control device, or any other suitable type of computing device. Figure 1A and Figure 1BIn the example embodiment shown, controller 130 includes processing hardware 132, network interface 134, display device 136, user input device 137, and memory unit 138. However, in some embodiments, controller 130 includes two or more computers located in the same location or geographically separated from each other. In these distributed embodiments, the operations described herein relating to processing hardware 132, network interface 134, and / or memory unit 138 may be divided among the various processing units, network interfaces, and / or memory units.

[0027] Processing hardware 132 includes one or more processors, each of which may be a programmable microprocessor that executes software instructions stored in memory cell 128 to perform some or all of the functions of controller 130 as described herein. Alternatively, some processors in processing hardware 132 may be other types of processors (e.g., application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), etc.), and some functions of controller 130 as described herein may alternatively be implemented in part or in whole by such hardware. Memory cell 138 may include one or more physical memory devices or cells containing volatile and / or non-volatile memory. Any suitable type of memory, such as read-only memory (ROM), solid-state drive (SSD), hard disk drive (HDD), etc., may be used.

[0028] Network interface 134 may include any suitable hardware (e.g., front-end transmitter and receiver hardware), firmware, and / or software configured to communicate via one or more communication networks and / or using one or more communication protocols. For example, network interface 134 may be or include an Ethernet interface and / or a serial interface via which controller 130 controls the operation of sensor 110, holder 115a or 115b, and / or light source 120.

[0029] Display device 136 may use any suitable display technology (e.g., LED, OLED, LCD, etc.) to present information to the user, and user input device 137 may be a keyboard or other suitable input device. In some embodiments, display device 136 and user input device 137 are integrated within a single device (e.g., a touchscreen display). Typically, display device 136 and user input device 137 may jointly enable a user to interact with a graphical user interface (GUI) provided by controller 130, for purposes such as determining the properties of container 105 and / or the precipitate 107 contained therein (e.g., the hematocrit (PCV) of precipitate 107). However, in some embodiments, controller 130 does not include display device 136 and / or user input device 137.

[0030] Memory unit 138 stores non-transitory instructions for one or more software applications, including a container evaluation application (not depicted). When executed by processing hardware 132, the container evaluation application is typically configured to communicate with sensor 110, holder 115a or 115b, and / or light source 120 to analytically determine the characteristics of container 105 and / or the sediment 107 contained therein. For example, in some embodiments, the container evaluation application may be configured to cause holder 115a or 115b to rotate container 105 at a fixed rate. In this example, the container evaluation application may be configured to control sensor 110 to capture sensor data associated with container 105 at fixed intervals (e.g., every 10°, every 20°, every 30°, every 60° rotation). As another example, to reduce motion blur, the container evaluation application may alternatively be configured to control holder 115a or 115b to rotate container 105 at discrete intervals (e.g., 10° intervals, 20° intervals, 30° intervals, 60° intervals). In this example, the container evaluation application can be configured to cause sensor 110 to capture sensor data from container 105 after holder 115a or 115b has completed a rotation interval. In embodiments where sensor 110 is an image sensor or camera, the container evaluation application can first control light source 120 to emit illumination light before controlling holder 115a or 115b and sensor 110. In any case, the container evaluation application can compile the sensor datasets captured at each interval into a sequence of sensor data.

[0031] In addition to the container evaluation application, memory unit 138 can be configured to store model data representing the dimensions of container 105. For example, the model data can be obtained from manufacturer documentation provided by the manufacturer and / or supplier of container 105. As another example, the model data can be a 3D scan and / or model of the container that includes dimensional information associated with container 105. The container evaluation application can be configured to access the model data to determine the characteristics of container 105 and / or sediment 107. For example, after determining the shape of the top surface 108, the container evaluation application can use the model of container 105 to determine the inner circumference of the lower portion of sediment 107. It should be understood that many containers 105 are not cylindrical along their entire length. Therefore, the model data can model different dimensions of container 105 along its entire length.

[0032] Turning Figure 2A and Figure 2BExample image data 212 of a container 205 (e.g., container 105) containing sediment 207 (e.g., sediment 107) captured by a sensor (e.g., sensor 110) is shown. As described above, the sensor can be configured to capture image data 212 according to instructions from the container evaluation application when the container evaluation application controls the holders (e.g., holders 115a, 115b) to rotate the container 205. In the example shown, the container evaluation application configures the sensor to capture seven sets of image data 212a-g at intervals of 60° axial rotation. Figure 2A In the process, the height of the leading edge of the top surface 208 of the precipitate 207 varies under different rotation angles.

[0033] Figure 2B A detailed view of the data extracted by the container evaluation application when analyzing image data 212a is shown. Specifically, Figure 2B Point 213, representing the leading edge of the top surface 208 of the sediment 207, is depicted. The container evaluation application can determine the lateral position of point 213 by defining a central axis along the lateral midpoint of the image data representing the container 205. The container evaluation application can determine the vertical position of point 213 by detecting the intensity offset along the central axis in the image data between the darker side of the sediment 207 and the illuminated top surface 208 of the sediment 207.

[0034] The container evaluation application can then determine the height of point 213. Typically, there are two options for determining the height of point 213 based on image data—(1) by analyzing the pixel height of point 213, or (2) by comparing the height of point 213 with a measurement line on container 205. It should be understood that pixel height techniques can eliminate errors in PCV calculations introduced by manufacturing tolerances of container 205.

[0035] Regarding pixel height technology, in embodiments where the holder holds the top portion of the container 205 (e.g.) Figure 1A As shown), the container evaluation application can calculate the height based on the number of pixels from the bottom of container 205. In embodiments where the holder holds the bottom portion of container 205 (as shown) Figure 1B As shown, the container evaluation application can calculate the height based on the number of pixels from a predetermined depth at the bottom of container 205. For the measurement line technique, the container evaluation application can compare the height of point 213 with the boundary measurement line of container 205 to obtain the height value. Regardless of the technique, the container evaluation application can repeat this process for each set of image data 212b-f, generating a sequence that associates the axial rotation angle with the corresponding height of the top surface 208.

[0036] It should be understood that, in alternative embodiments where the sensor is a laser sensor vertically positioned above container 205, the container evaluation application can obtain a depth value from the sensor indicating the distance from the sensor to the top surface 208. In these embodiments, the depth of the bottom surface of the sediment can be known based on physical measurements of the system configuration and model data of container 205. Therefore, in these embodiments, the height of sediment 207 can be determined by subtracting the sensor depth value obtained for a specific edge of the top surface 208 from a predetermined depth of the bottom surface of sediment 207.

[0037] Turning Figure 3 Graph 300 shows the height of the leading edge of the top surface (e.g., top surface 108, 208) of the precipitates (e.g., precipitates 107, 207). It should be understood that, compared with... Figure 2A The scene depicted is different; the image data was captured at 10° intervals instead of 60° intervals. Additionally, although... Figure 3 The illustration shows that height is measured based on pixel height, but in embodiments using laser depth or container measurement lines, height can utilize other units of measurement. Regardless of the unit of measurement, container evaluation applications can apply interpolation techniques (such as linear interpolation) to connect the height values ​​of samples included in the sequence.

[0038] The container evaluation application can then determine the PCV of the sediment by identifying the minimum value of curve 300, dividing the sediment volume into a body with a flat surface up to the minimum height and a body with a top surface defined by curve 300. To determine the volume of the bottom body, the container evaluation application can analyze the model and / or measurement lines on the container to determine the volume associated with the minimum height. For the upper body, the container evaluation application can calculate the area below the curve of curve 300 and combine the area with the model data to determine the volume of the upper body. The container evaluation application then adds the two volumes to determine the PCV of the sediment. It should be understood that this technique may not resolve any contour of the top surface along the radial axis. Therefore, this technique can be understood as defining a minimum energy surface that defines the shape of the outer edge measured by the sensor.

[0039] To simplify calculations, container evaluation applications may alternatively assume that the top surface of the sediment is typically shaped like a sloping ellipse. Furthermore, based on experimental testing, a sloping elliptical shape is the most common shape for sediment contained in containers. Therefore, in these embodiments, the container evaluation application can define the shape of the sloping ellipse (and thus the top surface of the sediment) by identifying the maximum and minimum values ​​of graph 300 and the inner circumference of the container.

[0040] Such as about Figure 1AAs described, in some embodiments, the holder 115a may be configured to hold the container 105 at an offset angle to improve illumination of the top surface 108 of the sediment 107. Additionally, in some systems, the connection between the holder 115a and the container 105 may not result in perfect vertical alignment. Accordingly, when the holder 115a axially rotates the container 105, the position of the container 105 shifts between multiple sets of image data. In these embodiments, when performing actions such as... Figure 2A , Figure 2B and Figure 3 Before the analysis shown, the container evaluation application can first digitally align the image data to ensure that the height calculation is consistent across each set of image data.

[0041] Figure 4 An example process 400 is depicted in which a container evaluation application preprocesses a set of image data 412 (e.g., image data 212) to align the image data 412 with a vertical axis before analyzing the image data to determine the height of sediment 407 (e.g., sediment 107, 207) in containers 405 (e.g., containers 105, 205). Although Figure 4 The process for aligning image data in a system in which a container 405 is held by a holder 415 (e.g., holder 115a) via the top portion is demonstrated, but similar techniques can be applied to aligning image data in a system where the container is tilted when it rests in a holder (e.g., holder 115b) at the bottom portion of the holding container 405.

[0042] Starting with image (a), this represents image data 412 captured by an image sensor or camera (e.g., sensor 110). A center line 414 is superimposed on image data 412 to show that the holder 415 is holding the container 405 at an angle. Turning to image (b), an edge-finding technique is applied to identify the edges 416 of the container 405. More specifically, when image data 412 is correctly aligned, an edge-finding technique is applied to identify a pair of vertically aligned edges 416a, 416b equidistant from the center line 414. In the example shown, a rake-style edge-finding technique is implemented. That is, other edge-finding techniques may be applied in other embodiments.

[0043] In the image (c), edge 416 is used to define the lateral and rotational deviations of container 405 in image data 412. For example, a container evaluation application can use the detected edge 416 and the following knowledge to define the actual centerline 417 of container 405: (i) edges 416a, 416b are equidistant from centerline 417, and (ii) centerline 417 should be vertically aligned. Based on the lateral and rotational deviations between actual centerline 417 and centerline 414, the container evaluation application can determine the rotational and lateral deviations of the container in image data 412. Using the rotational and lateral deviation values, the container evaluation application can obtain an offset vector by which the pixels of image data 412 are translated to produce aligned image data 422. Because the aligned image data 422 is laterally centered and vertically aligned, the height value of sediment 407 is defined relative to the same viewpoint when the container evaluation application applies similar techniques to each set of image data obtained from the image sensor. This ensures that any deviation in the connection method between container 405 and holder 415 will not affect the accuracy of PCV calculation.

[0044] As mentioned above, the measurement lines on the container fade over time. Therefore, in embodiments that rely on the measurement lines to determine the PCV of deposits, the measurement lines may not be visible to the image sensor at all rotation angles. Therefore, in some embodiments, the container evaluation application may apply techniques to enhance the measurement lines and overlay them onto the image data to facilitate image analysis techniques that rely on the measurement lines.

[0045] Turning Figure 5 The example process 500 is illustrated, in which a container evaluation application virtually overlays measurement lines onto containers 505 (e.g., containers 105, 205, 405). As shown in image (a), the measurement line 519 of the container has faded, making it difficult to use as a baseline for measuring volume. It should be understood that while image (a) depicts container 505 as containing sediment, in other embodiments, process 500 may be applied before sediment is contained within container 505. Turning to image (b), the extracted region of interest is shown, where the measurement lines have faded. It should be understood that in some embodiments, the container evaluation application captures images (a) of container 505 at multiple different rotation angles and extracts the corresponding image (b) of the region of interest from each image (a).

[0046] Turning to image (c), the container evaluation application combines the extracted regions of interest to produce a minimum intensity projection (MIP) of the region of interest. Specifically, the MIP process assigns a minimum value (i.e., the darkest value) to each pixel and / or line of the image data to fill any gaps in the printed measurement lines. Thus, as shown in Figure (d), when the MIP technique is applied to fill the faded measurement line 519, the container evaluation application can easily identify the measurement line for determining the PCV of the deposit. It should be understood that the container evaluation application can apply optical character recognition or other similar techniques to detect the presence of digits on container 505 and exclude those pixels from the MIP analysis to prevent the presence of digits from causing broadband on each measurement line.

[0047] It should be understood that in some embodiments, the deposit is the same color as the measurement line 519, making it difficult to detect the lower boundary measurement. In these embodiments, the container evaluation application can extrapolate and / or project the measurement line downwards onto the area obscured by the deposit. For example, the container evaluation application can determine the pixel-by-pixel spacing between the identified measurement lines 529a and 529b, and extrapolate an additional measurement line below measurement line 529b at a distance matching that pixel-by-pixel spacing. In embodiments, container 505 is a pseudo-cylindrical container where the inner diameter varies at different heights along the length of container 505. In these embodiments, the measurement lines on container 505 may be unevenly spaced due to the variation in the inner diameter along the length. Therefore, the container evaluation application can analyze a model of container 505 to account for the uneven spacing between the measurement lines. Thus, even though the deposit obscures the measurement line 519 in the image data, the container evaluation application can still rely on the measurement line 519 to determine the PCV of the deposit.

[0048] Alternatively, the container evaluation application can use an empty container to extract the correspondence between the pixel heights of container 505 and the measurement lines, storing the pixel height associated with each of the printed measurement lines in the memory of a controller (e.g., controller 130). Therefore, when the container evaluation application analyzes image data of printed measurement lines 519 on container 505 obscured by deposits, it can compare the pixel heights of the deposits with the stored correspondences when determining the PCV of the deposits. In these embodiments, the container evaluation application can identify specific features of container 505 (e.g., the height of the top of the container) to align the stored pixel heights associated with the printed measurement lines with the analyzed image data. In some embodiments where the container evaluation application is configured to display sensor data representing container 505, the application can overlay extrapolated and / or stored measurement line indications onto the displayed image of the container for manual verification.

[0049] While the foregoing techniques describe a process for determining the PCV of deposits in a container, similar techniques can be used to determine the volume of liquid also included in the container. For this purpose, a container evaluation application can be configured to detect the meniscus height of the liquid in the container. Therefore, using the disclosed pixel-by-pixel or measurement line volume determination techniques, the container evaluation application can determine the volume associated with the height of the bottom edge of the meniscus. In some embodiments, the container evaluation application can determine the volume of liquid in the meniscus region based on the surface tension of the liquid and the contact angle between the liquid and the container walls. The container evaluation application can then subtract the PCV of the deposits from the volume associated with the bottom edge of the meniscus to determine the volume of liquid in the container. In some embodiments, the container evaluation application can additionally determine the volume of liquid in the meniscus region based on the surface tension of the liquid and the contact angle between the liquid and the container walls, and add the volume of the meniscus region to the volume associated with the bottom edge of the meniscus before subtracting the PCV of the deposits.

[0050] Turning Figure 6 A flowchart illustrating an example method 600 for automatically inspecting samples (e.g., precipitates 107, 207, 407) in containers (e.g., containers 105, 205, 405, 505) is shown. Method 600 can be executed by one or more processors (e.g., processing hardware 132), and a controller (e.g., controller 130) executes a container evaluation application stored in a memory unit (e.g., memory unit 138). The controller can be operatively coupled to a container holder (e.g., holders 115a, 115b, 415) that holds the container and is configured to axially rotate the container according to instructions from the controller.

[0051] The controller may also be connected to a sensor (such as sensor 110) configured to have a sensing axis (such as sensing axis 111) passing through the container. In some embodiments, the sensor is one of a laser line profilometer sensor and a laser displacement sensor configured to sense the distance between the sensor and the top surface of the sample (such as top surfaces 108, 208, 408). In other embodiments, the sensor is an image sensor, which in some embodiments includes a telecentric lens. In these embodiments, the controller may also be coupled to a light source oriented to emit illumination toward the image sensor such that the emitted illumination is reflected from the top surface of the sample. To improve the reflectivity of the illumination, in some embodiments, the container holder and the sensor are configured such that the sensing axis is offset from the lateral axis of the container by an offset angle.

[0052] The method begins at block 602, where the controller controls the container holder to rotate the container axially. At block 604, the controller controls the sensors to capture sensor data from the container at multiple axial rotation angles.

[0053] At box 606, the controller analyzes the captured sensor data to determine the shape of the top surface of the sample. In embodiments where the container is held at an offset angle, the controller can preprocess the captured sensor data by vertically and / or laterally aligning it (e.g., by applying techniques associated with process 400). To determine the shape of the top surface, the controller can determine the height of the leading edge of the sample's top surface at multiple axial rotation angles and define the shape by applying a fitting algorithm to the determined height. For example, the fitting algorithm could be a minimum energy surface (e.g., by applying techniques described with respect to graph 300) or a fitting algorithm that fits a tilted elliptical shape to the determined height.

[0054] At box 608, the controller determines the sample volume (e.g., PCV) based on the shape of the top surface. In some embodiments, the controller compares sensor data and the shape of the top surface with a model of the container. For example, the controller may identify the pixel height of the top surface and use the pixel height along with inner diameter and / or perimeter data to determine the sample volume. In other embodiments, the controller may compare the sensor data and the shape of the top surface with a measurement scale (e.g., measurement line 519) included on the surface of the container. In these embodiments, to improve the ability to detect the measurement line, the controller may be configured to (i) control the sensor to capture sensor data of the container at multiple axial rotation angles; (ii) generate a minimum intensity projection (MIP) of the measurement scale based on the captured sensor data; and (iii) extrapolate the measurement scale to the region associated with the sample (e.g., by applying the techniques described with respect to process 500). Alternatively, the controller may be configured to (i) obtain a stored correspondence between the printed measurement lines of the measurement scale and the corresponding pixel heights, and (ii) align the measurement scale with the region associated with the sample.

[0055] The sample volume can then be used in other processes within the biopharmaceutical manufacturing process. For example, the sample volume can be used to determine the volume of liquid contained in a container. As another example, the sample volume can be used to configure a harvesting process for the sample (such as a centrifugal harvesting process). In some embodiments, the controller is operatively coupled to the centrifuge controller and provides it with the sample volume to assist in the automated configuration of the centrifugation process. In other embodiments, the controller outputs the sample volume for clinicians to configure the centrifugation process. In particular, the sample volume can be used to configure the centrifuge drum discharge interval for stainless steel centrifuges, or the heavy phase (cell discharge / waste) and light phase (supernatant / product) split flow rates for disposable centrifuges.

[0056] It should be understood that while the foregoing describes the application of automated PCV measurement in the manufacturing process of centrifuged biopharmaceutical products, the disclosed technology can be applied to improve other centrifugation processes. For example, the disclosed technology can be applied to measure the volume of blood components during centrifuged blood component analysis.

[0057] We will now address any additional considerations relating to this disclosure.

[0058] Some of the figures described herein illustrate example block diagrams with one or more functional components. It will be understood that such block diagrams are for illustrative purposes, and the devices described and illustrated may have additional, fewer, or alternative components than those shown. Furthermore, in various embodiments, components (and the functionality provided by the respective components) may be associated with or otherwise integrated into any suitable component.

[0059] Embodiments of this disclosure relate to non-transitory computer-readable storage media having computer code on it for performing various computer-implemented operations. The term "computer-readable storage medium" is used herein to include any medium capable of storing or encoding a series of instructions or computer code for performing the operations, methods, and techniques described herein. The medium and computer code may be specifically designed and constructed for the purposes of embodiments of this disclosure, or the medium and computer code may be of a type known and available to those skilled in the art of computer software. Examples of computer-readable storage media include, but are not limited to: magnetic media such as hard disks, floppy disks, and magnetic tapes; optical media such as CD-ROMs and holographic devices; magneto-optical media such as optical discs; and hardware devices specifically configured to store and execute program code, such as ASICs, programmable logic devices ("PLDs"), and ROM and RAM devices.

[0060] Examples of computer code include machine code generated by a compiler, and files containing higher-level code that a computer executes using an interpreter or compiler. For example, embodiments of this disclosure can be implemented using Java, C++, or other object-oriented programming languages ​​and development tools. Additional examples of computer code include encrypted and compressed code. Furthermore, embodiments of this disclosure can be downloaded as a computer program product that can be transmitted via a transmission channel from a remote computer (e.g., a server computer) to a requesting computer (e.g., a client computer or a different server computer). Another embodiment of this disclosure can be implemented using a hardwired circuit system instead of or in combination with machine-executable software instructions.

[0061] As used herein, unless the context clearly indicates otherwise, the singular terms “a”, “an”, and “the” may include plural references.

[0062] As used herein, the terms “approximately,” “substantially,” “basically,” and “about” are used to describe and explain small variations. When used in conjunction with an event or situation, these terms can refer to a situation where the event or situation occurs exactly or approximately. For example, when used in conjunction with a numerical value, these terms can refer to a range of variation where the value is less than or equal to ±10%, such as less than or equal to ±5%, less than or equal to ±4%, less than or equal to ±3%, less than or equal to ±2%, less than or equal to ±1%, less than or equal to ±0.5%, less than or equal to ±0.1%, or less than or equal to ±0.05%. For example, if the difference between values ​​is less than or equal to ±10% of the average of the values, such as less than or equal to ±5%, less than or equal to ±4%, less than or equal to ±3%, less than or equal to ±2%, less than or equal to ±1%, less than or equal to ±0.5%, less than or equal to ±0.1%, or less than or equal to ±0.05%, then the two values ​​can be considered “substantially” the same.

[0063] Additionally, quantities, ratios, and other numerical values ​​are sometimes presented in range format in this document. It should be understood that this range format is used for convenience and brevity, and should be flexibly interpreted to include values ​​explicitly specified as range limits, but also to include all individual values ​​and subranges covered within the range, as if each value or subrange were explicitly specified.

[0064] While this disclosure has been described and illustrated with reference to specific embodiments thereof, such descriptions and illustrations are not intended to limit the scope of this disclosure. Those skilled in the art will understand that various changes and substitutions may be made without departing from the true spirit and scope of this disclosure as defined by the appended claims. These illustrations are not necessarily drawn to scale. Differences may exist between artistic representations in this disclosure and actual installations due to manufacturing processes, tolerances, and / or other reasons. Other embodiments of this disclosure not specifically shown may exist. The specification (other than the claims) and drawings should be considered illustrative rather than restrictive. Modifications may be made to adapt particular circumstances, materials, composition, techniques, or processes to the purpose, spirit, and scope of this disclosure. All such modifications are intended to fall within the scope of the appended claims. While the techniques disclosed herein have been described with reference to specific operations performed in a particular order, it should be understood that these operations may be combined, subdivided, or reordered to form equivalent techniques without departing from the teachings of this disclosure. Therefore, unless specifically indicated herein, the order and grouping of operations are not a limitation of this disclosure.

Claims

1. An automated visual inspection system, comprising: A container holder configured to (i) hold a container containing a sample, and (ii) allow the container to rotate axially. A sensor having a sensing axis passing through the container; as well as The controller, which is operatively coupled to the container holder and the sensor, and is configured to: Control the container holder to rotate the container axially; The sensor is controlled to capture sensor data of the container at multiple axial rotation angles; Analyze the captured sensor data to determine the shape of the top surface of the sample; and The sample volume is determined based on the shape of the top surface.

2. The automatic visual inspection system as described in claim 1, wherein, The sensor is one of a laser line profiler sensor and a laser displacement sensor, and is configured to sense the distance between the sensor and the top surface of the sample.

3. The automatic visual inspection system as described in claim 1, wherein, The sensor is an image sensor, and the automated visual inspection system further includes: A light source is directed to emit illumination toward the image sensor such that the emitted illumination is reflected from the top surface of the sample.

4. The automatic visual inspection system as described in claim 3, wherein, The image sensor further includes a telecentric lens.

5. The automated visual inspection system as described in any one of claims 3 or 4, wherein, The container holder and the sensor are configured such that the sensing axis is offset from the lateral axis of the container.

6. The automated visual inspection system as described in claim 5, wherein, The controller is configured as follows: The captured sensor data is processed to make it vertically aligned.

7. The automated visual inspection system as described in any one of claims 5 or 6, wherein, The controller is configured as follows: The captured sensor data is processed to make it horizontally aligned.

8. The automated visual inspection system as claimed in any one of claims 1 to 7, wherein, To determine the shape of the top surface of the sample, the controller is configured as follows: Determine the height of the leading edge of the top surface of the sample at the various axial rotation angles; and The shape is defined by applying a fitting algorithm to the determined height.

9. The automated visual inspection system as described in claim 8, wherein, The fitting algorithm fits the tilted elliptical shape to the determined height.

10. The automated visual inspection system as described in claim 8, wherein, The fitting algorithm is the minimum energy surface algorithm.

11. The automated visual inspection system as claimed in any one of claims 1 to 10, wherein, To determine the sample volume, the controller is configured as follows: The sensor data and the shape of the top surface are compared with the model of the container.

12. The automated visual inspection system as claimed in any one of claims 1 to 10, wherein, To determine the sample volume, the controller is configured as follows: The sensor data and the shape of the top surface are compared with the measurement scale included on the surface of the container.

13. The automated visual inspection system as claimed in claim 12, wherein, The controller is configured as follows: The sensor is controlled to capture sensor data of the container at multiple axial rotation angles; The minimum intensity projection (MIP) of the measurement scale is generated based on the captured sensor data; and Extrapolate the measurement scale to the region associated with the sample.

14. The automated visual inspection system as described in claim 12, wherein, The controller is configured as follows: Obtain the stored correspondence between the printed measurement lines of the measurement scale and the corresponding pixel heights; and Align the measurement scale with the area associated with the sample.

15. The automated visual inspection system as claimed in any one of claims 1 to 14, wherein, The sample volume is used to configure the harvesting process for that sample.

16. A method for automated analysis of a sample contained in a container, the method comprising: The container holder, which holds the container in place, is controlled by the controller to rotate the container axially. The controller controls the sensors to capture sensor data of the container at multiple axial rotation angles; The controller analyzes the captured sensor data to determine the shape of the top surface of the sample; as well as The sample volume is determined by the controller based on the shape of the top surface.

17. The method of claim 16, wherein, The sensor is an image sensor, and the method further includes: The controller controls the light source to emit illumination toward the image sensor, such that the emitted illumination is reflected from the top surface of the sample.

18. The method of any one of claims 16 or 17, further comprising: The container holder is configured to hold the container at an offset angle relative to an axis orthogonal to the sensing axis of the sensor.

19. The method of claim 18, further comprising: The controller processes the captured sensor data to make it vertically aligned.

20. The method of any one of claims 18 or 19, further comprising: The controller processes the captured sensor data to align it laterally.

21. The method according to any one of claims 16 to 20, wherein, Determining the shape of the top surface of the sample includes: The controller determines the height of the leading edge of the top surface of the sample at the various axial rotation angles; and The controller defines the shape by applying a fitting algorithm to the determined height.

22. The method of claim 21, wherein, The fitting algorithm fits a tilted elliptical shape or a minimum energy surface to a determined height.

23. The method according to any one of claims 16 to 22, wherein, Determining the sample volume includes: The controller compares the sensor data and the shape of the top surface with the model of the container.

24. The method according to any one of claims 16 to 23, wherein, Determining the sample volume includes: The sensor data and the shape of the top surface are compared with the measurement scale included on the surface of the container.

25. The method of claim 24, further comprising: The controller controls the sensor to capture sensor data of the container at multiple axial rotation angles; The controller generates the minimum intensity projection (MIP) of the measurement scale based on the captured sensor data; and The controller projects the measurement scale onto the region associated with the sample.

26. The method of claim 24, further comprising: The controller obtains the stored correspondence between the printed measurement lines of the measurement scale and the corresponding pixel heights. as well as The controller aligns the measurement scale with the area associated with the sample.

27. The method of any one of claims 16 to 26, further comprising: Use this sample volume to configure the harvesting process for this sample.

28. One or more non-transitory computer-readable media storing instructions that, when executed by the processing hardware of a controller, cause the controller to perform the method as described in any one of claims 16 to 27.

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